Research ArticleGIS Based Approach for Vulnerability Assessment ofthe Karnataka Coast India

Akshaya Beluru Jana and Arkal Vittal Hegde

Department of Applied Mechanics and Hydraulics NITK Surathkal Mangaluru 575025 India

Correspondence should be addressed to Akshaya Beluru Jana akshjanagmailcom

Received 16 November 2015 Accepted 17 April 2016

Academic Editor Kirk Hatfield

Copyright copy 2016 A Beluru Jana and A V Hegde This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

The coastal zones are highly resourceful and dynamic In recent times increased events of tropical cyclones and the devastatingimpact of the December 2004 tsunami have brought forth the importance of assessing the vulnerability of the coast to hazard-induced flooding and inundation in coastal areas This study intends to develop coastal vulnerability index (CVI) for theadministrative units known as talukas of the Karnataka state Seven physical and geologic risk variables characterizing thevulnerability of the coast including rate of relative sea level change historical shoreline change coastal slope coastal regionalelevation mean tidal range and significant wave height derived using conventional and remotely sensed data along with onesocioeconomic parameter ldquopopulationrdquo were used in the study A total of 298 km of shoreline are ranked in the study It wasobserved that about 6865 km of the shoreline is under very high vulnerable category and 7926 km of shoreline is under highvulnerable category Of the remaining shoreline 5914 km and 9104 km are of moderate and low vulnerable categories respectively

1 Introduction

Significant changes in environmental and physical processeshave been observed in coastal areas as a result of intensiveurbanization and tourism [1] It has been estimated thathuman population of around 600 million would inhabitcoastal flood plains by the year 2100 [2] Additionally coastalecosystem is being subjected to frequent events of hazardssuch as storms associated waves and storm surges tsunamisriver flooding shoreline erosion and the influx of biohazardslike algal blooms and pollutants [3] Further global climatechange and the threat of accelerated sea level rise haveaggravated the already existing high risks of storm surgessevere waves and tsunamis [3]

Indian main land has a coastline of about 5400 km andaround 250 million people live within 50 km of the coastlineof India [4] In spite of the various policies and regulatoryframeworks Indiarsquos coastal and marine ecosystems are underthreat due to multiple stresses [5] The event of December2004 tsunami brought about importance for scientific studyof the natural hazards and coastal processes of the Indiancoast [6]

Mitigating the effects of potential disasters and having theappropriate infrastructure in place for the response require adetailed knowledge about vulnerability of the places to a widerange of hazards [7] Since vulnerability may be associatedwith natural or social hazards or sometimes a combinationof both various dimensions involving a hazardmust be takeninto account to effectively carry out a vulnerability assessment[8] Various coastal vulnerability assessment methods weredeveloped for managing the coasts which include inundationmaps common methodology (IPCC) and computer aidedmodels Coastal vulnerability index (CVI) developed byThieler and Hammar-Klose [9ndash11] is one of the accepted andmost commonly used indices for calculating the vulnerabilitytowards the coastal erosion and sea level rise The majorityof the studies using CVI have categorized the vulnerabil-ity of different coastal environments relatively using basicinformation on coastal geomorphology rate of sea level risepast shoreline evolution coastal slope mean tidal rangeand mean wave height and acknowledged that inclusion ofdemographic and economic variables may result in a usefuland more comprehensive index [12] Subsequent studies did

Hindawi Publishing CorporationAdvances in Civil EngineeringVolume 2016 Article ID 5642523 10 pageshttpdxdoiorg10115520165642523

2 Advances in Civil Engineering

Shoreline

Karnataka

Maharashtra

Andhra Pradesh

Tamil NaduKerala

Goa

13∘ 0

998400 0998400998400

N13

∘ 30998400 0

998400998400N

14∘ 0

998400 0998400998400

N15

∘ 0998400 0

998400998400N

14∘ 30998400 0

998400998400N

13∘ 45998400 0

998400998400N

13∘ 15998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘559984000998400998400E74∘259984000998400998400E

74∘559984000998400998400E

N

74∘259984000998400998400E

N

Figure 1 Study area

consider the socioeconomic variables for their assessments[13ndash15] Researchers adopted techniques of remote sensingand Geographic Information System (GIS) to assembleassess and display data about various vulnerability variablesand to calculate CVI [6 16ndash18]

Geographic Information System (GIS) handles spatialinformation by linking location with its attribute informa-tion GIS has functions and tools required to efficientlycapture store analyze and display the information aboutplaces and things The preparation of data and mappingthe spatial relationships between natural hazard phenomenaand the elements under threat require the use of GIS Thetechniques of remote sensingGIS andGPShave been provento provide extremely valuable data for analysis of the scenarioand develop management action plans Studies showed thatsatellite remote sensing offered high temporal resolution formonitoring of land-use change at lower costs than thoseassociated with the use of traditional methods [19 20] Theadvantages of repetitive coverage and synoptic view of theregion of interest from various earth observation satelliteshave assisted in generation of databases on various aspectsof the coastal and marine environment [21]

Vulnerabilities associated with the various coastal statesof India are being studied in recent times [6 22ndash27] Fromthe literatures it was noticed that previously Hegde and Reju[18] and Dwarakish et al [28] had assessed the vulnerabilityfor the smaller parts of the Karnataka Coast Both the studieswere limited to a smaller stretch of coast Dwarakish et al

[28] did not include socioeconomic variables for their studyand Hegde and Reju [18] used coastal slope as a supplementto regional elevation Though Appelquist and Balstroslashm [29]had applied the concept of Coastal Hazard Wheel (CHW)framework for the complete coast of the Karnataka theirframework had lacuna of noninclusion of the socioeconomicvariables for the assessment The present study attempts toassess vulnerability of the coastal Karnataka for various haz-ards by combining physical geological and socioeconomicalvariables using techniques of remote sensing and GIS

2 Study Area

The study area (Figure 1) is the coast of Karnataka stateextending from Talpadi to Sadashivgad between longitude74∘51015840220910158401015840E and 74∘511015840537510158401015840E and latitude 14∘531015840365310158401015840Nand 12∘4510158400210158401015840N covering a distance of about 298 km Thecoastal Karnataka consists of the entire stretch of UdupiDakshina Kannada and parts of Uttara Kannada districtsThe coast is bounded by the Western Ghats in the east andthe Arabian Sea on the west and is intercepted with a numberof rivers joining the Arabian Sea Coastal areas near the rivermouths along the study area suffer permanent erosion due tonatural shifting and migration of the river mouths [30] Thetides are of mixed semidiurnal type and its range increasestowards the north of the state [31] Significant wave heightduring the monsoon has been assessed to be greater than3m [6] and is normally less than 15m during the rest of

Advances in Civil Engineering 3

Table 1 List of variables and data source

Variables Data source Time periodSea level change rate PSMSL (httpwwwpsmslorg) 1976ndash2004Shoreline change rate Earth Explorer (httpearthexplorerusgsgov) 1972ndash2014Coastal slope GEBCO (httpwwwgebconet) mdashRegional elevation SRTM (httpsrtmcsicgiarorg) mdashTidal range Secondary data mdashSignificant wave height Secondary data mdashPopulation Worldpop (httpwwwworldpoporguk) 2010

the year Deep-water waves approach the coast from south-western and north-western directions [6]

The northern part of the study area is geologically com-posed of Precambrian crystalline gneiss schist and graniterocks fronted by a narrow coastal plain of alluvial or tertiarydeposits In locations where the rock extends to the coastlinecoastal cliffs and rocky shores are formed The coastline hasdrowned river valleys estuaries andmany small inlets whichis a typical submergence characteristic [32] The southernpart of study area has extensive straight beaches and estuarieswith low estuarine islands and mangroves

3 Methodology

The present study adopts the CVI methodology formulatedby Thieler and Hammer-Klose [9ndash11] The process resultsin a classification of coast using simple criteria and yieldsnumerical data that cannot be equated directly with par-ticular physical effects but shows the arearsquos most affectedby the hazard Initially a database of the variables underconsideration for the study area was built by compiling datafrom various sources Table 1 details the variables and theirdata sources used in the present study The data values ofvariables under consideration were assigned a vulnerabilityranking based on value ranges contributing to coastal vul-nerability while the nonnumerical geomorphology variablewas ranked qualitatively according to the relative resistanceof a given landform to erosion Later the key variables wereintegrated to a single index and categorized based on therelative intensity of risk it imparts to the coast namely verylow low medium high and very high The entire coastlinewas divided into 8 zones based on administrative boundaryof talukas A grid template of 15 km by 15 km was used tostore and analyze data and display the CVI similar to theprocedure adopted by Abuodha and Woodroffe [33] Eachcell of the grid template was assigned with an identificationnumber as shown in Figure 2 The software package ArcGIS93 offers the suitable environment to carry out the processThe variation of each variable within the area was analyzedand suitable risk ratings were awarded for each specific datavariable and the coastal vulnerability index was calculated

In the present study eight variables were considered fordeveloping the CVI rate of relative sea level change histor-ical rate of shoreline change (erosion or accretion) coastalregional elevation coastal slope mean tidal range significantwave height and socioeconomic dataThe importance of each

up11

up08

up01

up02

up10

up12

up13

up07

up06

up09

up03

up04

up05

up14

mn25

mn24

mn23

Karnataka

Arabian Sea

N

Figure 2 Grid template for the study area

of the considered parameters and the procedure to generatethe same for use in assessment of CVI are given in thefollowing section

31 Relative Sea Level Change Rate Sea level rise shifts thewave action zone to higher elevations due to recession ofcoast to inland This recession of shoreline will be greater inmild slope regions [34] The direct effect of such recessionis submergence of coastal land and aggravated events offlooding Long-term effects can be increased erosion and salt-water intrusion into ground water as the coast adjusts to thenew conditions [35] According to IPCC every millimeterrise of mean sea level on the coast would result in a shorelineretreat of about 1mMean sea level at the coast is the height ofthe sea with respect to a local land benchmark averaged overa long time period Changes inmean sea level as measured bycoastal tide gauges are called relative sea level changes [36]

4 Advances in Civil Engineering

The Permanent Service for Mean Sea Level (PSMSL)data has been used in the study to calculate the relative sealevel change rate The study area consists of two PSMSL tidegauge stations namely Mangaluru and KarwarThe monthlymean sea level data from 1976 to 2000 are downloaded forMangaluru station and from 1970 to 2004 for the Karwarstation from the PSMSLwebsiteThemonthlymean values ofsea level recorded at these stations were plotted from whicha linear best fit line adopting least squares method was com-puted to calculate the sea level change rate and risk ratingswere assigned Coast subjected to a high rate of sea level risewas considered as a high vulnerable area and vice versa

32 Shoreline Change Rate The shoreline change rate is oneof the most common measurements used to indicate thedynamics and the hazards of the coast [41] Coastal shorelinesare always subjected to changes due to coastal processeswhich are controlled by wave characteristics and the resultantnear-shore circulation sediment characteristics beach formand so forth From the coastal vulnerability point of viewcoasts subjected to accretion are considered as less vulnerableareas as they move towards the ocean and result in theaddition of land areas whereas areas of coastal erosion areconsidered to be more vulnerable because of the resultantloss of individual and public property as well as importantnatural habitats It also trims down the distance betweencoastal population and ocean thereby increasing the risk ofexposure of population to coastal hazards

Orthorectified satellite images of the study area from thesensors LandsatMSS ETM+andOLI-TIRS for the years 19721991 1998 2000 2006 2012 and 2014 were downloaded fromUSGS Earth Explorer web tool The images were projected tothe Universal Transverse Mercator (UTM) projection systemwith WGS-84 datum Histogram splicing was applied tocreate a binary image from near infrared band of each imageand is classified as unsupervised to form image with completeseparation between land and water classes These classifiedimages were used to extract the shorelines in the form ofvector layer using ERDAS Imagine 92 and ArcMap 93

Thedigitized shoreline for the years 1972 1991 1998 20002006 2012 and 2014 in the vector format was used as theinput to the Digital Shoreline Analysis System (DSAS) DSAScomputes rate-of-change statistics from multiple historicshoreline positions by using GIS [42] Transects were castperpendicular to the baseline at a 100m interval all alongthe shore using DSAS The crossover of these transects withshoreline along the baseline is then used to calculate the rate-of-change statistics Linear Regression Rate (LRR) method ofshoreline change rate estimation was used in this study LRRuses all the available data to find a line which has the overallminimumof the squared distance to the known shoreline andis an established method for computing long-term rates ofshoreline change [43] Risk ratings were assigned based onthe LRR

33 Coastal Slope The coastal slope is change in altitude fora unit horizontal distance between any two points on thecoast The degree of steepness or flatness of a coastal regiondetermines the susceptibility of the coast to inundation by

Table 2 Tidal range for various zones and their source

Location Tidal range (m) SourceKarwar Ankola amp Kumta 158 Kumar et al [37]Honnavar 21

Sanil Kumar et al [38]Kundapur amp Bhatkal 19Udupi (Malpe) 18Mangaluru 16 Dwarakish et al [28]

flooding [44] Determination of regional coastal slope iden-tifies the relative vulnerability of inundation and potentialrapidity of shoreline retreat because low sloping coastalregions are thought to retreat faster than steeper regions [17]

General Bathymetric Chart of the Oceans (GEBCO)data of 30-arc seconds grid resolution coastal topographyand bathymetry has been used to get the regional slope ofthe coastal area GEBCO also incorporates land elevationsderived from the Global Land One-kilometer Base Elevationproject data set GEBCO data sets are useful in deriving thecoastal slope values both on land and in the ocean 3D analysttool of ArcGIS 93 was used in preparing the coastal slopemap Coastal areas having gentle slope were considered ashighly vulnerable areas and areas of steep slope as areas oflow vulnerability

34 Regional Elevation It is important to study the coastalregional elevation detail in the study area to identify andestimate the extent of land area threatened by future sea levelriseThese coastal elevation data are also used to estimate theland potentially available for wetland migration in responseto sea level rise and the sea level rise impacts on thehuman built environment [45] From the coastal vulnerabilitypoint of view coastal regions having high elevation will beconsidered as less vulnerable areas because they providemoreresistance for inundation against the rising sea level tsunamirun-up and storm surge

Those coastal regions having low elevation are consideredas highly vulnerable areas In the present study Shuttle RadarTopography Mission (SRTM) data was used to derive thecoastal regional elevation A zonal statistical analysis wascarried out using ArcGIS and elevation in each grid cell wasdetermined and risk rating was awarded

35 Tidal Range The tidal range is the vertical differencebetween the highest high tide and the lowest low tide Fromthe vulnerability point of view it is an obvious tendency todesignate coastal areas of high tidal range as highly vulner-able This decision is based on the concept that large tidalrange is associated with strong tidal currents that influencecoastal behavior For the current study coastal areas withhigh tidal range are considered as highly vulnerable and lowtidal range as less vulnerable Previously studies were carriedout at various locations of the study area and the tidal rangehas been determined [28 31 37] Table 2 lists the details ofthe studies and the tidal range This secondary data was alsoconsidered for calculations

Advances in Civil Engineering 5

Table 3 Mean significant wave height for different talukas as collected from the literatures

Location Mean significant wave height (m) SourceKarwar Ankola amp Kumta 16 Kumar et al [31]Honnavar 19 Kumar et al [31]Kundapur 10 Shanas and Sanil Kumar [39]Bhatkal 125 Nayak et al [40]Udupi (Malpe) 19 Kumar et al [31]Mangaluru 20 Dwarakish et al [28]

36 Significant Wave Height Significant wave height is theaverage height of the one-third highest waves valid for theindicated 12-hour period Mean significant wave height isused as a proxy for wave energy that drives coastal sedimenttransport [46] The vulnerability study based on wave heightis an important step in setting up an all-hazards warning andmanagement system [46]

The movement and transport of coastal sediments aredependent upon the wave energy which varies as the squareof the wave height [47] With increase in the wave height andeventual increase in wave energy land is lost and coast willwitness increased erosion and inundation along the shoreHence the coastal areas of high wave height are consideredas more vulnerable coasts and areas of low wave height asless vulnerable coasts In the present study wave heights inthe study area were collected from the various other studiesconducted primarily onwave characteristics in the study areaTable 3 shows the details of the data collected

37 Population Coastal region has high population densitycompared to upland areas Population can also be interpretedas a direct ldquoerosion-inducingrdquo variable because the presenceof large number of people near the coast may producedamaging impacts on the coastal area [48] Hence presenceof human habitation increases the vulnerability of the regionIn the present study the population was considered as apressure exerting factor on the coastal system and hence areaswith a higher concentration of people are considered as moresusceptible to erosion similar to Hegde and Reju [18]

Worldpop project provides high resolution and contem-porary data on human population distributions for SoutheastAsian countries in raster data format An alpha version dataestimated to match UN population estimate for the year2015 was used in the present study The data set is of rasterformat with resolution of 100m at the equator The assembleof the Worldpop spatial data sets principally follows themethodologies outlined by Gaughan et al [49] Linard et al[50] Linard et al [51] and Tatem et al [52]

38 Calculation of CVI Once each section of coastline isassigned a risk value for each variable the CVI is calculated asthe square root of the product of the ranked variables dividedby the total number of variables [17] The CVI is representedby

CVI = radic119886 lowast 119887 lowast 119888 lowast 119889 lowast 119890 lowast 119891 lowast 119892

7

(1)

where 119886 = risk rating assigned to sea level change rate 119887 =risk rating assigned to shoreline change rate 119888 = risk ratingassigned to coastal slope 119889 = risk rating assigned to coastalregional elevation 119890 = risk rating assigned to tidal range 119891 =risk rating assigned to significant wave height and 119892 = riskrating assigned to population density

4 Results and Discussion

41 Relative Sea Level Change Rate For the available datait was observed that sea level was falling at a rate of 13mmper year at the Karwar station while it was rising at a rate of08mmper year at theMangaluru station as shown in Figures3(a) and 3(b) respectively Douglas [53] acknowledged thatto determine the trends in long-term sea level changes idealrecord length greater than 60 years is desirable Since suchlong duration records were not available for the present studyregion the tide gauge data of Cochin (64 years) was alsoconsidered to verify the trend of SLR and it was observed thatsea level rise was about 10mm per year

Unnikrishnan and Shankar [54] estimated that the sealevel along the Indian coast has increased at a rate varyingbetween 106 and 175mm per year during the period 1969to 2007 depending on the tide gauge recording site with anestimated regional average of 129mmper year subsequent toa global isostatic adjustment correctionThe SLR observed atthe study area is less in comparisonwith global average rate ofabout 17mmper year [55] and also less than regional averageHence the study area is considered to be less vulnerable to sealevel rise and lowest ranking of 1 was awarded for the entirecoast

42 Coastal Slope The regional coastal slope was calculatedfor a distance of 6 km (3 km each from shoreline on seaand landside) perpendicular to the shoreline at an intervalof 15 km The five vulnerability classes and the slope rangein each class are adopted by Pendleton et al [56] A slopegreater than 06 is assigned low vulnerability and less than03 is assigned high vulnerability as shown in Table 4 andaccordingly vulnerability ranks (indicating the vulnerabilitylevels in terms of coastal slope) are assigned to all segmentsof the coast

43 Regional Elevation The mean regional elevation withinstudy area varied between 069m in Mangaluru and 7894min Karwar An elevation value greater than 40m is assignedlow vulnerability and less than 10m is assigned high vul-nerability as shown in Table 4 The minimum value of 10m

6 Advances in Civil Engineering

Sea levelTrend line

y = (minus2658E minus 7)x + 7649

06-2003

06-2008

06-2013

06-1988

06-1983

06-1998

06-1978

06-1973

06-1993

06-1968

Date (mm-yyy)

66

69

72

75

78

81Se

a lev

el (m

)

(a)

81

78

75

72

69

66

Sea l

evel

(m)

y = (4303E minus 6)x minus 3457

06-2004

06-2009

06-1989

06-1984

06-1999

06-1979

06-1994

06-1974

Date (mm-yyy)

Sea levelTrend line

(b)Figure 3 (a) Sea Level variation at Karwar (b) Sea Level variation at Mangaluru

Table 4 Ranges of variables for vulnerability ranking

Variable Ranking of vulnerability1 2 3 4 5

Coastal slope () gt060 05ndash06 04ndash05 03ndash04 lt03Mean tide range (m) lt10 10ndash20 20ndash30 30ndash40 gt40Regional elevation (m) lt10 10ndash20 20ndash30 30ndash40 gt40Shoreline change rate (m yearminus1) gt+20 +10 to +20 minus10 to +10 minus20 to minus10 ltminus20Mean significant wave height (m) lt07 07ndash14 14ndash21 21ndash28 gt28Population (person per 200m2) lt19 44ndash20 80ndash45 326ndash81 gt326

was considered based on the Indian Ocean earthquake of 26December 2004 of magnitude 90 on the Richter scale whichresulted in devastating tsunami along the shores of IndonesiaSri Lanka South India Thailand and other countries withwaves up to 15m high

44 Tidal Range Tidal range is ranked such that microtidal(lt1m) coasts have very low vulnerability and macrotidal(gt6m) coasts have a very high vulnerabilityThe vulnerabilityranking given is taken from the vulnerability ranges of Diezet al [57]The study area is characterized by mesotidal coastsas the tidal range is within 6m but greater than 1m Entirestudy area has fallen into two categories namely very lowvulnerable level (lt10m) and low vulnerable level (10 to20m) as far as the tidal range is considered Accordinglythe entire coast is classified into these two vulnerabilitycategories

45 SignificantWave Height (SWH) Mean SWH in the studyarea varied between 10m and 20m The vulnerability levelswere adopted by Dwarakish et al [28] Kundapur was havinga lowest SWH of 10m while Mangaluru had highest SWH of20m It was assumed that the mean SWH was as per Table 3within the limits of corresponding talukas

46 Shoreline Change Rate The shoreline change rate in thestudy area was calculated for a period of 42 years (1972 to2014) The Output from DSAS revealed that about 409 km

kw05

akw

11kw

16kw

22ak03

aak09

km05

km11

km17

km23

hn06

hn12

bt02

bt08

bt14

kd03

kd09

kd15

kd21

kd27

up05

up11

up17

up23

up29

mn0

2m

n08

mn1

4m

n20minus6

minus4

minus2

0

2

4

6

8

10

Grid ID

LRR

(m ye

arminus

1 )

Figure 4 Mean shoreline change rate along the grids

of coastline had a very high risk rating along the coastalstretch of southern Mangaluru About 1425 km of coastlinewas of high risk rating along the coastal stretches nearsouthern parts of Mangaluru Kundapur and Kumta and alsoin northern Udupi and Bhatkal About 26750 km of coastlinewas under amoderate riskwhile 15 and 1066 km stretchwereunder low and very low risk category respectively Averageaccretion for the whole of the study area was found to be1133m per year and average erosion was 0533m per yearFigure 4 shows the mean shoreline change rate in each grid

Advances in Civil Engineering 7

CVI CVI173ndash450451ndash670

671ndash10391040ndash1897

Karwar Ankola

Kumta Honnavar

Bhatkal

Udupi

Kundapur

Mangaluru

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E 74∘209984000998400998400E74∘159984000998400998400E

74∘209984000998400998400E74∘159984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N 14∘ 40998400 0

998400998400N

14∘ 40998400 0

998400998400N

14∘ 20998400 0

998400998400N

14∘ 15998400 0

998400998400N

14∘ 10998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘259984000998400998400E74∘159984000998400998400E

74∘259984000998400998400E74∘159984000998400998400E

14∘ 35998400 0

998400998400N

14∘ 25998400 0

998400998400N 14∘ 30998400 0

998400998400N

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

13∘ 20998400 0

998400998400N

13∘ 30998400 0

998400998400N

13∘ 10998400 0

998400998400N

13∘ 25998400 0

998400998400N

13∘ 15998400 0

998400998400N

173ndash450451ndash670

671ndash10391040ndash1897

Figure 5 CVI for study area

8 Advances in Civil Engineering

Table 5 CVI for talukas

Taluka CVIMax Min Average 120590

Karwar 1897 424 604 336Ankola 948 367 644 237Kumta 948 367 628 187Honnavar 734 367 520 146Bhatkal 774 173 534 165Kundapur 800 244 589 121Udupi 979 600 778 241Mangaluru 1549 489 794 094

along the study area The risk ranking was awarded basedon the risk category formed by Pendleton et al [56] and isdescribed in Table 4

47 Population Distribution Georeferenced populationraster downloaded from Worldpop project has data valuesvarying from 0 to 326 persons per 200m2 for the study areaThe population is considered to be a stressor variable in thestudy It was assumed that vulnerability varied exponentiallywith population density and the data was classified into 5classes The zones with values equal to or less than 19 personsper 200m2 were awarded with least ranking and regionswith value equal to or more than a value of 326 persons per200m2 were considered as highly vulnerable and highestrank was assigned Table 4 shows the intermediate values forother classes

Coastal Vulnerability Index (CVI) Coastal vulnerability indexmap for the Karnataka Coast is shown in Figure 5 Thecalculated CVI values range from 173 to 1897 Table 5 detailsthe CVI for each taluk with statistical parameters The meanmode andmedian CVI values are 652 734 and 692 respec-tively The standard deviation is 221 The CVI scores aredivided into low moderate high and very high vulnerabilitycategories based on the quartile ranges [56] The 25th 50thand 75th percentiles are 490 692 and 735 respectively Thelower range of CVI values indicates low risk followed bymoderate risk high risk and finally the upper range of valuesindicating the coastal stretches having very high risk

The present study is an attempt to categorize the coast ofKarnataka according to its coastal vulnerabilities The vari-ables under consideration are sea level change coastal sloperegional elevation tidal range significant wave height andpopulation density A total of 298 km of shoreline are rankedin the study About 6865 km of the shoreline is very high vul-nerable category and 7926 km of shoreline is high vulnerablecategory Of the remaining shoreline 5914 km and 9104 kmare of moderate and low vulnerable categories respectively

Table 5 shows variation of CVI for each talukaThe coastsof Mangaluru and Udupi fall under high risk category andall other talukas are under moderate risk The CVI in thepresent study was primarily influenced by the risk rankingof the shoreline change rate population and the coastalslope It was observed that coasts of Mangaluru Kumta and

Bhatkal were under erosion with an average value of 021013 and 014m per year respectively while for other talukasaccretion was observed The sensitivity of the CVI to thesocioeconomic variable ldquopopulationrdquo was examined and itwas found that CVI significantly decreased in the talukasof Mangaluru Udupi and Karwar on omission of variableand on a relative basis The coastal slope was observed tobe steep in northern talukas that is in Karwar Ankola andKumta while Kundapur Udupi and Mangaluru had mildslope topography This was primarily because in KarwarAnkola andKumtawe find the headlands and cliffs very closeto the coast and southern talukas have more open beaches

5 Conclusion

In the view of the rising sea levels and other coastal hazardsan assessment of coast for its vulnerability to these threatsis necessary in order to take suitable actions to protect thepeople and property It was observed that 6865 km of theshoreline of the study area was under very high vulnerablecategory and 7926 km of shoreline is high vulnerable cate-gory while 5914 km and 9104 km of coast are of moderateand low vulnerable categories respectively Present study alsoevaluated the transformation of theKarnataka coastline usingLandsat satellite images The CVI developed in the presentstudy provides an understanding about the vulnerability ofthe Karnataka Coast to erosion coastal flooding and relativesea level change and as well as facilitates policy options forcoastal planners and authorities with regard to prioritizingcoastal areas for mitigation

Competing Interests

The present study is a work of pure academic researchThe authors declare that there are no competing interestsregarding the publication of this paper

References

[1] F L Alves C Coelho C D Coelho and P Pinto ldquoModellingcoastal vulnerabilities tool for decision support system at inter-municipality levelrdquo Journal of Coastal Research no 64 pp 966ndash970 2011

[2] R J Nicholls and N Mimura ldquoRegional issues raised by sea-level rise and their policy implicationsrdquo Climate Research vol11 no 1 pp 5ndash18 1999

[3] IPCC (Intergovernmental Panel on Climate Change) IPCCReport Working Group-I Climate Change 2001 The ScientificBasis Cambridge University Press Cambridge UK 2001httpwwwipccchipccreportstarwg1408htm

[4] ICZMP ldquoDocument of world bankmdashproject appraisaldocument for an integrated coastal zone management projectrdquoReport 54612-IN Integrated Coastal Zone Management2010 httpwwwsicommoefinDataSites1skinsgec-sicomimagesdocspadpdf

[5] N N V Sudha Rani A N V Satyanarayana and P KBhaskaran ldquoCoastal vulnerability assessment studies overIndia a reviewrdquo Natural Hazards vol 77 no 1 pp 405ndash4282015

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

2 Advances in Civil Engineering

Shoreline

Karnataka

Maharashtra

Andhra Pradesh

Tamil NaduKerala

Goa

13∘ 0

998400 0998400998400

N13

∘ 30998400 0

998400998400N

14∘ 0

998400 0998400998400

N15

∘ 0998400 0

998400998400N

14∘ 30998400 0

998400998400N

13∘ 45998400 0

998400998400N

13∘ 15998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘559984000998400998400E74∘259984000998400998400E

74∘559984000998400998400E

N

74∘259984000998400998400E

N

Figure 1 Study area

consider the socioeconomic variables for their assessments[13ndash15] Researchers adopted techniques of remote sensingand Geographic Information System (GIS) to assembleassess and display data about various vulnerability variablesand to calculate CVI [6 16ndash18]

Geographic Information System (GIS) handles spatialinformation by linking location with its attribute informa-tion GIS has functions and tools required to efficientlycapture store analyze and display the information aboutplaces and things The preparation of data and mappingthe spatial relationships between natural hazard phenomenaand the elements under threat require the use of GIS Thetechniques of remote sensingGIS andGPShave been provento provide extremely valuable data for analysis of the scenarioand develop management action plans Studies showed thatsatellite remote sensing offered high temporal resolution formonitoring of land-use change at lower costs than thoseassociated with the use of traditional methods [19 20] Theadvantages of repetitive coverage and synoptic view of theregion of interest from various earth observation satelliteshave assisted in generation of databases on various aspectsof the coastal and marine environment [21]

Vulnerabilities associated with the various coastal statesof India are being studied in recent times [6 22ndash27] Fromthe literatures it was noticed that previously Hegde and Reju[18] and Dwarakish et al [28] had assessed the vulnerabilityfor the smaller parts of the Karnataka Coast Both the studieswere limited to a smaller stretch of coast Dwarakish et al

[28] did not include socioeconomic variables for their studyand Hegde and Reju [18] used coastal slope as a supplementto regional elevation Though Appelquist and Balstroslashm [29]had applied the concept of Coastal Hazard Wheel (CHW)framework for the complete coast of the Karnataka theirframework had lacuna of noninclusion of the socioeconomicvariables for the assessment The present study attempts toassess vulnerability of the coastal Karnataka for various haz-ards by combining physical geological and socioeconomicalvariables using techniques of remote sensing and GIS

2 Study Area

The study area (Figure 1) is the coast of Karnataka stateextending from Talpadi to Sadashivgad between longitude74∘51015840220910158401015840E and 74∘511015840537510158401015840E and latitude 14∘531015840365310158401015840Nand 12∘4510158400210158401015840N covering a distance of about 298 km Thecoastal Karnataka consists of the entire stretch of UdupiDakshina Kannada and parts of Uttara Kannada districtsThe coast is bounded by the Western Ghats in the east andthe Arabian Sea on the west and is intercepted with a numberof rivers joining the Arabian Sea Coastal areas near the rivermouths along the study area suffer permanent erosion due tonatural shifting and migration of the river mouths [30] Thetides are of mixed semidiurnal type and its range increasestowards the north of the state [31] Significant wave heightduring the monsoon has been assessed to be greater than3m [6] and is normally less than 15m during the rest of

Advances in Civil Engineering 3

Table 1 List of variables and data source

Variables Data source Time periodSea level change rate PSMSL (httpwwwpsmslorg) 1976ndash2004Shoreline change rate Earth Explorer (httpearthexplorerusgsgov) 1972ndash2014Coastal slope GEBCO (httpwwwgebconet) mdashRegional elevation SRTM (httpsrtmcsicgiarorg) mdashTidal range Secondary data mdashSignificant wave height Secondary data mdashPopulation Worldpop (httpwwwworldpoporguk) 2010

the year Deep-water waves approach the coast from south-western and north-western directions [6]

The northern part of the study area is geologically com-posed of Precambrian crystalline gneiss schist and graniterocks fronted by a narrow coastal plain of alluvial or tertiarydeposits In locations where the rock extends to the coastlinecoastal cliffs and rocky shores are formed The coastline hasdrowned river valleys estuaries andmany small inlets whichis a typical submergence characteristic [32] The southernpart of study area has extensive straight beaches and estuarieswith low estuarine islands and mangroves

3 Methodology

The present study adopts the CVI methodology formulatedby Thieler and Hammer-Klose [9ndash11] The process resultsin a classification of coast using simple criteria and yieldsnumerical data that cannot be equated directly with par-ticular physical effects but shows the arearsquos most affectedby the hazard Initially a database of the variables underconsideration for the study area was built by compiling datafrom various sources Table 1 details the variables and theirdata sources used in the present study The data values ofvariables under consideration were assigned a vulnerabilityranking based on value ranges contributing to coastal vul-nerability while the nonnumerical geomorphology variablewas ranked qualitatively according to the relative resistanceof a given landform to erosion Later the key variables wereintegrated to a single index and categorized based on therelative intensity of risk it imparts to the coast namely verylow low medium high and very high The entire coastlinewas divided into 8 zones based on administrative boundaryof talukas A grid template of 15 km by 15 km was used tostore and analyze data and display the CVI similar to theprocedure adopted by Abuodha and Woodroffe [33] Eachcell of the grid template was assigned with an identificationnumber as shown in Figure 2 The software package ArcGIS93 offers the suitable environment to carry out the processThe variation of each variable within the area was analyzedand suitable risk ratings were awarded for each specific datavariable and the coastal vulnerability index was calculated

In the present study eight variables were considered fordeveloping the CVI rate of relative sea level change histor-ical rate of shoreline change (erosion or accretion) coastalregional elevation coastal slope mean tidal range significantwave height and socioeconomic dataThe importance of each

up11

up08

up01

up02

up10

up12

up13

up07

up06

up09

up03

up04

up05

up14

mn25

mn24

mn23

Karnataka

Arabian Sea

N

Figure 2 Grid template for the study area

of the considered parameters and the procedure to generatethe same for use in assessment of CVI are given in thefollowing section

31 Relative Sea Level Change Rate Sea level rise shifts thewave action zone to higher elevations due to recession ofcoast to inland This recession of shoreline will be greater inmild slope regions [34] The direct effect of such recessionis submergence of coastal land and aggravated events offlooding Long-term effects can be increased erosion and salt-water intrusion into ground water as the coast adjusts to thenew conditions [35] According to IPCC every millimeterrise of mean sea level on the coast would result in a shorelineretreat of about 1mMean sea level at the coast is the height ofthe sea with respect to a local land benchmark averaged overa long time period Changes inmean sea level as measured bycoastal tide gauges are called relative sea level changes [36]

4 Advances in Civil Engineering

The Permanent Service for Mean Sea Level (PSMSL)data has been used in the study to calculate the relative sealevel change rate The study area consists of two PSMSL tidegauge stations namely Mangaluru and KarwarThe monthlymean sea level data from 1976 to 2000 are downloaded forMangaluru station and from 1970 to 2004 for the Karwarstation from the PSMSLwebsiteThemonthlymean values ofsea level recorded at these stations were plotted from whicha linear best fit line adopting least squares method was com-puted to calculate the sea level change rate and risk ratingswere assigned Coast subjected to a high rate of sea level risewas considered as a high vulnerable area and vice versa

32 Shoreline Change Rate The shoreline change rate is oneof the most common measurements used to indicate thedynamics and the hazards of the coast [41] Coastal shorelinesare always subjected to changes due to coastal processeswhich are controlled by wave characteristics and the resultantnear-shore circulation sediment characteristics beach formand so forth From the coastal vulnerability point of viewcoasts subjected to accretion are considered as less vulnerableareas as they move towards the ocean and result in theaddition of land areas whereas areas of coastal erosion areconsidered to be more vulnerable because of the resultantloss of individual and public property as well as importantnatural habitats It also trims down the distance betweencoastal population and ocean thereby increasing the risk ofexposure of population to coastal hazards

Orthorectified satellite images of the study area from thesensors LandsatMSS ETM+andOLI-TIRS for the years 19721991 1998 2000 2006 2012 and 2014 were downloaded fromUSGS Earth Explorer web tool The images were projected tothe Universal Transverse Mercator (UTM) projection systemwith WGS-84 datum Histogram splicing was applied tocreate a binary image from near infrared band of each imageand is classified as unsupervised to form image with completeseparation between land and water classes These classifiedimages were used to extract the shorelines in the form ofvector layer using ERDAS Imagine 92 and ArcMap 93

Thedigitized shoreline for the years 1972 1991 1998 20002006 2012 and 2014 in the vector format was used as theinput to the Digital Shoreline Analysis System (DSAS) DSAScomputes rate-of-change statistics from multiple historicshoreline positions by using GIS [42] Transects were castperpendicular to the baseline at a 100m interval all alongthe shore using DSAS The crossover of these transects withshoreline along the baseline is then used to calculate the rate-of-change statistics Linear Regression Rate (LRR) method ofshoreline change rate estimation was used in this study LRRuses all the available data to find a line which has the overallminimumof the squared distance to the known shoreline andis an established method for computing long-term rates ofshoreline change [43] Risk ratings were assigned based onthe LRR

33 Coastal Slope The coastal slope is change in altitude fora unit horizontal distance between any two points on thecoast The degree of steepness or flatness of a coastal regiondetermines the susceptibility of the coast to inundation by

Table 2 Tidal range for various zones and their source

Location Tidal range (m) SourceKarwar Ankola amp Kumta 158 Kumar et al [37]Honnavar 21

Sanil Kumar et al [38]Kundapur amp Bhatkal 19Udupi (Malpe) 18Mangaluru 16 Dwarakish et al [28]

flooding [44] Determination of regional coastal slope iden-tifies the relative vulnerability of inundation and potentialrapidity of shoreline retreat because low sloping coastalregions are thought to retreat faster than steeper regions [17]

General Bathymetric Chart of the Oceans (GEBCO)data of 30-arc seconds grid resolution coastal topographyand bathymetry has been used to get the regional slope ofthe coastal area GEBCO also incorporates land elevationsderived from the Global Land One-kilometer Base Elevationproject data set GEBCO data sets are useful in deriving thecoastal slope values both on land and in the ocean 3D analysttool of ArcGIS 93 was used in preparing the coastal slopemap Coastal areas having gentle slope were considered ashighly vulnerable areas and areas of steep slope as areas oflow vulnerability

34 Regional Elevation It is important to study the coastalregional elevation detail in the study area to identify andestimate the extent of land area threatened by future sea levelriseThese coastal elevation data are also used to estimate theland potentially available for wetland migration in responseto sea level rise and the sea level rise impacts on thehuman built environment [45] From the coastal vulnerabilitypoint of view coastal regions having high elevation will beconsidered as less vulnerable areas because they providemoreresistance for inundation against the rising sea level tsunamirun-up and storm surge

Those coastal regions having low elevation are consideredas highly vulnerable areas In the present study Shuttle RadarTopography Mission (SRTM) data was used to derive thecoastal regional elevation A zonal statistical analysis wascarried out using ArcGIS and elevation in each grid cell wasdetermined and risk rating was awarded

35 Tidal Range The tidal range is the vertical differencebetween the highest high tide and the lowest low tide Fromthe vulnerability point of view it is an obvious tendency todesignate coastal areas of high tidal range as highly vulner-able This decision is based on the concept that large tidalrange is associated with strong tidal currents that influencecoastal behavior For the current study coastal areas withhigh tidal range are considered as highly vulnerable and lowtidal range as less vulnerable Previously studies were carriedout at various locations of the study area and the tidal rangehas been determined [28 31 37] Table 2 lists the details ofthe studies and the tidal range This secondary data was alsoconsidered for calculations

Advances in Civil Engineering 5

Table 3 Mean significant wave height for different talukas as collected from the literatures

Location Mean significant wave height (m) SourceKarwar Ankola amp Kumta 16 Kumar et al [31]Honnavar 19 Kumar et al [31]Kundapur 10 Shanas and Sanil Kumar [39]Bhatkal 125 Nayak et al [40]Udupi (Malpe) 19 Kumar et al [31]Mangaluru 20 Dwarakish et al [28]

36 Significant Wave Height Significant wave height is theaverage height of the one-third highest waves valid for theindicated 12-hour period Mean significant wave height isused as a proxy for wave energy that drives coastal sedimenttransport [46] The vulnerability study based on wave heightis an important step in setting up an all-hazards warning andmanagement system [46]

The movement and transport of coastal sediments aredependent upon the wave energy which varies as the squareof the wave height [47] With increase in the wave height andeventual increase in wave energy land is lost and coast willwitness increased erosion and inundation along the shoreHence the coastal areas of high wave height are consideredas more vulnerable coasts and areas of low wave height asless vulnerable coasts In the present study wave heights inthe study area were collected from the various other studiesconducted primarily onwave characteristics in the study areaTable 3 shows the details of the data collected

37 Population Coastal region has high population densitycompared to upland areas Population can also be interpretedas a direct ldquoerosion-inducingrdquo variable because the presenceof large number of people near the coast may producedamaging impacts on the coastal area [48] Hence presenceof human habitation increases the vulnerability of the regionIn the present study the population was considered as apressure exerting factor on the coastal system and hence areaswith a higher concentration of people are considered as moresusceptible to erosion similar to Hegde and Reju [18]

Worldpop project provides high resolution and contem-porary data on human population distributions for SoutheastAsian countries in raster data format An alpha version dataestimated to match UN population estimate for the year2015 was used in the present study The data set is of rasterformat with resolution of 100m at the equator The assembleof the Worldpop spatial data sets principally follows themethodologies outlined by Gaughan et al [49] Linard et al[50] Linard et al [51] and Tatem et al [52]

38 Calculation of CVI Once each section of coastline isassigned a risk value for each variable the CVI is calculated asthe square root of the product of the ranked variables dividedby the total number of variables [17] The CVI is representedby

CVI = radic119886 lowast 119887 lowast 119888 lowast 119889 lowast 119890 lowast 119891 lowast 119892

7

(1)

where 119886 = risk rating assigned to sea level change rate 119887 =risk rating assigned to shoreline change rate 119888 = risk ratingassigned to coastal slope 119889 = risk rating assigned to coastalregional elevation 119890 = risk rating assigned to tidal range 119891 =risk rating assigned to significant wave height and 119892 = riskrating assigned to population density

4 Results and Discussion

41 Relative Sea Level Change Rate For the available datait was observed that sea level was falling at a rate of 13mmper year at the Karwar station while it was rising at a rate of08mmper year at theMangaluru station as shown in Figures3(a) and 3(b) respectively Douglas [53] acknowledged thatto determine the trends in long-term sea level changes idealrecord length greater than 60 years is desirable Since suchlong duration records were not available for the present studyregion the tide gauge data of Cochin (64 years) was alsoconsidered to verify the trend of SLR and it was observed thatsea level rise was about 10mm per year

Unnikrishnan and Shankar [54] estimated that the sealevel along the Indian coast has increased at a rate varyingbetween 106 and 175mm per year during the period 1969to 2007 depending on the tide gauge recording site with anestimated regional average of 129mmper year subsequent toa global isostatic adjustment correctionThe SLR observed atthe study area is less in comparisonwith global average rate ofabout 17mmper year [55] and also less than regional averageHence the study area is considered to be less vulnerable to sealevel rise and lowest ranking of 1 was awarded for the entirecoast

42 Coastal Slope The regional coastal slope was calculatedfor a distance of 6 km (3 km each from shoreline on seaand landside) perpendicular to the shoreline at an intervalof 15 km The five vulnerability classes and the slope rangein each class are adopted by Pendleton et al [56] A slopegreater than 06 is assigned low vulnerability and less than03 is assigned high vulnerability as shown in Table 4 andaccordingly vulnerability ranks (indicating the vulnerabilitylevels in terms of coastal slope) are assigned to all segmentsof the coast

43 Regional Elevation The mean regional elevation withinstudy area varied between 069m in Mangaluru and 7894min Karwar An elevation value greater than 40m is assignedlow vulnerability and less than 10m is assigned high vul-nerability as shown in Table 4 The minimum value of 10m

6 Advances in Civil Engineering

Sea levelTrend line

y = (minus2658E minus 7)x + 7649

06-2003

06-2008

06-2013

06-1988

06-1983

06-1998

06-1978

06-1973

06-1993

06-1968

Date (mm-yyy)

66

69

72

75

78

81Se

a lev

el (m

)

(a)

81

78

75

72

69

66

Sea l

evel

(m)

y = (4303E minus 6)x minus 3457

06-2004

06-2009

06-1989

06-1984

06-1999

06-1979

06-1994

06-1974

Date (mm-yyy)

Sea levelTrend line

(b)Figure 3 (a) Sea Level variation at Karwar (b) Sea Level variation at Mangaluru

Table 4 Ranges of variables for vulnerability ranking

Variable Ranking of vulnerability1 2 3 4 5

Coastal slope () gt060 05ndash06 04ndash05 03ndash04 lt03Mean tide range (m) lt10 10ndash20 20ndash30 30ndash40 gt40Regional elevation (m) lt10 10ndash20 20ndash30 30ndash40 gt40Shoreline change rate (m yearminus1) gt+20 +10 to +20 minus10 to +10 minus20 to minus10 ltminus20Mean significant wave height (m) lt07 07ndash14 14ndash21 21ndash28 gt28Population (person per 200m2) lt19 44ndash20 80ndash45 326ndash81 gt326

was considered based on the Indian Ocean earthquake of 26December 2004 of magnitude 90 on the Richter scale whichresulted in devastating tsunami along the shores of IndonesiaSri Lanka South India Thailand and other countries withwaves up to 15m high

44 Tidal Range Tidal range is ranked such that microtidal(lt1m) coasts have very low vulnerability and macrotidal(gt6m) coasts have a very high vulnerabilityThe vulnerabilityranking given is taken from the vulnerability ranges of Diezet al [57]The study area is characterized by mesotidal coastsas the tidal range is within 6m but greater than 1m Entirestudy area has fallen into two categories namely very lowvulnerable level (lt10m) and low vulnerable level (10 to20m) as far as the tidal range is considered Accordinglythe entire coast is classified into these two vulnerabilitycategories

45 SignificantWave Height (SWH) Mean SWH in the studyarea varied between 10m and 20m The vulnerability levelswere adopted by Dwarakish et al [28] Kundapur was havinga lowest SWH of 10m while Mangaluru had highest SWH of20m It was assumed that the mean SWH was as per Table 3within the limits of corresponding talukas

46 Shoreline Change Rate The shoreline change rate in thestudy area was calculated for a period of 42 years (1972 to2014) The Output from DSAS revealed that about 409 km

kw05

akw

11kw

16kw

22ak03

aak09

km05

km11

km17

km23

hn06

hn12

bt02

bt08

bt14

kd03

kd09

kd15

kd21

kd27

up05

up11

up17

up23

up29

mn0

2m

n08

mn1

4m

n20minus6

minus4

minus2

0

2

4

6

8

10

Grid ID

LRR

(m ye

arminus

1 )

Figure 4 Mean shoreline change rate along the grids

of coastline had a very high risk rating along the coastalstretch of southern Mangaluru About 1425 km of coastlinewas of high risk rating along the coastal stretches nearsouthern parts of Mangaluru Kundapur and Kumta and alsoin northern Udupi and Bhatkal About 26750 km of coastlinewas under amoderate riskwhile 15 and 1066 km stretchwereunder low and very low risk category respectively Averageaccretion for the whole of the study area was found to be1133m per year and average erosion was 0533m per yearFigure 4 shows the mean shoreline change rate in each grid

Advances in Civil Engineering 7

CVI CVI173ndash450451ndash670

671ndash10391040ndash1897

Karwar Ankola

Kumta Honnavar

Bhatkal

Udupi

Kundapur

Mangaluru

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E 74∘209984000998400998400E74∘159984000998400998400E

74∘209984000998400998400E74∘159984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N 14∘ 40998400 0

998400998400N

14∘ 40998400 0

998400998400N

14∘ 20998400 0

998400998400N

14∘ 15998400 0

998400998400N

14∘ 10998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘259984000998400998400E74∘159984000998400998400E

74∘259984000998400998400E74∘159984000998400998400E

14∘ 35998400 0

998400998400N

14∘ 25998400 0

998400998400N 14∘ 30998400 0

998400998400N

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

13∘ 20998400 0

998400998400N

13∘ 30998400 0

998400998400N

13∘ 10998400 0

998400998400N

13∘ 25998400 0

998400998400N

13∘ 15998400 0

998400998400N

173ndash450451ndash670

671ndash10391040ndash1897

Figure 5 CVI for study area

8 Advances in Civil Engineering

Table 5 CVI for talukas

Taluka CVIMax Min Average 120590

Karwar 1897 424 604 336Ankola 948 367 644 237Kumta 948 367 628 187Honnavar 734 367 520 146Bhatkal 774 173 534 165Kundapur 800 244 589 121Udupi 979 600 778 241Mangaluru 1549 489 794 094

along the study area The risk ranking was awarded basedon the risk category formed by Pendleton et al [56] and isdescribed in Table 4

47 Population Distribution Georeferenced populationraster downloaded from Worldpop project has data valuesvarying from 0 to 326 persons per 200m2 for the study areaThe population is considered to be a stressor variable in thestudy It was assumed that vulnerability varied exponentiallywith population density and the data was classified into 5classes The zones with values equal to or less than 19 personsper 200m2 were awarded with least ranking and regionswith value equal to or more than a value of 326 persons per200m2 were considered as highly vulnerable and highestrank was assigned Table 4 shows the intermediate values forother classes

Coastal Vulnerability Index (CVI) Coastal vulnerability indexmap for the Karnataka Coast is shown in Figure 5 Thecalculated CVI values range from 173 to 1897 Table 5 detailsthe CVI for each taluk with statistical parameters The meanmode andmedian CVI values are 652 734 and 692 respec-tively The standard deviation is 221 The CVI scores aredivided into low moderate high and very high vulnerabilitycategories based on the quartile ranges [56] The 25th 50thand 75th percentiles are 490 692 and 735 respectively Thelower range of CVI values indicates low risk followed bymoderate risk high risk and finally the upper range of valuesindicating the coastal stretches having very high risk

The present study is an attempt to categorize the coast ofKarnataka according to its coastal vulnerabilities The vari-ables under consideration are sea level change coastal sloperegional elevation tidal range significant wave height andpopulation density A total of 298 km of shoreline are rankedin the study About 6865 km of the shoreline is very high vul-nerable category and 7926 km of shoreline is high vulnerablecategory Of the remaining shoreline 5914 km and 9104 kmare of moderate and low vulnerable categories respectively

Table 5 shows variation of CVI for each talukaThe coastsof Mangaluru and Udupi fall under high risk category andall other talukas are under moderate risk The CVI in thepresent study was primarily influenced by the risk rankingof the shoreline change rate population and the coastalslope It was observed that coasts of Mangaluru Kumta and

Bhatkal were under erosion with an average value of 021013 and 014m per year respectively while for other talukasaccretion was observed The sensitivity of the CVI to thesocioeconomic variable ldquopopulationrdquo was examined and itwas found that CVI significantly decreased in the talukasof Mangaluru Udupi and Karwar on omission of variableand on a relative basis The coastal slope was observed tobe steep in northern talukas that is in Karwar Ankola andKumta while Kundapur Udupi and Mangaluru had mildslope topography This was primarily because in KarwarAnkola andKumtawe find the headlands and cliffs very closeto the coast and southern talukas have more open beaches

5 Conclusion

In the view of the rising sea levels and other coastal hazardsan assessment of coast for its vulnerability to these threatsis necessary in order to take suitable actions to protect thepeople and property It was observed that 6865 km of theshoreline of the study area was under very high vulnerablecategory and 7926 km of shoreline is high vulnerable cate-gory while 5914 km and 9104 km of coast are of moderateand low vulnerable categories respectively Present study alsoevaluated the transformation of theKarnataka coastline usingLandsat satellite images The CVI developed in the presentstudy provides an understanding about the vulnerability ofthe Karnataka Coast to erosion coastal flooding and relativesea level change and as well as facilitates policy options forcoastal planners and authorities with regard to prioritizingcoastal areas for mitigation

Competing Interests

The present study is a work of pure academic researchThe authors declare that there are no competing interestsregarding the publication of this paper

References

[1] F L Alves C Coelho C D Coelho and P Pinto ldquoModellingcoastal vulnerabilities tool for decision support system at inter-municipality levelrdquo Journal of Coastal Research no 64 pp 966ndash970 2011

[2] R J Nicholls and N Mimura ldquoRegional issues raised by sea-level rise and their policy implicationsrdquo Climate Research vol11 no 1 pp 5ndash18 1999

[3] IPCC (Intergovernmental Panel on Climate Change) IPCCReport Working Group-I Climate Change 2001 The ScientificBasis Cambridge University Press Cambridge UK 2001httpwwwipccchipccreportstarwg1408htm

[4] ICZMP ldquoDocument of world bankmdashproject appraisaldocument for an integrated coastal zone management projectrdquoReport 54612-IN Integrated Coastal Zone Management2010 httpwwwsicommoefinDataSites1skinsgec-sicomimagesdocspadpdf

[5] N N V Sudha Rani A N V Satyanarayana and P KBhaskaran ldquoCoastal vulnerability assessment studies overIndia a reviewrdquo Natural Hazards vol 77 no 1 pp 405ndash4282015

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Advances in Civil Engineering 3

Table 1 List of variables and data source

Variables Data source Time periodSea level change rate PSMSL (httpwwwpsmslorg) 1976ndash2004Shoreline change rate Earth Explorer (httpearthexplorerusgsgov) 1972ndash2014Coastal slope GEBCO (httpwwwgebconet) mdashRegional elevation SRTM (httpsrtmcsicgiarorg) mdashTidal range Secondary data mdashSignificant wave height Secondary data mdashPopulation Worldpop (httpwwwworldpoporguk) 2010

the year Deep-water waves approach the coast from south-western and north-western directions [6]

The northern part of the study area is geologically com-posed of Precambrian crystalline gneiss schist and graniterocks fronted by a narrow coastal plain of alluvial or tertiarydeposits In locations where the rock extends to the coastlinecoastal cliffs and rocky shores are formed The coastline hasdrowned river valleys estuaries andmany small inlets whichis a typical submergence characteristic [32] The southernpart of study area has extensive straight beaches and estuarieswith low estuarine islands and mangroves

3 Methodology

The present study adopts the CVI methodology formulatedby Thieler and Hammer-Klose [9ndash11] The process resultsin a classification of coast using simple criteria and yieldsnumerical data that cannot be equated directly with par-ticular physical effects but shows the arearsquos most affectedby the hazard Initially a database of the variables underconsideration for the study area was built by compiling datafrom various sources Table 1 details the variables and theirdata sources used in the present study The data values ofvariables under consideration were assigned a vulnerabilityranking based on value ranges contributing to coastal vul-nerability while the nonnumerical geomorphology variablewas ranked qualitatively according to the relative resistanceof a given landform to erosion Later the key variables wereintegrated to a single index and categorized based on therelative intensity of risk it imparts to the coast namely verylow low medium high and very high The entire coastlinewas divided into 8 zones based on administrative boundaryof talukas A grid template of 15 km by 15 km was used tostore and analyze data and display the CVI similar to theprocedure adopted by Abuodha and Woodroffe [33] Eachcell of the grid template was assigned with an identificationnumber as shown in Figure 2 The software package ArcGIS93 offers the suitable environment to carry out the processThe variation of each variable within the area was analyzedand suitable risk ratings were awarded for each specific datavariable and the coastal vulnerability index was calculated

In the present study eight variables were considered fordeveloping the CVI rate of relative sea level change histor-ical rate of shoreline change (erosion or accretion) coastalregional elevation coastal slope mean tidal range significantwave height and socioeconomic dataThe importance of each

up11

up08

up01

up02

up10

up12

up13

up07

up06

up09

up03

up04

up05

up14

mn25

mn24

mn23

Karnataka

Arabian Sea

N

Figure 2 Grid template for the study area

of the considered parameters and the procedure to generatethe same for use in assessment of CVI are given in thefollowing section

31 Relative Sea Level Change Rate Sea level rise shifts thewave action zone to higher elevations due to recession ofcoast to inland This recession of shoreline will be greater inmild slope regions [34] The direct effect of such recessionis submergence of coastal land and aggravated events offlooding Long-term effects can be increased erosion and salt-water intrusion into ground water as the coast adjusts to thenew conditions [35] According to IPCC every millimeterrise of mean sea level on the coast would result in a shorelineretreat of about 1mMean sea level at the coast is the height ofthe sea with respect to a local land benchmark averaged overa long time period Changes inmean sea level as measured bycoastal tide gauges are called relative sea level changes [36]

4 Advances in Civil Engineering

The Permanent Service for Mean Sea Level (PSMSL)data has been used in the study to calculate the relative sealevel change rate The study area consists of two PSMSL tidegauge stations namely Mangaluru and KarwarThe monthlymean sea level data from 1976 to 2000 are downloaded forMangaluru station and from 1970 to 2004 for the Karwarstation from the PSMSLwebsiteThemonthlymean values ofsea level recorded at these stations were plotted from whicha linear best fit line adopting least squares method was com-puted to calculate the sea level change rate and risk ratingswere assigned Coast subjected to a high rate of sea level risewas considered as a high vulnerable area and vice versa

32 Shoreline Change Rate The shoreline change rate is oneof the most common measurements used to indicate thedynamics and the hazards of the coast [41] Coastal shorelinesare always subjected to changes due to coastal processeswhich are controlled by wave characteristics and the resultantnear-shore circulation sediment characteristics beach formand so forth From the coastal vulnerability point of viewcoasts subjected to accretion are considered as less vulnerableareas as they move towards the ocean and result in theaddition of land areas whereas areas of coastal erosion areconsidered to be more vulnerable because of the resultantloss of individual and public property as well as importantnatural habitats It also trims down the distance betweencoastal population and ocean thereby increasing the risk ofexposure of population to coastal hazards

Orthorectified satellite images of the study area from thesensors LandsatMSS ETM+andOLI-TIRS for the years 19721991 1998 2000 2006 2012 and 2014 were downloaded fromUSGS Earth Explorer web tool The images were projected tothe Universal Transverse Mercator (UTM) projection systemwith WGS-84 datum Histogram splicing was applied tocreate a binary image from near infrared band of each imageand is classified as unsupervised to form image with completeseparation between land and water classes These classifiedimages were used to extract the shorelines in the form ofvector layer using ERDAS Imagine 92 and ArcMap 93

Thedigitized shoreline for the years 1972 1991 1998 20002006 2012 and 2014 in the vector format was used as theinput to the Digital Shoreline Analysis System (DSAS) DSAScomputes rate-of-change statistics from multiple historicshoreline positions by using GIS [42] Transects were castperpendicular to the baseline at a 100m interval all alongthe shore using DSAS The crossover of these transects withshoreline along the baseline is then used to calculate the rate-of-change statistics Linear Regression Rate (LRR) method ofshoreline change rate estimation was used in this study LRRuses all the available data to find a line which has the overallminimumof the squared distance to the known shoreline andis an established method for computing long-term rates ofshoreline change [43] Risk ratings were assigned based onthe LRR

33 Coastal Slope The coastal slope is change in altitude fora unit horizontal distance between any two points on thecoast The degree of steepness or flatness of a coastal regiondetermines the susceptibility of the coast to inundation by

Table 2 Tidal range for various zones and their source

Location Tidal range (m) SourceKarwar Ankola amp Kumta 158 Kumar et al [37]Honnavar 21

Sanil Kumar et al [38]Kundapur amp Bhatkal 19Udupi (Malpe) 18Mangaluru 16 Dwarakish et al [28]

flooding [44] Determination of regional coastal slope iden-tifies the relative vulnerability of inundation and potentialrapidity of shoreline retreat because low sloping coastalregions are thought to retreat faster than steeper regions [17]

General Bathymetric Chart of the Oceans (GEBCO)data of 30-arc seconds grid resolution coastal topographyand bathymetry has been used to get the regional slope ofthe coastal area GEBCO also incorporates land elevationsderived from the Global Land One-kilometer Base Elevationproject data set GEBCO data sets are useful in deriving thecoastal slope values both on land and in the ocean 3D analysttool of ArcGIS 93 was used in preparing the coastal slopemap Coastal areas having gentle slope were considered ashighly vulnerable areas and areas of steep slope as areas oflow vulnerability

34 Regional Elevation It is important to study the coastalregional elevation detail in the study area to identify andestimate the extent of land area threatened by future sea levelriseThese coastal elevation data are also used to estimate theland potentially available for wetland migration in responseto sea level rise and the sea level rise impacts on thehuman built environment [45] From the coastal vulnerabilitypoint of view coastal regions having high elevation will beconsidered as less vulnerable areas because they providemoreresistance for inundation against the rising sea level tsunamirun-up and storm surge

Those coastal regions having low elevation are consideredas highly vulnerable areas In the present study Shuttle RadarTopography Mission (SRTM) data was used to derive thecoastal regional elevation A zonal statistical analysis wascarried out using ArcGIS and elevation in each grid cell wasdetermined and risk rating was awarded

35 Tidal Range The tidal range is the vertical differencebetween the highest high tide and the lowest low tide Fromthe vulnerability point of view it is an obvious tendency todesignate coastal areas of high tidal range as highly vulner-able This decision is based on the concept that large tidalrange is associated with strong tidal currents that influencecoastal behavior For the current study coastal areas withhigh tidal range are considered as highly vulnerable and lowtidal range as less vulnerable Previously studies were carriedout at various locations of the study area and the tidal rangehas been determined [28 31 37] Table 2 lists the details ofthe studies and the tidal range This secondary data was alsoconsidered for calculations

Advances in Civil Engineering 5

Table 3 Mean significant wave height for different talukas as collected from the literatures

Location Mean significant wave height (m) SourceKarwar Ankola amp Kumta 16 Kumar et al [31]Honnavar 19 Kumar et al [31]Kundapur 10 Shanas and Sanil Kumar [39]Bhatkal 125 Nayak et al [40]Udupi (Malpe) 19 Kumar et al [31]Mangaluru 20 Dwarakish et al [28]

36 Significant Wave Height Significant wave height is theaverage height of the one-third highest waves valid for theindicated 12-hour period Mean significant wave height isused as a proxy for wave energy that drives coastal sedimenttransport [46] The vulnerability study based on wave heightis an important step in setting up an all-hazards warning andmanagement system [46]

The movement and transport of coastal sediments aredependent upon the wave energy which varies as the squareof the wave height [47] With increase in the wave height andeventual increase in wave energy land is lost and coast willwitness increased erosion and inundation along the shoreHence the coastal areas of high wave height are consideredas more vulnerable coasts and areas of low wave height asless vulnerable coasts In the present study wave heights inthe study area were collected from the various other studiesconducted primarily onwave characteristics in the study areaTable 3 shows the details of the data collected

37 Population Coastal region has high population densitycompared to upland areas Population can also be interpretedas a direct ldquoerosion-inducingrdquo variable because the presenceof large number of people near the coast may producedamaging impacts on the coastal area [48] Hence presenceof human habitation increases the vulnerability of the regionIn the present study the population was considered as apressure exerting factor on the coastal system and hence areaswith a higher concentration of people are considered as moresusceptible to erosion similar to Hegde and Reju [18]

Worldpop project provides high resolution and contem-porary data on human population distributions for SoutheastAsian countries in raster data format An alpha version dataestimated to match UN population estimate for the year2015 was used in the present study The data set is of rasterformat with resolution of 100m at the equator The assembleof the Worldpop spatial data sets principally follows themethodologies outlined by Gaughan et al [49] Linard et al[50] Linard et al [51] and Tatem et al [52]

38 Calculation of CVI Once each section of coastline isassigned a risk value for each variable the CVI is calculated asthe square root of the product of the ranked variables dividedby the total number of variables [17] The CVI is representedby

CVI = radic119886 lowast 119887 lowast 119888 lowast 119889 lowast 119890 lowast 119891 lowast 119892

7

(1)

where 119886 = risk rating assigned to sea level change rate 119887 =risk rating assigned to shoreline change rate 119888 = risk ratingassigned to coastal slope 119889 = risk rating assigned to coastalregional elevation 119890 = risk rating assigned to tidal range 119891 =risk rating assigned to significant wave height and 119892 = riskrating assigned to population density

4 Results and Discussion

41 Relative Sea Level Change Rate For the available datait was observed that sea level was falling at a rate of 13mmper year at the Karwar station while it was rising at a rate of08mmper year at theMangaluru station as shown in Figures3(a) and 3(b) respectively Douglas [53] acknowledged thatto determine the trends in long-term sea level changes idealrecord length greater than 60 years is desirable Since suchlong duration records were not available for the present studyregion the tide gauge data of Cochin (64 years) was alsoconsidered to verify the trend of SLR and it was observed thatsea level rise was about 10mm per year

Unnikrishnan and Shankar [54] estimated that the sealevel along the Indian coast has increased at a rate varyingbetween 106 and 175mm per year during the period 1969to 2007 depending on the tide gauge recording site with anestimated regional average of 129mmper year subsequent toa global isostatic adjustment correctionThe SLR observed atthe study area is less in comparisonwith global average rate ofabout 17mmper year [55] and also less than regional averageHence the study area is considered to be less vulnerable to sealevel rise and lowest ranking of 1 was awarded for the entirecoast

42 Coastal Slope The regional coastal slope was calculatedfor a distance of 6 km (3 km each from shoreline on seaand landside) perpendicular to the shoreline at an intervalof 15 km The five vulnerability classes and the slope rangein each class are adopted by Pendleton et al [56] A slopegreater than 06 is assigned low vulnerability and less than03 is assigned high vulnerability as shown in Table 4 andaccordingly vulnerability ranks (indicating the vulnerabilitylevels in terms of coastal slope) are assigned to all segmentsof the coast

43 Regional Elevation The mean regional elevation withinstudy area varied between 069m in Mangaluru and 7894min Karwar An elevation value greater than 40m is assignedlow vulnerability and less than 10m is assigned high vul-nerability as shown in Table 4 The minimum value of 10m

6 Advances in Civil Engineering

Sea levelTrend line

y = (minus2658E minus 7)x + 7649

06-2003

06-2008

06-2013

06-1988

06-1983

06-1998

06-1978

06-1973

06-1993

06-1968

Date (mm-yyy)

66

69

72

75

78

81Se

a lev

el (m

)

(a)

81

78

75

72

69

66

Sea l

evel

(m)

y = (4303E minus 6)x minus 3457

06-2004

06-2009

06-1989

06-1984

06-1999

06-1979

06-1994

06-1974

Date (mm-yyy)

Sea levelTrend line

(b)Figure 3 (a) Sea Level variation at Karwar (b) Sea Level variation at Mangaluru

Table 4 Ranges of variables for vulnerability ranking

Variable Ranking of vulnerability1 2 3 4 5

Coastal slope () gt060 05ndash06 04ndash05 03ndash04 lt03Mean tide range (m) lt10 10ndash20 20ndash30 30ndash40 gt40Regional elevation (m) lt10 10ndash20 20ndash30 30ndash40 gt40Shoreline change rate (m yearminus1) gt+20 +10 to +20 minus10 to +10 minus20 to minus10 ltminus20Mean significant wave height (m) lt07 07ndash14 14ndash21 21ndash28 gt28Population (person per 200m2) lt19 44ndash20 80ndash45 326ndash81 gt326

was considered based on the Indian Ocean earthquake of 26December 2004 of magnitude 90 on the Richter scale whichresulted in devastating tsunami along the shores of IndonesiaSri Lanka South India Thailand and other countries withwaves up to 15m high

44 Tidal Range Tidal range is ranked such that microtidal(lt1m) coasts have very low vulnerability and macrotidal(gt6m) coasts have a very high vulnerabilityThe vulnerabilityranking given is taken from the vulnerability ranges of Diezet al [57]The study area is characterized by mesotidal coastsas the tidal range is within 6m but greater than 1m Entirestudy area has fallen into two categories namely very lowvulnerable level (lt10m) and low vulnerable level (10 to20m) as far as the tidal range is considered Accordinglythe entire coast is classified into these two vulnerabilitycategories

45 SignificantWave Height (SWH) Mean SWH in the studyarea varied between 10m and 20m The vulnerability levelswere adopted by Dwarakish et al [28] Kundapur was havinga lowest SWH of 10m while Mangaluru had highest SWH of20m It was assumed that the mean SWH was as per Table 3within the limits of corresponding talukas

46 Shoreline Change Rate The shoreline change rate in thestudy area was calculated for a period of 42 years (1972 to2014) The Output from DSAS revealed that about 409 km

kw05

akw

11kw

16kw

22ak03

aak09

km05

km11

km17

km23

hn06

hn12

bt02

bt08

bt14

kd03

kd09

kd15

kd21

kd27

up05

up11

up17

up23

up29

mn0

2m

n08

mn1

4m

n20minus6

minus4

minus2

0

2

4

6

8

10

Grid ID

LRR

(m ye

arminus

1 )

Figure 4 Mean shoreline change rate along the grids

of coastline had a very high risk rating along the coastalstretch of southern Mangaluru About 1425 km of coastlinewas of high risk rating along the coastal stretches nearsouthern parts of Mangaluru Kundapur and Kumta and alsoin northern Udupi and Bhatkal About 26750 km of coastlinewas under amoderate riskwhile 15 and 1066 km stretchwereunder low and very low risk category respectively Averageaccretion for the whole of the study area was found to be1133m per year and average erosion was 0533m per yearFigure 4 shows the mean shoreline change rate in each grid

Advances in Civil Engineering 7

CVI CVI173ndash450451ndash670

671ndash10391040ndash1897

Karwar Ankola

Kumta Honnavar

Bhatkal

Udupi

Kundapur

Mangaluru

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E 74∘209984000998400998400E74∘159984000998400998400E

74∘209984000998400998400E74∘159984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N 14∘ 40998400 0

998400998400N

14∘ 40998400 0

998400998400N

14∘ 20998400 0

998400998400N

14∘ 15998400 0

998400998400N

14∘ 10998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘259984000998400998400E74∘159984000998400998400E

74∘259984000998400998400E74∘159984000998400998400E

14∘ 35998400 0

998400998400N

14∘ 25998400 0

998400998400N 14∘ 30998400 0

998400998400N

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

13∘ 20998400 0

998400998400N

13∘ 30998400 0

998400998400N

13∘ 10998400 0

998400998400N

13∘ 25998400 0

998400998400N

13∘ 15998400 0

998400998400N

173ndash450451ndash670

671ndash10391040ndash1897

Figure 5 CVI for study area

8 Advances in Civil Engineering

Table 5 CVI for talukas

Taluka CVIMax Min Average 120590

Karwar 1897 424 604 336Ankola 948 367 644 237Kumta 948 367 628 187Honnavar 734 367 520 146Bhatkal 774 173 534 165Kundapur 800 244 589 121Udupi 979 600 778 241Mangaluru 1549 489 794 094

along the study area The risk ranking was awarded basedon the risk category formed by Pendleton et al [56] and isdescribed in Table 4

47 Population Distribution Georeferenced populationraster downloaded from Worldpop project has data valuesvarying from 0 to 326 persons per 200m2 for the study areaThe population is considered to be a stressor variable in thestudy It was assumed that vulnerability varied exponentiallywith population density and the data was classified into 5classes The zones with values equal to or less than 19 personsper 200m2 were awarded with least ranking and regionswith value equal to or more than a value of 326 persons per200m2 were considered as highly vulnerable and highestrank was assigned Table 4 shows the intermediate values forother classes

Coastal Vulnerability Index (CVI) Coastal vulnerability indexmap for the Karnataka Coast is shown in Figure 5 Thecalculated CVI values range from 173 to 1897 Table 5 detailsthe CVI for each taluk with statistical parameters The meanmode andmedian CVI values are 652 734 and 692 respec-tively The standard deviation is 221 The CVI scores aredivided into low moderate high and very high vulnerabilitycategories based on the quartile ranges [56] The 25th 50thand 75th percentiles are 490 692 and 735 respectively Thelower range of CVI values indicates low risk followed bymoderate risk high risk and finally the upper range of valuesindicating the coastal stretches having very high risk

The present study is an attempt to categorize the coast ofKarnataka according to its coastal vulnerabilities The vari-ables under consideration are sea level change coastal sloperegional elevation tidal range significant wave height andpopulation density A total of 298 km of shoreline are rankedin the study About 6865 km of the shoreline is very high vul-nerable category and 7926 km of shoreline is high vulnerablecategory Of the remaining shoreline 5914 km and 9104 kmare of moderate and low vulnerable categories respectively

Table 5 shows variation of CVI for each talukaThe coastsof Mangaluru and Udupi fall under high risk category andall other talukas are under moderate risk The CVI in thepresent study was primarily influenced by the risk rankingof the shoreline change rate population and the coastalslope It was observed that coasts of Mangaluru Kumta and

Bhatkal were under erosion with an average value of 021013 and 014m per year respectively while for other talukasaccretion was observed The sensitivity of the CVI to thesocioeconomic variable ldquopopulationrdquo was examined and itwas found that CVI significantly decreased in the talukasof Mangaluru Udupi and Karwar on omission of variableand on a relative basis The coastal slope was observed tobe steep in northern talukas that is in Karwar Ankola andKumta while Kundapur Udupi and Mangaluru had mildslope topography This was primarily because in KarwarAnkola andKumtawe find the headlands and cliffs very closeto the coast and southern talukas have more open beaches

5 Conclusion

In the view of the rising sea levels and other coastal hazardsan assessment of coast for its vulnerability to these threatsis necessary in order to take suitable actions to protect thepeople and property It was observed that 6865 km of theshoreline of the study area was under very high vulnerablecategory and 7926 km of shoreline is high vulnerable cate-gory while 5914 km and 9104 km of coast are of moderateand low vulnerable categories respectively Present study alsoevaluated the transformation of theKarnataka coastline usingLandsat satellite images The CVI developed in the presentstudy provides an understanding about the vulnerability ofthe Karnataka Coast to erosion coastal flooding and relativesea level change and as well as facilitates policy options forcoastal planners and authorities with regard to prioritizingcoastal areas for mitigation

Competing Interests

The present study is a work of pure academic researchThe authors declare that there are no competing interestsregarding the publication of this paper

References

[1] F L Alves C Coelho C D Coelho and P Pinto ldquoModellingcoastal vulnerabilities tool for decision support system at inter-municipality levelrdquo Journal of Coastal Research no 64 pp 966ndash970 2011

[2] R J Nicholls and N Mimura ldquoRegional issues raised by sea-level rise and their policy implicationsrdquo Climate Research vol11 no 1 pp 5ndash18 1999

[3] IPCC (Intergovernmental Panel on Climate Change) IPCCReport Working Group-I Climate Change 2001 The ScientificBasis Cambridge University Press Cambridge UK 2001httpwwwipccchipccreportstarwg1408htm

[4] ICZMP ldquoDocument of world bankmdashproject appraisaldocument for an integrated coastal zone management projectrdquoReport 54612-IN Integrated Coastal Zone Management2010 httpwwwsicommoefinDataSites1skinsgec-sicomimagesdocspadpdf

[5] N N V Sudha Rani A N V Satyanarayana and P KBhaskaran ldquoCoastal vulnerability assessment studies overIndia a reviewrdquo Natural Hazards vol 77 no 1 pp 405ndash4282015

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

4 Advances in Civil Engineering

The Permanent Service for Mean Sea Level (PSMSL)data has been used in the study to calculate the relative sealevel change rate The study area consists of two PSMSL tidegauge stations namely Mangaluru and KarwarThe monthlymean sea level data from 1976 to 2000 are downloaded forMangaluru station and from 1970 to 2004 for the Karwarstation from the PSMSLwebsiteThemonthlymean values ofsea level recorded at these stations were plotted from whicha linear best fit line adopting least squares method was com-puted to calculate the sea level change rate and risk ratingswere assigned Coast subjected to a high rate of sea level risewas considered as a high vulnerable area and vice versa

32 Shoreline Change Rate The shoreline change rate is oneof the most common measurements used to indicate thedynamics and the hazards of the coast [41] Coastal shorelinesare always subjected to changes due to coastal processeswhich are controlled by wave characteristics and the resultantnear-shore circulation sediment characteristics beach formand so forth From the coastal vulnerability point of viewcoasts subjected to accretion are considered as less vulnerableareas as they move towards the ocean and result in theaddition of land areas whereas areas of coastal erosion areconsidered to be more vulnerable because of the resultantloss of individual and public property as well as importantnatural habitats It also trims down the distance betweencoastal population and ocean thereby increasing the risk ofexposure of population to coastal hazards

Orthorectified satellite images of the study area from thesensors LandsatMSS ETM+andOLI-TIRS for the years 19721991 1998 2000 2006 2012 and 2014 were downloaded fromUSGS Earth Explorer web tool The images were projected tothe Universal Transverse Mercator (UTM) projection systemwith WGS-84 datum Histogram splicing was applied tocreate a binary image from near infrared band of each imageand is classified as unsupervised to form image with completeseparation between land and water classes These classifiedimages were used to extract the shorelines in the form ofvector layer using ERDAS Imagine 92 and ArcMap 93

Thedigitized shoreline for the years 1972 1991 1998 20002006 2012 and 2014 in the vector format was used as theinput to the Digital Shoreline Analysis System (DSAS) DSAScomputes rate-of-change statistics from multiple historicshoreline positions by using GIS [42] Transects were castperpendicular to the baseline at a 100m interval all alongthe shore using DSAS The crossover of these transects withshoreline along the baseline is then used to calculate the rate-of-change statistics Linear Regression Rate (LRR) method ofshoreline change rate estimation was used in this study LRRuses all the available data to find a line which has the overallminimumof the squared distance to the known shoreline andis an established method for computing long-term rates ofshoreline change [43] Risk ratings were assigned based onthe LRR

33 Coastal Slope The coastal slope is change in altitude fora unit horizontal distance between any two points on thecoast The degree of steepness or flatness of a coastal regiondetermines the susceptibility of the coast to inundation by

Table 2 Tidal range for various zones and their source

Location Tidal range (m) SourceKarwar Ankola amp Kumta 158 Kumar et al [37]Honnavar 21

Sanil Kumar et al [38]Kundapur amp Bhatkal 19Udupi (Malpe) 18Mangaluru 16 Dwarakish et al [28]

flooding [44] Determination of regional coastal slope iden-tifies the relative vulnerability of inundation and potentialrapidity of shoreline retreat because low sloping coastalregions are thought to retreat faster than steeper regions [17]

General Bathymetric Chart of the Oceans (GEBCO)data of 30-arc seconds grid resolution coastal topographyand bathymetry has been used to get the regional slope ofthe coastal area GEBCO also incorporates land elevationsderived from the Global Land One-kilometer Base Elevationproject data set GEBCO data sets are useful in deriving thecoastal slope values both on land and in the ocean 3D analysttool of ArcGIS 93 was used in preparing the coastal slopemap Coastal areas having gentle slope were considered ashighly vulnerable areas and areas of steep slope as areas oflow vulnerability

34 Regional Elevation It is important to study the coastalregional elevation detail in the study area to identify andestimate the extent of land area threatened by future sea levelriseThese coastal elevation data are also used to estimate theland potentially available for wetland migration in responseto sea level rise and the sea level rise impacts on thehuman built environment [45] From the coastal vulnerabilitypoint of view coastal regions having high elevation will beconsidered as less vulnerable areas because they providemoreresistance for inundation against the rising sea level tsunamirun-up and storm surge

Those coastal regions having low elevation are consideredas highly vulnerable areas In the present study Shuttle RadarTopography Mission (SRTM) data was used to derive thecoastal regional elevation A zonal statistical analysis wascarried out using ArcGIS and elevation in each grid cell wasdetermined and risk rating was awarded

35 Tidal Range The tidal range is the vertical differencebetween the highest high tide and the lowest low tide Fromthe vulnerability point of view it is an obvious tendency todesignate coastal areas of high tidal range as highly vulner-able This decision is based on the concept that large tidalrange is associated with strong tidal currents that influencecoastal behavior For the current study coastal areas withhigh tidal range are considered as highly vulnerable and lowtidal range as less vulnerable Previously studies were carriedout at various locations of the study area and the tidal rangehas been determined [28 31 37] Table 2 lists the details ofthe studies and the tidal range This secondary data was alsoconsidered for calculations

Advances in Civil Engineering 5

Table 3 Mean significant wave height for different talukas as collected from the literatures

Location Mean significant wave height (m) SourceKarwar Ankola amp Kumta 16 Kumar et al [31]Honnavar 19 Kumar et al [31]Kundapur 10 Shanas and Sanil Kumar [39]Bhatkal 125 Nayak et al [40]Udupi (Malpe) 19 Kumar et al [31]Mangaluru 20 Dwarakish et al [28]

36 Significant Wave Height Significant wave height is theaverage height of the one-third highest waves valid for theindicated 12-hour period Mean significant wave height isused as a proxy for wave energy that drives coastal sedimenttransport [46] The vulnerability study based on wave heightis an important step in setting up an all-hazards warning andmanagement system [46]

The movement and transport of coastal sediments aredependent upon the wave energy which varies as the squareof the wave height [47] With increase in the wave height andeventual increase in wave energy land is lost and coast willwitness increased erosion and inundation along the shoreHence the coastal areas of high wave height are consideredas more vulnerable coasts and areas of low wave height asless vulnerable coasts In the present study wave heights inthe study area were collected from the various other studiesconducted primarily onwave characteristics in the study areaTable 3 shows the details of the data collected

37 Population Coastal region has high population densitycompared to upland areas Population can also be interpretedas a direct ldquoerosion-inducingrdquo variable because the presenceof large number of people near the coast may producedamaging impacts on the coastal area [48] Hence presenceof human habitation increases the vulnerability of the regionIn the present study the population was considered as apressure exerting factor on the coastal system and hence areaswith a higher concentration of people are considered as moresusceptible to erosion similar to Hegde and Reju [18]

Worldpop project provides high resolution and contem-porary data on human population distributions for SoutheastAsian countries in raster data format An alpha version dataestimated to match UN population estimate for the year2015 was used in the present study The data set is of rasterformat with resolution of 100m at the equator The assembleof the Worldpop spatial data sets principally follows themethodologies outlined by Gaughan et al [49] Linard et al[50] Linard et al [51] and Tatem et al [52]

38 Calculation of CVI Once each section of coastline isassigned a risk value for each variable the CVI is calculated asthe square root of the product of the ranked variables dividedby the total number of variables [17] The CVI is representedby

CVI = radic119886 lowast 119887 lowast 119888 lowast 119889 lowast 119890 lowast 119891 lowast 119892

7

(1)

where 119886 = risk rating assigned to sea level change rate 119887 =risk rating assigned to shoreline change rate 119888 = risk ratingassigned to coastal slope 119889 = risk rating assigned to coastalregional elevation 119890 = risk rating assigned to tidal range 119891 =risk rating assigned to significant wave height and 119892 = riskrating assigned to population density

4 Results and Discussion

41 Relative Sea Level Change Rate For the available datait was observed that sea level was falling at a rate of 13mmper year at the Karwar station while it was rising at a rate of08mmper year at theMangaluru station as shown in Figures3(a) and 3(b) respectively Douglas [53] acknowledged thatto determine the trends in long-term sea level changes idealrecord length greater than 60 years is desirable Since suchlong duration records were not available for the present studyregion the tide gauge data of Cochin (64 years) was alsoconsidered to verify the trend of SLR and it was observed thatsea level rise was about 10mm per year

Unnikrishnan and Shankar [54] estimated that the sealevel along the Indian coast has increased at a rate varyingbetween 106 and 175mm per year during the period 1969to 2007 depending on the tide gauge recording site with anestimated regional average of 129mmper year subsequent toa global isostatic adjustment correctionThe SLR observed atthe study area is less in comparisonwith global average rate ofabout 17mmper year [55] and also less than regional averageHence the study area is considered to be less vulnerable to sealevel rise and lowest ranking of 1 was awarded for the entirecoast

42 Coastal Slope The regional coastal slope was calculatedfor a distance of 6 km (3 km each from shoreline on seaand landside) perpendicular to the shoreline at an intervalof 15 km The five vulnerability classes and the slope rangein each class are adopted by Pendleton et al [56] A slopegreater than 06 is assigned low vulnerability and less than03 is assigned high vulnerability as shown in Table 4 andaccordingly vulnerability ranks (indicating the vulnerabilitylevels in terms of coastal slope) are assigned to all segmentsof the coast

43 Regional Elevation The mean regional elevation withinstudy area varied between 069m in Mangaluru and 7894min Karwar An elevation value greater than 40m is assignedlow vulnerability and less than 10m is assigned high vul-nerability as shown in Table 4 The minimum value of 10m

6 Advances in Civil Engineering

Sea levelTrend line

y = (minus2658E minus 7)x + 7649

06-2003

06-2008

06-2013

06-1988

06-1983

06-1998

06-1978

06-1973

06-1993

06-1968

Date (mm-yyy)

66

69

72

75

78

81Se

a lev

el (m

)

(a)

81

78

75

72

69

66

Sea l

evel

(m)

y = (4303E minus 6)x minus 3457

06-2004

06-2009

06-1989

06-1984

06-1999

06-1979

06-1994

06-1974

Date (mm-yyy)

Sea levelTrend line

(b)Figure 3 (a) Sea Level variation at Karwar (b) Sea Level variation at Mangaluru

Table 4 Ranges of variables for vulnerability ranking

Variable Ranking of vulnerability1 2 3 4 5

Coastal slope () gt060 05ndash06 04ndash05 03ndash04 lt03Mean tide range (m) lt10 10ndash20 20ndash30 30ndash40 gt40Regional elevation (m) lt10 10ndash20 20ndash30 30ndash40 gt40Shoreline change rate (m yearminus1) gt+20 +10 to +20 minus10 to +10 minus20 to minus10 ltminus20Mean significant wave height (m) lt07 07ndash14 14ndash21 21ndash28 gt28Population (person per 200m2) lt19 44ndash20 80ndash45 326ndash81 gt326

was considered based on the Indian Ocean earthquake of 26December 2004 of magnitude 90 on the Richter scale whichresulted in devastating tsunami along the shores of IndonesiaSri Lanka South India Thailand and other countries withwaves up to 15m high

44 Tidal Range Tidal range is ranked such that microtidal(lt1m) coasts have very low vulnerability and macrotidal(gt6m) coasts have a very high vulnerabilityThe vulnerabilityranking given is taken from the vulnerability ranges of Diezet al [57]The study area is characterized by mesotidal coastsas the tidal range is within 6m but greater than 1m Entirestudy area has fallen into two categories namely very lowvulnerable level (lt10m) and low vulnerable level (10 to20m) as far as the tidal range is considered Accordinglythe entire coast is classified into these two vulnerabilitycategories

45 SignificantWave Height (SWH) Mean SWH in the studyarea varied between 10m and 20m The vulnerability levelswere adopted by Dwarakish et al [28] Kundapur was havinga lowest SWH of 10m while Mangaluru had highest SWH of20m It was assumed that the mean SWH was as per Table 3within the limits of corresponding talukas

46 Shoreline Change Rate The shoreline change rate in thestudy area was calculated for a period of 42 years (1972 to2014) The Output from DSAS revealed that about 409 km

kw05

akw

11kw

16kw

22ak03

aak09

km05

km11

km17

km23

hn06

hn12

bt02

bt08

bt14

kd03

kd09

kd15

kd21

kd27

up05

up11

up17

up23

up29

mn0

2m

n08

mn1

4m

n20minus6

minus4

minus2

0

2

4

6

8

10

Grid ID

LRR

(m ye

arminus

1 )

Figure 4 Mean shoreline change rate along the grids

of coastline had a very high risk rating along the coastalstretch of southern Mangaluru About 1425 km of coastlinewas of high risk rating along the coastal stretches nearsouthern parts of Mangaluru Kundapur and Kumta and alsoin northern Udupi and Bhatkal About 26750 km of coastlinewas under amoderate riskwhile 15 and 1066 km stretchwereunder low and very low risk category respectively Averageaccretion for the whole of the study area was found to be1133m per year and average erosion was 0533m per yearFigure 4 shows the mean shoreline change rate in each grid

Advances in Civil Engineering 7

CVI CVI173ndash450451ndash670

671ndash10391040ndash1897

Karwar Ankola

Kumta Honnavar

Bhatkal

Udupi

Kundapur

Mangaluru

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E 74∘209984000998400998400E74∘159984000998400998400E

74∘209984000998400998400E74∘159984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N 14∘ 40998400 0

998400998400N

14∘ 40998400 0

998400998400N

14∘ 20998400 0

998400998400N

14∘ 15998400 0

998400998400N

14∘ 10998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘259984000998400998400E74∘159984000998400998400E

74∘259984000998400998400E74∘159984000998400998400E

14∘ 35998400 0

998400998400N

14∘ 25998400 0

998400998400N 14∘ 30998400 0

998400998400N

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

13∘ 20998400 0

998400998400N

13∘ 30998400 0

998400998400N

13∘ 10998400 0

998400998400N

13∘ 25998400 0

998400998400N

13∘ 15998400 0

998400998400N

173ndash450451ndash670

671ndash10391040ndash1897

Figure 5 CVI for study area

8 Advances in Civil Engineering

Table 5 CVI for talukas

Taluka CVIMax Min Average 120590

Karwar 1897 424 604 336Ankola 948 367 644 237Kumta 948 367 628 187Honnavar 734 367 520 146Bhatkal 774 173 534 165Kundapur 800 244 589 121Udupi 979 600 778 241Mangaluru 1549 489 794 094

along the study area The risk ranking was awarded basedon the risk category formed by Pendleton et al [56] and isdescribed in Table 4

47 Population Distribution Georeferenced populationraster downloaded from Worldpop project has data valuesvarying from 0 to 326 persons per 200m2 for the study areaThe population is considered to be a stressor variable in thestudy It was assumed that vulnerability varied exponentiallywith population density and the data was classified into 5classes The zones with values equal to or less than 19 personsper 200m2 were awarded with least ranking and regionswith value equal to or more than a value of 326 persons per200m2 were considered as highly vulnerable and highestrank was assigned Table 4 shows the intermediate values forother classes

Coastal Vulnerability Index (CVI) Coastal vulnerability indexmap for the Karnataka Coast is shown in Figure 5 Thecalculated CVI values range from 173 to 1897 Table 5 detailsthe CVI for each taluk with statistical parameters The meanmode andmedian CVI values are 652 734 and 692 respec-tively The standard deviation is 221 The CVI scores aredivided into low moderate high and very high vulnerabilitycategories based on the quartile ranges [56] The 25th 50thand 75th percentiles are 490 692 and 735 respectively Thelower range of CVI values indicates low risk followed bymoderate risk high risk and finally the upper range of valuesindicating the coastal stretches having very high risk

The present study is an attempt to categorize the coast ofKarnataka according to its coastal vulnerabilities The vari-ables under consideration are sea level change coastal sloperegional elevation tidal range significant wave height andpopulation density A total of 298 km of shoreline are rankedin the study About 6865 km of the shoreline is very high vul-nerable category and 7926 km of shoreline is high vulnerablecategory Of the remaining shoreline 5914 km and 9104 kmare of moderate and low vulnerable categories respectively

Table 5 shows variation of CVI for each talukaThe coastsof Mangaluru and Udupi fall under high risk category andall other talukas are under moderate risk The CVI in thepresent study was primarily influenced by the risk rankingof the shoreline change rate population and the coastalslope It was observed that coasts of Mangaluru Kumta and

Bhatkal were under erosion with an average value of 021013 and 014m per year respectively while for other talukasaccretion was observed The sensitivity of the CVI to thesocioeconomic variable ldquopopulationrdquo was examined and itwas found that CVI significantly decreased in the talukasof Mangaluru Udupi and Karwar on omission of variableand on a relative basis The coastal slope was observed tobe steep in northern talukas that is in Karwar Ankola andKumta while Kundapur Udupi and Mangaluru had mildslope topography This was primarily because in KarwarAnkola andKumtawe find the headlands and cliffs very closeto the coast and southern talukas have more open beaches

5 Conclusion

In the view of the rising sea levels and other coastal hazardsan assessment of coast for its vulnerability to these threatsis necessary in order to take suitable actions to protect thepeople and property It was observed that 6865 km of theshoreline of the study area was under very high vulnerablecategory and 7926 km of shoreline is high vulnerable cate-gory while 5914 km and 9104 km of coast are of moderateand low vulnerable categories respectively Present study alsoevaluated the transformation of theKarnataka coastline usingLandsat satellite images The CVI developed in the presentstudy provides an understanding about the vulnerability ofthe Karnataka Coast to erosion coastal flooding and relativesea level change and as well as facilitates policy options forcoastal planners and authorities with regard to prioritizingcoastal areas for mitigation

Competing Interests

The present study is a work of pure academic researchThe authors declare that there are no competing interestsregarding the publication of this paper

References

[1] F L Alves C Coelho C D Coelho and P Pinto ldquoModellingcoastal vulnerabilities tool for decision support system at inter-municipality levelrdquo Journal of Coastal Research no 64 pp 966ndash970 2011

[2] R J Nicholls and N Mimura ldquoRegional issues raised by sea-level rise and their policy implicationsrdquo Climate Research vol11 no 1 pp 5ndash18 1999

[3] IPCC (Intergovernmental Panel on Climate Change) IPCCReport Working Group-I Climate Change 2001 The ScientificBasis Cambridge University Press Cambridge UK 2001httpwwwipccchipccreportstarwg1408htm

[4] ICZMP ldquoDocument of world bankmdashproject appraisaldocument for an integrated coastal zone management projectrdquoReport 54612-IN Integrated Coastal Zone Management2010 httpwwwsicommoefinDataSites1skinsgec-sicomimagesdocspadpdf

[5] N N V Sudha Rani A N V Satyanarayana and P KBhaskaran ldquoCoastal vulnerability assessment studies overIndia a reviewrdquo Natural Hazards vol 77 no 1 pp 405ndash4282015

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Advances in Civil Engineering 5

Table 3 Mean significant wave height for different talukas as collected from the literatures

Location Mean significant wave height (m) SourceKarwar Ankola amp Kumta 16 Kumar et al [31]Honnavar 19 Kumar et al [31]Kundapur 10 Shanas and Sanil Kumar [39]Bhatkal 125 Nayak et al [40]Udupi (Malpe) 19 Kumar et al [31]Mangaluru 20 Dwarakish et al [28]

36 Significant Wave Height Significant wave height is theaverage height of the one-third highest waves valid for theindicated 12-hour period Mean significant wave height isused as a proxy for wave energy that drives coastal sedimenttransport [46] The vulnerability study based on wave heightis an important step in setting up an all-hazards warning andmanagement system [46]

The movement and transport of coastal sediments aredependent upon the wave energy which varies as the squareof the wave height [47] With increase in the wave height andeventual increase in wave energy land is lost and coast willwitness increased erosion and inundation along the shoreHence the coastal areas of high wave height are consideredas more vulnerable coasts and areas of low wave height asless vulnerable coasts In the present study wave heights inthe study area were collected from the various other studiesconducted primarily onwave characteristics in the study areaTable 3 shows the details of the data collected

37 Population Coastal region has high population densitycompared to upland areas Population can also be interpretedas a direct ldquoerosion-inducingrdquo variable because the presenceof large number of people near the coast may producedamaging impacts on the coastal area [48] Hence presenceof human habitation increases the vulnerability of the regionIn the present study the population was considered as apressure exerting factor on the coastal system and hence areaswith a higher concentration of people are considered as moresusceptible to erosion similar to Hegde and Reju [18]

Worldpop project provides high resolution and contem-porary data on human population distributions for SoutheastAsian countries in raster data format An alpha version dataestimated to match UN population estimate for the year2015 was used in the present study The data set is of rasterformat with resolution of 100m at the equator The assembleof the Worldpop spatial data sets principally follows themethodologies outlined by Gaughan et al [49] Linard et al[50] Linard et al [51] and Tatem et al [52]

38 Calculation of CVI Once each section of coastline isassigned a risk value for each variable the CVI is calculated asthe square root of the product of the ranked variables dividedby the total number of variables [17] The CVI is representedby

CVI = radic119886 lowast 119887 lowast 119888 lowast 119889 lowast 119890 lowast 119891 lowast 119892

7

(1)

where 119886 = risk rating assigned to sea level change rate 119887 =risk rating assigned to shoreline change rate 119888 = risk ratingassigned to coastal slope 119889 = risk rating assigned to coastalregional elevation 119890 = risk rating assigned to tidal range 119891 =risk rating assigned to significant wave height and 119892 = riskrating assigned to population density

4 Results and Discussion

41 Relative Sea Level Change Rate For the available datait was observed that sea level was falling at a rate of 13mmper year at the Karwar station while it was rising at a rate of08mmper year at theMangaluru station as shown in Figures3(a) and 3(b) respectively Douglas [53] acknowledged thatto determine the trends in long-term sea level changes idealrecord length greater than 60 years is desirable Since suchlong duration records were not available for the present studyregion the tide gauge data of Cochin (64 years) was alsoconsidered to verify the trend of SLR and it was observed thatsea level rise was about 10mm per year

Unnikrishnan and Shankar [54] estimated that the sealevel along the Indian coast has increased at a rate varyingbetween 106 and 175mm per year during the period 1969to 2007 depending on the tide gauge recording site with anestimated regional average of 129mmper year subsequent toa global isostatic adjustment correctionThe SLR observed atthe study area is less in comparisonwith global average rate ofabout 17mmper year [55] and also less than regional averageHence the study area is considered to be less vulnerable to sealevel rise and lowest ranking of 1 was awarded for the entirecoast

42 Coastal Slope The regional coastal slope was calculatedfor a distance of 6 km (3 km each from shoreline on seaand landside) perpendicular to the shoreline at an intervalof 15 km The five vulnerability classes and the slope rangein each class are adopted by Pendleton et al [56] A slopegreater than 06 is assigned low vulnerability and less than03 is assigned high vulnerability as shown in Table 4 andaccordingly vulnerability ranks (indicating the vulnerabilitylevels in terms of coastal slope) are assigned to all segmentsof the coast

43 Regional Elevation The mean regional elevation withinstudy area varied between 069m in Mangaluru and 7894min Karwar An elevation value greater than 40m is assignedlow vulnerability and less than 10m is assigned high vul-nerability as shown in Table 4 The minimum value of 10m

6 Advances in Civil Engineering

Sea levelTrend line

y = (minus2658E minus 7)x + 7649

06-2003

06-2008

06-2013

06-1988

06-1983

06-1998

06-1978

06-1973

06-1993

06-1968

Date (mm-yyy)

66

69

72

75

78

81Se

a lev

el (m

)

(a)

81

78

75

72

69

66

Sea l

evel

(m)

y = (4303E minus 6)x minus 3457

06-2004

06-2009

06-1989

06-1984

06-1999

06-1979

06-1994

06-1974

Date (mm-yyy)

Sea levelTrend line

(b)Figure 3 (a) Sea Level variation at Karwar (b) Sea Level variation at Mangaluru

Table 4 Ranges of variables for vulnerability ranking

Variable Ranking of vulnerability1 2 3 4 5

Coastal slope () gt060 05ndash06 04ndash05 03ndash04 lt03Mean tide range (m) lt10 10ndash20 20ndash30 30ndash40 gt40Regional elevation (m) lt10 10ndash20 20ndash30 30ndash40 gt40Shoreline change rate (m yearminus1) gt+20 +10 to +20 minus10 to +10 minus20 to minus10 ltminus20Mean significant wave height (m) lt07 07ndash14 14ndash21 21ndash28 gt28Population (person per 200m2) lt19 44ndash20 80ndash45 326ndash81 gt326

was considered based on the Indian Ocean earthquake of 26December 2004 of magnitude 90 on the Richter scale whichresulted in devastating tsunami along the shores of IndonesiaSri Lanka South India Thailand and other countries withwaves up to 15m high

44 Tidal Range Tidal range is ranked such that microtidal(lt1m) coasts have very low vulnerability and macrotidal(gt6m) coasts have a very high vulnerabilityThe vulnerabilityranking given is taken from the vulnerability ranges of Diezet al [57]The study area is characterized by mesotidal coastsas the tidal range is within 6m but greater than 1m Entirestudy area has fallen into two categories namely very lowvulnerable level (lt10m) and low vulnerable level (10 to20m) as far as the tidal range is considered Accordinglythe entire coast is classified into these two vulnerabilitycategories

45 SignificantWave Height (SWH) Mean SWH in the studyarea varied between 10m and 20m The vulnerability levelswere adopted by Dwarakish et al [28] Kundapur was havinga lowest SWH of 10m while Mangaluru had highest SWH of20m It was assumed that the mean SWH was as per Table 3within the limits of corresponding talukas

46 Shoreline Change Rate The shoreline change rate in thestudy area was calculated for a period of 42 years (1972 to2014) The Output from DSAS revealed that about 409 km

kw05

akw

11kw

16kw

22ak03

aak09

km05

km11

km17

km23

hn06

hn12

bt02

bt08

bt14

kd03

kd09

kd15

kd21

kd27

up05

up11

up17

up23

up29

mn0

2m

n08

mn1

4m

n20minus6

minus4

minus2

0

2

4

6

8

10

Grid ID

LRR

(m ye

arminus

1 )

Figure 4 Mean shoreline change rate along the grids

of coastline had a very high risk rating along the coastalstretch of southern Mangaluru About 1425 km of coastlinewas of high risk rating along the coastal stretches nearsouthern parts of Mangaluru Kundapur and Kumta and alsoin northern Udupi and Bhatkal About 26750 km of coastlinewas under amoderate riskwhile 15 and 1066 km stretchwereunder low and very low risk category respectively Averageaccretion for the whole of the study area was found to be1133m per year and average erosion was 0533m per yearFigure 4 shows the mean shoreline change rate in each grid

Advances in Civil Engineering 7

CVI CVI173ndash450451ndash670

671ndash10391040ndash1897

Karwar Ankola

Kumta Honnavar

Bhatkal

Udupi

Kundapur

Mangaluru

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E 74∘209984000998400998400E74∘159984000998400998400E

74∘209984000998400998400E74∘159984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N 14∘ 40998400 0

998400998400N

14∘ 40998400 0

998400998400N

14∘ 20998400 0

998400998400N

14∘ 15998400 0

998400998400N

14∘ 10998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘259984000998400998400E74∘159984000998400998400E

74∘259984000998400998400E74∘159984000998400998400E

14∘ 35998400 0

998400998400N

14∘ 25998400 0

998400998400N 14∘ 30998400 0

998400998400N

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

13∘ 20998400 0

998400998400N

13∘ 30998400 0

998400998400N

13∘ 10998400 0

998400998400N

13∘ 25998400 0

998400998400N

13∘ 15998400 0

998400998400N

173ndash450451ndash670

671ndash10391040ndash1897

Figure 5 CVI for study area

8 Advances in Civil Engineering

Table 5 CVI for talukas

Taluka CVIMax Min Average 120590

Karwar 1897 424 604 336Ankola 948 367 644 237Kumta 948 367 628 187Honnavar 734 367 520 146Bhatkal 774 173 534 165Kundapur 800 244 589 121Udupi 979 600 778 241Mangaluru 1549 489 794 094

along the study area The risk ranking was awarded basedon the risk category formed by Pendleton et al [56] and isdescribed in Table 4

47 Population Distribution Georeferenced populationraster downloaded from Worldpop project has data valuesvarying from 0 to 326 persons per 200m2 for the study areaThe population is considered to be a stressor variable in thestudy It was assumed that vulnerability varied exponentiallywith population density and the data was classified into 5classes The zones with values equal to or less than 19 personsper 200m2 were awarded with least ranking and regionswith value equal to or more than a value of 326 persons per200m2 were considered as highly vulnerable and highestrank was assigned Table 4 shows the intermediate values forother classes

Coastal Vulnerability Index (CVI) Coastal vulnerability indexmap for the Karnataka Coast is shown in Figure 5 Thecalculated CVI values range from 173 to 1897 Table 5 detailsthe CVI for each taluk with statistical parameters The meanmode andmedian CVI values are 652 734 and 692 respec-tively The standard deviation is 221 The CVI scores aredivided into low moderate high and very high vulnerabilitycategories based on the quartile ranges [56] The 25th 50thand 75th percentiles are 490 692 and 735 respectively Thelower range of CVI values indicates low risk followed bymoderate risk high risk and finally the upper range of valuesindicating the coastal stretches having very high risk

The present study is an attempt to categorize the coast ofKarnataka according to its coastal vulnerabilities The vari-ables under consideration are sea level change coastal sloperegional elevation tidal range significant wave height andpopulation density A total of 298 km of shoreline are rankedin the study About 6865 km of the shoreline is very high vul-nerable category and 7926 km of shoreline is high vulnerablecategory Of the remaining shoreline 5914 km and 9104 kmare of moderate and low vulnerable categories respectively

Table 5 shows variation of CVI for each talukaThe coastsof Mangaluru and Udupi fall under high risk category andall other talukas are under moderate risk The CVI in thepresent study was primarily influenced by the risk rankingof the shoreline change rate population and the coastalslope It was observed that coasts of Mangaluru Kumta and

Bhatkal were under erosion with an average value of 021013 and 014m per year respectively while for other talukasaccretion was observed The sensitivity of the CVI to thesocioeconomic variable ldquopopulationrdquo was examined and itwas found that CVI significantly decreased in the talukasof Mangaluru Udupi and Karwar on omission of variableand on a relative basis The coastal slope was observed tobe steep in northern talukas that is in Karwar Ankola andKumta while Kundapur Udupi and Mangaluru had mildslope topography This was primarily because in KarwarAnkola andKumtawe find the headlands and cliffs very closeto the coast and southern talukas have more open beaches

5 Conclusion

In the view of the rising sea levels and other coastal hazardsan assessment of coast for its vulnerability to these threatsis necessary in order to take suitable actions to protect thepeople and property It was observed that 6865 km of theshoreline of the study area was under very high vulnerablecategory and 7926 km of shoreline is high vulnerable cate-gory while 5914 km and 9104 km of coast are of moderateand low vulnerable categories respectively Present study alsoevaluated the transformation of theKarnataka coastline usingLandsat satellite images The CVI developed in the presentstudy provides an understanding about the vulnerability ofthe Karnataka Coast to erosion coastal flooding and relativesea level change and as well as facilitates policy options forcoastal planners and authorities with regard to prioritizingcoastal areas for mitigation

Competing Interests

The present study is a work of pure academic researchThe authors declare that there are no competing interestsregarding the publication of this paper

References

[1] F L Alves C Coelho C D Coelho and P Pinto ldquoModellingcoastal vulnerabilities tool for decision support system at inter-municipality levelrdquo Journal of Coastal Research no 64 pp 966ndash970 2011

[2] R J Nicholls and N Mimura ldquoRegional issues raised by sea-level rise and their policy implicationsrdquo Climate Research vol11 no 1 pp 5ndash18 1999

[3] IPCC (Intergovernmental Panel on Climate Change) IPCCReport Working Group-I Climate Change 2001 The ScientificBasis Cambridge University Press Cambridge UK 2001httpwwwipccchipccreportstarwg1408htm

[4] ICZMP ldquoDocument of world bankmdashproject appraisaldocument for an integrated coastal zone management projectrdquoReport 54612-IN Integrated Coastal Zone Management2010 httpwwwsicommoefinDataSites1skinsgec-sicomimagesdocspadpdf

[5] N N V Sudha Rani A N V Satyanarayana and P KBhaskaran ldquoCoastal vulnerability assessment studies overIndia a reviewrdquo Natural Hazards vol 77 no 1 pp 405ndash4282015

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

6 Advances in Civil Engineering

Sea levelTrend line

y = (minus2658E minus 7)x + 7649

06-2003

06-2008

06-2013

06-1988

06-1983

06-1998

06-1978

06-1973

06-1993

06-1968

Date (mm-yyy)

66

69

72

75

78

81Se

a lev

el (m

)

(a)

81

78

75

72

69

66

Sea l

evel

(m)

y = (4303E minus 6)x minus 3457

06-2004

06-2009

06-1989

06-1984

06-1999

06-1979

06-1994

06-1974

Date (mm-yyy)

Sea levelTrend line

(b)Figure 3 (a) Sea Level variation at Karwar (b) Sea Level variation at Mangaluru

Table 4 Ranges of variables for vulnerability ranking

Variable Ranking of vulnerability1 2 3 4 5

Coastal slope () gt060 05ndash06 04ndash05 03ndash04 lt03Mean tide range (m) lt10 10ndash20 20ndash30 30ndash40 gt40Regional elevation (m) lt10 10ndash20 20ndash30 30ndash40 gt40Shoreline change rate (m yearminus1) gt+20 +10 to +20 minus10 to +10 minus20 to minus10 ltminus20Mean significant wave height (m) lt07 07ndash14 14ndash21 21ndash28 gt28Population (person per 200m2) lt19 44ndash20 80ndash45 326ndash81 gt326

was considered based on the Indian Ocean earthquake of 26December 2004 of magnitude 90 on the Richter scale whichresulted in devastating tsunami along the shores of IndonesiaSri Lanka South India Thailand and other countries withwaves up to 15m high

44 Tidal Range Tidal range is ranked such that microtidal(lt1m) coasts have very low vulnerability and macrotidal(gt6m) coasts have a very high vulnerabilityThe vulnerabilityranking given is taken from the vulnerability ranges of Diezet al [57]The study area is characterized by mesotidal coastsas the tidal range is within 6m but greater than 1m Entirestudy area has fallen into two categories namely very lowvulnerable level (lt10m) and low vulnerable level (10 to20m) as far as the tidal range is considered Accordinglythe entire coast is classified into these two vulnerabilitycategories

45 SignificantWave Height (SWH) Mean SWH in the studyarea varied between 10m and 20m The vulnerability levelswere adopted by Dwarakish et al [28] Kundapur was havinga lowest SWH of 10m while Mangaluru had highest SWH of20m It was assumed that the mean SWH was as per Table 3within the limits of corresponding talukas

46 Shoreline Change Rate The shoreline change rate in thestudy area was calculated for a period of 42 years (1972 to2014) The Output from DSAS revealed that about 409 km

kw05

akw

11kw

16kw

22ak03

aak09

km05

km11

km17

km23

hn06

hn12

bt02

bt08

bt14

kd03

kd09

kd15

kd21

kd27

up05

up11

up17

up23

up29

mn0

2m

n08

mn1

4m

n20minus6

minus4

minus2

0

2

4

6

8

10

Grid ID

LRR

(m ye

arminus

1 )

Figure 4 Mean shoreline change rate along the grids

of coastline had a very high risk rating along the coastalstretch of southern Mangaluru About 1425 km of coastlinewas of high risk rating along the coastal stretches nearsouthern parts of Mangaluru Kundapur and Kumta and alsoin northern Udupi and Bhatkal About 26750 km of coastlinewas under amoderate riskwhile 15 and 1066 km stretchwereunder low and very low risk category respectively Averageaccretion for the whole of the study area was found to be1133m per year and average erosion was 0533m per yearFigure 4 shows the mean shoreline change rate in each grid

Advances in Civil Engineering 7

CVI CVI173ndash450451ndash670

671ndash10391040ndash1897

Karwar Ankola

Kumta Honnavar

Bhatkal

Udupi

Kundapur

Mangaluru

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E 74∘209984000998400998400E74∘159984000998400998400E

74∘209984000998400998400E74∘159984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N 14∘ 40998400 0

998400998400N

14∘ 40998400 0

998400998400N

14∘ 20998400 0

998400998400N

14∘ 15998400 0

998400998400N

14∘ 10998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘259984000998400998400E74∘159984000998400998400E

74∘259984000998400998400E74∘159984000998400998400E

14∘ 35998400 0

998400998400N

14∘ 25998400 0

998400998400N 14∘ 30998400 0

998400998400N

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

13∘ 20998400 0

998400998400N

13∘ 30998400 0

998400998400N

13∘ 10998400 0

998400998400N

13∘ 25998400 0

998400998400N

13∘ 15998400 0

998400998400N

173ndash450451ndash670

671ndash10391040ndash1897

Figure 5 CVI for study area

8 Advances in Civil Engineering

Table 5 CVI for talukas

Taluka CVIMax Min Average 120590

Karwar 1897 424 604 336Ankola 948 367 644 237Kumta 948 367 628 187Honnavar 734 367 520 146Bhatkal 774 173 534 165Kundapur 800 244 589 121Udupi 979 600 778 241Mangaluru 1549 489 794 094

along the study area The risk ranking was awarded basedon the risk category formed by Pendleton et al [56] and isdescribed in Table 4

47 Population Distribution Georeferenced populationraster downloaded from Worldpop project has data valuesvarying from 0 to 326 persons per 200m2 for the study areaThe population is considered to be a stressor variable in thestudy It was assumed that vulnerability varied exponentiallywith population density and the data was classified into 5classes The zones with values equal to or less than 19 personsper 200m2 were awarded with least ranking and regionswith value equal to or more than a value of 326 persons per200m2 were considered as highly vulnerable and highestrank was assigned Table 4 shows the intermediate values forother classes

Coastal Vulnerability Index (CVI) Coastal vulnerability indexmap for the Karnataka Coast is shown in Figure 5 Thecalculated CVI values range from 173 to 1897 Table 5 detailsthe CVI for each taluk with statistical parameters The meanmode andmedian CVI values are 652 734 and 692 respec-tively The standard deviation is 221 The CVI scores aredivided into low moderate high and very high vulnerabilitycategories based on the quartile ranges [56] The 25th 50thand 75th percentiles are 490 692 and 735 respectively Thelower range of CVI values indicates low risk followed bymoderate risk high risk and finally the upper range of valuesindicating the coastal stretches having very high risk

The present study is an attempt to categorize the coast ofKarnataka according to its coastal vulnerabilities The vari-ables under consideration are sea level change coastal sloperegional elevation tidal range significant wave height andpopulation density A total of 298 km of shoreline are rankedin the study About 6865 km of the shoreline is very high vul-nerable category and 7926 km of shoreline is high vulnerablecategory Of the remaining shoreline 5914 km and 9104 kmare of moderate and low vulnerable categories respectively

Table 5 shows variation of CVI for each talukaThe coastsof Mangaluru and Udupi fall under high risk category andall other talukas are under moderate risk The CVI in thepresent study was primarily influenced by the risk rankingof the shoreline change rate population and the coastalslope It was observed that coasts of Mangaluru Kumta and

Bhatkal were under erosion with an average value of 021013 and 014m per year respectively while for other talukasaccretion was observed The sensitivity of the CVI to thesocioeconomic variable ldquopopulationrdquo was examined and itwas found that CVI significantly decreased in the talukasof Mangaluru Udupi and Karwar on omission of variableand on a relative basis The coastal slope was observed tobe steep in northern talukas that is in Karwar Ankola andKumta while Kundapur Udupi and Mangaluru had mildslope topography This was primarily because in KarwarAnkola andKumtawe find the headlands and cliffs very closeto the coast and southern talukas have more open beaches

5 Conclusion

In the view of the rising sea levels and other coastal hazardsan assessment of coast for its vulnerability to these threatsis necessary in order to take suitable actions to protect thepeople and property It was observed that 6865 km of theshoreline of the study area was under very high vulnerablecategory and 7926 km of shoreline is high vulnerable cate-gory while 5914 km and 9104 km of coast are of moderateand low vulnerable categories respectively Present study alsoevaluated the transformation of theKarnataka coastline usingLandsat satellite images The CVI developed in the presentstudy provides an understanding about the vulnerability ofthe Karnataka Coast to erosion coastal flooding and relativesea level change and as well as facilitates policy options forcoastal planners and authorities with regard to prioritizingcoastal areas for mitigation

Competing Interests

The present study is a work of pure academic researchThe authors declare that there are no competing interestsregarding the publication of this paper

References

[1] F L Alves C Coelho C D Coelho and P Pinto ldquoModellingcoastal vulnerabilities tool for decision support system at inter-municipality levelrdquo Journal of Coastal Research no 64 pp 966ndash970 2011

[2] R J Nicholls and N Mimura ldquoRegional issues raised by sea-level rise and their policy implicationsrdquo Climate Research vol11 no 1 pp 5ndash18 1999

[3] IPCC (Intergovernmental Panel on Climate Change) IPCCReport Working Group-I Climate Change 2001 The ScientificBasis Cambridge University Press Cambridge UK 2001httpwwwipccchipccreportstarwg1408htm

[4] ICZMP ldquoDocument of world bankmdashproject appraisaldocument for an integrated coastal zone management projectrdquoReport 54612-IN Integrated Coastal Zone Management2010 httpwwwsicommoefinDataSites1skinsgec-sicomimagesdocspadpdf

[5] N N V Sudha Rani A N V Satyanarayana and P KBhaskaran ldquoCoastal vulnerability assessment studies overIndia a reviewrdquo Natural Hazards vol 77 no 1 pp 405ndash4282015

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Advances in Civil Engineering 7

CVI CVI173ndash450451ndash670

671ndash10391040ndash1897

Karwar Ankola

Kumta Honnavar

Bhatkal

Udupi

Kundapur

Mangaluru

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E

74∘159984000998400998400E74∘109984000998400998400E74∘59984000998400998400E 74∘209984000998400998400E74∘159984000998400998400E

74∘209984000998400998400E74∘159984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

74∘309984000998400998400E74∘259984000998400998400E74∘209984000998400998400E

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N

14∘ 50998400 0

998400998400N

14∘ 45998400 0

998400998400N 14∘ 40998400 0

998400998400N

14∘ 40998400 0

998400998400N

14∘ 20998400 0

998400998400N

14∘ 15998400 0

998400998400N

14∘ 10998400 0

998400998400N

14∘ 15998400 0

998400998400N

74∘259984000998400998400E74∘159984000998400998400E

74∘259984000998400998400E74∘159984000998400998400E

14∘ 35998400 0

998400998400N

14∘ 25998400 0

998400998400N 14∘ 30998400 0

998400998400N

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘359984000998400998400E74∘309984000998400998400E74∘259984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

74∘509984000998400998400E74∘409984000998400998400E74∘309984000998400998400E

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

14∘ 5

998400 0998400998400

N14∘ 0

998400 0998400998400

N

13∘ 50998400 0

998400998400N

13∘ 40998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

13∘ 5

998400 0998400998400

N12∘ 55998400 0

998400998400N

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

74∘559984000998400998400E74∘459984000998400998400E74∘359984000998400998400E

13∘ 20998400 0

998400998400N

13∘ 30998400 0

998400998400N

13∘ 10998400 0

998400998400N

13∘ 25998400 0

998400998400N

13∘ 15998400 0

998400998400N

173ndash450451ndash670

671ndash10391040ndash1897

Figure 5 CVI for study area

8 Advances in Civil Engineering

Table 5 CVI for talukas

Taluka CVIMax Min Average 120590

Karwar 1897 424 604 336Ankola 948 367 644 237Kumta 948 367 628 187Honnavar 734 367 520 146Bhatkal 774 173 534 165Kundapur 800 244 589 121Udupi 979 600 778 241Mangaluru 1549 489 794 094

along the study area The risk ranking was awarded basedon the risk category formed by Pendleton et al [56] and isdescribed in Table 4

47 Population Distribution Georeferenced populationraster downloaded from Worldpop project has data valuesvarying from 0 to 326 persons per 200m2 for the study areaThe population is considered to be a stressor variable in thestudy It was assumed that vulnerability varied exponentiallywith population density and the data was classified into 5classes The zones with values equal to or less than 19 personsper 200m2 were awarded with least ranking and regionswith value equal to or more than a value of 326 persons per200m2 were considered as highly vulnerable and highestrank was assigned Table 4 shows the intermediate values forother classes

Coastal Vulnerability Index (CVI) Coastal vulnerability indexmap for the Karnataka Coast is shown in Figure 5 Thecalculated CVI values range from 173 to 1897 Table 5 detailsthe CVI for each taluk with statistical parameters The meanmode andmedian CVI values are 652 734 and 692 respec-tively The standard deviation is 221 The CVI scores aredivided into low moderate high and very high vulnerabilitycategories based on the quartile ranges [56] The 25th 50thand 75th percentiles are 490 692 and 735 respectively Thelower range of CVI values indicates low risk followed bymoderate risk high risk and finally the upper range of valuesindicating the coastal stretches having very high risk

The present study is an attempt to categorize the coast ofKarnataka according to its coastal vulnerabilities The vari-ables under consideration are sea level change coastal sloperegional elevation tidal range significant wave height andpopulation density A total of 298 km of shoreline are rankedin the study About 6865 km of the shoreline is very high vul-nerable category and 7926 km of shoreline is high vulnerablecategory Of the remaining shoreline 5914 km and 9104 kmare of moderate and low vulnerable categories respectively

Table 5 shows variation of CVI for each talukaThe coastsof Mangaluru and Udupi fall under high risk category andall other talukas are under moderate risk The CVI in thepresent study was primarily influenced by the risk rankingof the shoreline change rate population and the coastalslope It was observed that coasts of Mangaluru Kumta and

Bhatkal were under erosion with an average value of 021013 and 014m per year respectively while for other talukasaccretion was observed The sensitivity of the CVI to thesocioeconomic variable ldquopopulationrdquo was examined and itwas found that CVI significantly decreased in the talukasof Mangaluru Udupi and Karwar on omission of variableand on a relative basis The coastal slope was observed tobe steep in northern talukas that is in Karwar Ankola andKumta while Kundapur Udupi and Mangaluru had mildslope topography This was primarily because in KarwarAnkola andKumtawe find the headlands and cliffs very closeto the coast and southern talukas have more open beaches

5 Conclusion

In the view of the rising sea levels and other coastal hazardsan assessment of coast for its vulnerability to these threatsis necessary in order to take suitable actions to protect thepeople and property It was observed that 6865 km of theshoreline of the study area was under very high vulnerablecategory and 7926 km of shoreline is high vulnerable cate-gory while 5914 km and 9104 km of coast are of moderateand low vulnerable categories respectively Present study alsoevaluated the transformation of theKarnataka coastline usingLandsat satellite images The CVI developed in the presentstudy provides an understanding about the vulnerability ofthe Karnataka Coast to erosion coastal flooding and relativesea level change and as well as facilitates policy options forcoastal planners and authorities with regard to prioritizingcoastal areas for mitigation

Competing Interests

The present study is a work of pure academic researchThe authors declare that there are no competing interestsregarding the publication of this paper

References

[1] F L Alves C Coelho C D Coelho and P Pinto ldquoModellingcoastal vulnerabilities tool for decision support system at inter-municipality levelrdquo Journal of Coastal Research no 64 pp 966ndash970 2011

[2] R J Nicholls and N Mimura ldquoRegional issues raised by sea-level rise and their policy implicationsrdquo Climate Research vol11 no 1 pp 5ndash18 1999

[3] IPCC (Intergovernmental Panel on Climate Change) IPCCReport Working Group-I Climate Change 2001 The ScientificBasis Cambridge University Press Cambridge UK 2001httpwwwipccchipccreportstarwg1408htm

[4] ICZMP ldquoDocument of world bankmdashproject appraisaldocument for an integrated coastal zone management projectrdquoReport 54612-IN Integrated Coastal Zone Management2010 httpwwwsicommoefinDataSites1skinsgec-sicomimagesdocspadpdf

[5] N N V Sudha Rani A N V Satyanarayana and P KBhaskaran ldquoCoastal vulnerability assessment studies overIndia a reviewrdquo Natural Hazards vol 77 no 1 pp 405ndash4282015

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

8 Advances in Civil Engineering

Table 5 CVI for talukas

Taluka CVIMax Min Average 120590

Karwar 1897 424 604 336Ankola 948 367 644 237Kumta 948 367 628 187Honnavar 734 367 520 146Bhatkal 774 173 534 165Kundapur 800 244 589 121Udupi 979 600 778 241Mangaluru 1549 489 794 094

along the study area The risk ranking was awarded basedon the risk category formed by Pendleton et al [56] and isdescribed in Table 4

47 Population Distribution Georeferenced populationraster downloaded from Worldpop project has data valuesvarying from 0 to 326 persons per 200m2 for the study areaThe population is considered to be a stressor variable in thestudy It was assumed that vulnerability varied exponentiallywith population density and the data was classified into 5classes The zones with values equal to or less than 19 personsper 200m2 were awarded with least ranking and regionswith value equal to or more than a value of 326 persons per200m2 were considered as highly vulnerable and highestrank was assigned Table 4 shows the intermediate values forother classes

Coastal Vulnerability Index (CVI) Coastal vulnerability indexmap for the Karnataka Coast is shown in Figure 5 Thecalculated CVI values range from 173 to 1897 Table 5 detailsthe CVI for each taluk with statistical parameters The meanmode andmedian CVI values are 652 734 and 692 respec-tively The standard deviation is 221 The CVI scores aredivided into low moderate high and very high vulnerabilitycategories based on the quartile ranges [56] The 25th 50thand 75th percentiles are 490 692 and 735 respectively Thelower range of CVI values indicates low risk followed bymoderate risk high risk and finally the upper range of valuesindicating the coastal stretches having very high risk

The present study is an attempt to categorize the coast ofKarnataka according to its coastal vulnerabilities The vari-ables under consideration are sea level change coastal sloperegional elevation tidal range significant wave height andpopulation density A total of 298 km of shoreline are rankedin the study About 6865 km of the shoreline is very high vul-nerable category and 7926 km of shoreline is high vulnerablecategory Of the remaining shoreline 5914 km and 9104 kmare of moderate and low vulnerable categories respectively

Table 5 shows variation of CVI for each talukaThe coastsof Mangaluru and Udupi fall under high risk category andall other talukas are under moderate risk The CVI in thepresent study was primarily influenced by the risk rankingof the shoreline change rate population and the coastalslope It was observed that coasts of Mangaluru Kumta and

Bhatkal were under erosion with an average value of 021013 and 014m per year respectively while for other talukasaccretion was observed The sensitivity of the CVI to thesocioeconomic variable ldquopopulationrdquo was examined and itwas found that CVI significantly decreased in the talukasof Mangaluru Udupi and Karwar on omission of variableand on a relative basis The coastal slope was observed tobe steep in northern talukas that is in Karwar Ankola andKumta while Kundapur Udupi and Mangaluru had mildslope topography This was primarily because in KarwarAnkola andKumtawe find the headlands and cliffs very closeto the coast and southern talukas have more open beaches

5 Conclusion

In the view of the rising sea levels and other coastal hazardsan assessment of coast for its vulnerability to these threatsis necessary in order to take suitable actions to protect thepeople and property It was observed that 6865 km of theshoreline of the study area was under very high vulnerablecategory and 7926 km of shoreline is high vulnerable cate-gory while 5914 km and 9104 km of coast are of moderateand low vulnerable categories respectively Present study alsoevaluated the transformation of theKarnataka coastline usingLandsat satellite images The CVI developed in the presentstudy provides an understanding about the vulnerability ofthe Karnataka Coast to erosion coastal flooding and relativesea level change and as well as facilitates policy options forcoastal planners and authorities with regard to prioritizingcoastal areas for mitigation

Competing Interests

The present study is a work of pure academic researchThe authors declare that there are no competing interestsregarding the publication of this paper

References

[1] F L Alves C Coelho C D Coelho and P Pinto ldquoModellingcoastal vulnerabilities tool for decision support system at inter-municipality levelrdquo Journal of Coastal Research no 64 pp 966ndash970 2011

[2] R J Nicholls and N Mimura ldquoRegional issues raised by sea-level rise and their policy implicationsrdquo Climate Research vol11 no 1 pp 5ndash18 1999

[3] IPCC (Intergovernmental Panel on Climate Change) IPCCReport Working Group-I Climate Change 2001 The ScientificBasis Cambridge University Press Cambridge UK 2001httpwwwipccchipccreportstarwg1408htm

[4] ICZMP ldquoDocument of world bankmdashproject appraisaldocument for an integrated coastal zone management projectrdquoReport 54612-IN Integrated Coastal Zone Management2010 httpwwwsicommoefinDataSites1skinsgec-sicomimagesdocspadpdf

[5] N N V Sudha Rani A N V Satyanarayana and P KBhaskaran ldquoCoastal vulnerability assessment studies overIndia a reviewrdquo Natural Hazards vol 77 no 1 pp 405ndash4282015

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

Advances in Civil Engineering 9

[6] T S Kumar R S Mahendra S Nayak K Radhakrishnan andK C Sahu ldquoCoastal vulnerability assessment for Orissa StateEast Coast of Indiardquo Journal of Coastal Research vol 26 no 3pp 523ndash534 2010

[7] S L Cutter J T Mitchell and M S Scott ldquoRevealing thevulnerability of people and places a case study of GeorgetownCounty South Carolinardquo Annals of the Association of AmericanGeographers vol 90 no 4 pp 713ndash737 2000

[8] A Parthasarathy and U Natesan ldquoCoastal vulnerability assess-ment a case study on erosion and coastal change alongTuticorin Gulf of Mannarrdquo Natural Hazards vol 75 no 2 pp1713ndash1729 2015

[9] E R Thieler and E S Hammar-Klose ldquoNational assessment ofcoastal vulnerability to sea level riserdquo US Atlantic Coast USGeological Survey Open-File Report 99-593 1999

[10] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Gulf of Mexico Coast United States Geological Survey(USGS) Woods Hole Mass USA 2000

[11] E R Thieler and E S Hammer-Klose National Assessment ofCoastal Vulnerability to Sea-Level Rise Preliminary Results forthe US Pacific Coast United States Geological Survey (USGS)Woods Hole Mass USA 2000

[12] V M Gornitz R C Daniel T W White and K R BirdwellldquoThe development of a coastal risk assessment database vulner-ability to sea-level rise in the US Southeastrdquo Journal of CoastalResearch no 12 pp 327ndash338 1994

[13] B J Boruff C Emrich and S L Cutter ldquoErosion hazard vulner-ability of US coastal countiesrdquo Journal of Coastal Research vol21 no 5 pp 932ndash942 2005

[14] G Ozyurt andA Ergin ldquoApplication of sea level rise vulnerabil-ity assessmentmodel to selected coastal areas of Turkeyrdquo Journalof Coastal Research vol 1 no 56 pp 248ndash251 2009

[15] F Duriyapong and K Nakhapakorn ldquoCoastal vulnerabilityassessment a case study of Samut Sakhon coastal zonerdquo Songk-lanakarin Journal of Science and Technology vol 33 no 4 pp469ndash476 2011

[16] V M Gornitz ldquoVulnerability of the east coast USA to futuresea level riserdquo Journal of Coastal Research vol 9 pp 201ndash2371990

[17] E A Pendleton E R Thieler and S W Jeffress ldquoCoastalvulnerability assessment of golden gate national recreation areato sea level riserdquo USGS Open-File Report 1058 2005

[18] A V Hegde and V R Reju ldquoDevelopment of coastal vulner-ability index for Mangalore coast Indiardquo Journal of CoastalResearch vol 23 no 5 pp 1106ndash1111 2007

[19] J R Jensen and D L Toll ldquoDetecting residential land-usedevelopment at the urban fringerdquo Photogrammetric Engineeringamp Remote Sensing vol 48 no 4 pp 629ndash643 1982

[20] M El Raey ldquoRemote sensing of environmentrdquo in Proceedingof the 1st Symposium on Environmental Sciences (UNARC rsquo88)Alexandria University Alexandria Egypt April 1988

[21] G N Nayak and P T Hanamgond Encyclopaedia of the WorldrsquosCoastal Landforms Springer New York NY USA 2010

[22] K Nageswara Rao P Subraelu T Venkateswara Rao et al ldquoSea-level rise and coastal vulnerability an assessment of AndhraPradesh coast India through remote sensing and GISrdquo Journalof Coastal Conservation vol 12 no 4 pp 195ndash207 2009

[23] P SheikMujabar and N Chandrasekar ldquoCoastal erosion hazardand vulnerability assessment for southern coastal TamilNadu ofIndia by using remote sensing and GISrdquo Natural Hazards vol69 no 3 pp 1295ndash1314 2013

[24] A A Kumar and P D Kunte ldquoCoastal vulnerability assessmentfor Chennai east coast of India using geospatial techniquesrdquoNatural Hazards vol 64 no 1 pp 853ndash872 2012

[25] A Jana and A K Bhattacharya ldquoAssessment of coastal erosionvulnerability around Midnapur-Balasore coast Eastern Indiausing integrated remote sensing and GIS techniquesrdquo Journal ofthe Indian Society of Remote Sensing vol 41 no 3 pp 675ndash6862013

[26] P D Kunte N Jauhari U Mehrotra M Kotha A S Hurst-house and A S Gagnon ldquoMulti-hazards coastal vulnerabilityassessment of Goa India using geospatial techniquesrdquo Oceanamp Coastal Management vol 95 pp 264ndash281 2014

[27] M Mahapatra R Ramakrishnan and A S Rajawat ldquoCoastalvulnerability assessment using analytical hierarchical processfor South Gujarat coast Indiardquo Natural Hazards vol 76 no 1pp 139ndash159 2015

[28] G S Dwarakish S A Vinay U Natesan et al ldquoCoastalvulnerability assessment of the future sea level rise in Udupicoastal zone of Karnataka state west coast of Indiardquo Ocean ampCoastal Management vol 52 no 9 pp 467ndash478 2009

[29] L R Appelquist and T Balstroslashm ldquoApplication of a newmethodology for coastal multi-hazard-assessment amp manage-ment on the state of Karnataka Indiardquo Journal of EnvironmentalManagement vol 152 10 pages 2015

[30] J Dattatri Coastal Erosion and Protection along KarnatakaCoast Centre for Environmental Law Education Researchand Advocacy (CEERA) The National Law School of IndiaUniversity 2007

[31] V S Kumar G U Dora S Philip P Pednekar and J SinghldquoVariations in tidal constituents along the nearshore waters ofKarnataka West Coast of Indiardquo Journal of Coastal Researchvol 27 no 5 pp 824ndash829 2011

[32] S Nayak ldquoRole of remote sensing to integrated coastal zonemanagementrdquo in Proceedings of the 20th Congress of theInternational Society for Photogrammetry and Remote SensingCommission vol 7 p 18 Istanbul Turkey 2004

[33] P A O Abuodha and C DWoodroffe ldquoAssessing vulnerabilityto sea-level rise using a coastal sensitivity index a case studyfrom southeast Australiardquo Journal of Coastal Conservation vol14 no 3 pp 189ndash205 2010

[34] S B Mukesh ldquoCoastal vulnerability adaptation and riskassessment due to environmental change in Apodi Mossoroestuary Northeast Brazilrdquo International Journal of Geomaticsand Geosciences vol 1 no 3 pp 620ndash638 2010

[35] R J Nicholls P P Wong V R Burkett et al ldquoCoastalsystems and low-lying areasrdquo in Climate Change 2007 ImpactsAdaptation and Vulnerability Contribution of Working Group IIto the Fourth Assessment Report of the Intergovernmental Panelon Climate Change M L Parry O F Canziani J P PalutikofP J van der Linden and C E Hanson Eds chapter 6 pp 315ndash356 Cambridge University Press Cambridge UK 2007

[36] J A Church and J M Gregory Climate Change 2001 WorkingGroup I The Scientific Basis chapter 11 International Panel onClimate Change 2001

[37] V S Kumar K C Pathak P Pednekar N S N Raju andR Gowthaman ldquoCoastal processes along the Indian coastlinerdquoCurrent Science vol 91 no 4 pp 530ndash536 2006

[38] V Sanil Kumar G Johnson G Udhaba Dora S P ChempalayilJ Singh and P Pednekar ldquoVariations in nearshore waves alongKarnataka west coast of Indiardquo Journal of Earth System Sciencevol 121 no 2 pp 393ndash403 2012

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

10 Advances in Civil Engineering

[39] P R Shanas and V Sanil Kumar ldquoCoastal processes andlongshore sediment transport along Kundapura coast centralwest coast of IndiardquoGeomorphology vol 214 pp 436ndash451 2014

[40] S R Nayak V S Hegde G Shalini et al ldquoGeomorphicprocesses in the vicinity of the venkatapur river mouth centralwest coast of india implications for estuarine sedimentationrdquoJournal of Coastal Research vol 26 no 5 pp 925ndash934 2010

[41] R J Savage and E R Foster ldquoHistorical shoreline changein southeast Floridardquo in Coastal Zone rsquo89 O T Magoon HConverse D Miner L T Tobin and D Clark Eds pp 4406ndash4433 American Society of Civil Engineers Reston Va USA1989

[42] E R Thieler E A Himmelstoss J L Zichichi and T LMiller ldquoDigital Shoreline Analysis System (DSAS) version 30an ArcGIS extension for calculating shoreline changerdquo USGeological Survey Open-File Report 2005-1304 2005

[43] MCrowell and S P Leatherman ldquoCoastal erosionmapping andmanagementrdquo Journal of Coastal Research vol 28 pp 1ndash1961999

[44] E R Thieler ldquoNational assessment of coastal vulnerability tofuture sea-level riserdquo USGS Fact Sheet FS-076-00 US Geologi-cal Survey 2000 httppubsusgsgov

[45] K E Anderson D R Cahoon B Guitierrez and E R ThielerldquoThe physical environmentrdquo Public Review Draft US ClimateChange Science Program Environmental Protection AgencyWashington DC USA 2005

[46] USGS ldquoThe Digital Shoreline Analysis System (DSAS) version30 an ArcGIS extension for calculating histrionic shorelinechangerdquo Open-File Report 2005-1304 2005 httpwoodsholeerusgsgovproject-pagesDSASversion3

[47] USGS (US Geological Survey) National Assessment of CoastalVulnerability to Sea level Rise Preliminary Results for the USGulf of Mexico Coast 2001 httppubsusgsgovof2000of00-179pagesriskhtml

[48] S McLaughlin J McKenna and J A G Cooper ldquoSocio-economic data in coastal vulnerability indices constraints andopportunitiesrdquo Journal of Coastal Research vol 36 pp 487ndash4972002

[49] A E Gaughan F R Stevens C Linard P Jia and A J TatemldquoHigh resolution population distribution maps for SoutheastAsia in 2010 and 2015rdquo PLoS ONE vol 8 no 2 Article IDe55882 2013

[50] C Linard M Gilbert R W Snow A M Noor and A J TatemldquoPopulation distribution settlement patterns and accessibilityacross Africa in 2010rdquo PLoS ONE vol 7 no 2 Article ID e317432012

[51] C Linard V A Alegana A M Noor R W Snow and AJ Tatem ldquoA high resolution spatial population database ofSomalia for disease risk mappingrdquo International Journal ofHealth Geographics vol 9 article 45 2010

[52] A J Tatem A M Noor C von Hagen A Di Gregorio and S IHay ldquoHigh resolution populationmaps for low income nationscombining land cover and census in East Africardquo PLoS ONEvol 2 no 12 Article ID e1298 2007

[53] B C Douglas ldquoSea level change in the era of the recordingtidegauge in Sea Level Riserdquo in International GeophysicalService B C Douglas M S Kearney and S P LeathermanEds vol 75 pp 37ndash64 Elsevier New York NY USA 2001

[54] A S Unnikrishnan and D Shankar ldquoAre sea-level-rise trendsalong the coasts of the north Indian Ocean consistent withglobal estimatesrdquoGlobal and Planetary Change vol 57 no 3-4pp 301ndash307 2007

[55] J A Church and N J White ldquoA 20th century acceleration inglobal sea level riserdquo Geophysical Research Letters vol 33 no 12006

[56] E A Pendleton S J Williams and E R Thieler ldquoCoastalvulnerability assessment of assateague island national seashore(ASIS) to sea-level riserdquo US Geological Survey Open-FileReport 2004-1020 2004

[57] P G Diez G M E Perillo and M C Piccolo ldquoVulnerability tosea-level rise on the coast of the Buenos Aires provincerdquo Journalof Coastal Research vol 23 no 1 pp 119ndash142 2007

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of

International Journal of

AerospaceEngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

RoboticsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Active and Passive Electronic Components

Control Scienceand Engineering

Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Shock and Vibration

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Civil EngineeringAdvances in

Acoustics and VibrationAdvances in

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Electrical and Computer Engineering

Journal of

Advances inOptoElectronics

Hindawi Publishing Corporation httpwwwhindawicom

Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Chemical EngineeringInternational Journal of Antennas and

Propagation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Navigation and Observation

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

DistributedSensor Networks

International Journal of