Chapter 2. Literature Survey 2.1 Background of landusellandcover...
Transcript of Chapter 2. Literature Survey 2.1 Background of landusellandcover...
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Chapter 2. Literature Survey
2.1 Background of landusellandcover studies and pioneering works
Historically, human was dependant on surrounding for food, cloth or shelter. He
would hunt or look for fruits available around him when he would be hungry. He
was using leaves for covering body and caves for shelter. The very idea of
reproduction of seeds leads to the agriculture on land, which may be the primitive
use of land. The initial record of landuse in recent history in the form of land
record is available for agriculture land around the Nile River. As the floods would
ruin their crops, they put boundaries around the fields to prevent the flood and
assess individual loss (Anonymous). Colonies and settlements were established
mainly on the riverbank or on the coast as it provides them their basic needs for
food and shelter. The 'colony' concept provides a kind of protection also. This
plays an important role in the history of landuse. Human uses land as an eco
system (Vink, 1975). As the population keep on increasing, land availability
becomes important issue. Major threats in coastal area are listed and very well
addressed by Clark in the Manual of Coastal Zone Management (Clark,
1992, 1996).
In India, basically kings levied land-taxes, but there were no land records.
Earliest recorded efforts of preparing sketches, compilation and codification of
laws and rules were carried out during the Mauryas (321 - 184 B. C.) and
Harsha (606- 647 A. D.). Systematic land- tax rules were introduced by Sher
Shah (1540- 1545 A. D.). Raja Todar mal, architect of land settlement pattern,
first initiated his work in 1573 in Gujarat, started first land record system with land
ownership pattern. The prime interest of these exercises was to collect revenue
(Singh, 1989). Most of the countries use aerial photographs for survey purpose.
In India, the SurvEi~ of India started using aerial photographs around 1950.
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Initial space missions conducted by USSR and US provided initial photographs of
the earth and it opened a new dimension to the study of earth resources (Colwell,
R. N., 1983). With the availability of the initial LANDSAT (ERTS-1) images,
Anderson proposed the land use and landcover classification system (Anderson
et al., 1976). Researchers used remote sensing satellite data more for landuse
/landcover studies than any other discipline (Cihlar, 2000). In India, initially
Gautam (1989) carried out landuse/landcover studies at National remote Sensing
Agency (NRSA). Prior to that, the All India Soil and Landuse Survey (AIS&LUS)
were conducting landuse survey using conventional methods.
For coastal landuse/landcover study, Klemas (1975) has done initial work and
proposed a classification of various coastal features. In India, initially coastal
landuse/landcover study carried out at the Space Applications Centre (SAC)
(Nayak et al. 1984, Nayak et al. 1985). Nationwide database using various
coastal themes has been prepared at SAC (Anonymus, 1992).
2.2 Landuse models
A model can be defined as "a simplified representation of an object of
investigation for purpose of description, explanation, forecasting or planning" in
'Spatial model and GIS' (Camara, 1996). According to him, spatial model has two
dimensions space and attributes where as spatia-temporal model has space,
time and attributes. Various classification of spatial model are based on their
degree of formation, scale, conceptual and mathematical models (Steyaert,
1993). Other classification of spatial model based on how they deal with the
phenomenon (Berry, 1995). It can be classified based on their static ness or
dynamism. It also can be classified as per their space and time resolution. In
addition to this, spatial models can be classified based on their structure;
comprehensiveness, theoretical foundation or the modelling technique applied. . ...
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Skidmore (2002) explained taxonomy of environmental models available from
GIS and environment literature and classify them as 'models of logic' and 'model
based on processing method'. Logical methods can be inductive or deductive
type; where as processing method model can be deterministic or stochastic type.
The deterministic can be subdivided into empirical, process-based and
knowledge-based model. The complex model may be a combination of methods.
In such case, one should be carefully identify components of the models to hold
the taxonomy of the model. As per the Michael Wagener (Camara, 1996) the
scale of the spatial models ranges from sub-molecular to astronomical scale.
Example includes from weather forecasting models, climate models, air and
liquid dispersion models, chemical reaction models, rainfall-runoff models,
ground water models, soil erosion models, biological ecosystem models, energy
system models, noise propagation model·and landuse/landcover models.
Jakeman and his co-authors (Jakeman et al, 1993) in their book ' Modelling
change in environmental systems' defines the procedure and method of the
constructing and evaluating mathematical models of the behavior of
environmental systems. According to them, the purpose for which model is to be
used will influence the form of model and its way of development. They divide
procedure of the development of model in two broad categories. Analyst with his
knowledge and imagination and without any in-situ field data can develop it. This
is called synthesis, having steps of a) conceptulisation, b) computational
. representation, usually in the different equation form or as linguistic rules or as
the rule of cellular automata c) numerical solution algorithms of differential
equations. The other model development part, called as analysis. This involves
evaluating the model against in-situ field data, and having steps, d) evaluation of
hypothesis and model structure identification, e) Parameter estimation and
analysis of the identifiably of the model, f) statistical checks and g) validation and
forecasting.
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Though model in one form or other, is used to explain scientific phenomenon,
evolution of models goes in hand in hand with development of mathematics.
Differential equations and statistics have long historical association with model
development. Development of computers eases the limitation of human
computation power and with advancement in hardware and software help in
modelling complex phenomenon and interactions. Linguistic rules of the
conditions (IF -THEN) are part of our logical thinking and it can be realised and
manipulated through the programming language of artificial intelligence and
expert systems.
The Geographic Information System (GIS) also boost the modelling capabilities.
GIS can handle input, store, manipulate and provide output with overlaying and
for varying conditions. Thus its data manipulation and visualisation capabilities
can be used in model building and/or model evaluation. Camara (Camara, 1996)
discussed modelling using GIS and reported that spatial statistics and models to
analyse spatial data make up an area covering models for spatial point
processes, image analysis and gee-statistic methods. Though GIS helped to
boost the modelling, basically it is static system having rich database. Camara
classify three separate categories of combining dynamic models with GIS. They
are a) dynamic models are used spatially aggregated variables but their result
may be modified, b) active area dynamic and c) classical transport model. Most
of these models are governed by equations of Physics. The forth category
according to Camara, based on Object oriented representation, for natural
systems perceived as a set of interacting entities and not as a set of processes
representing theoretical principles (Tofoli and Mgrgdus, 1987, 1984).
2.3 Global landuse models
Cihlar discussed the status and research priorities in his article for landuse/
landcover studies (Cihlar, 2000). According to him, studying landcover is
important for understanding the climatic changes and for policy purposes. It is
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important factor in deciding the landuse and other value of the land to society.
Land cover varies at a spatial rate from local to global. Locally it is required for
micro-level planning and field implementation. While at regional level, it is
required for the modelling the policy scenario and to forecast the environmental
impact of policies. At regional and national level, it helped in integrated and
sustainable management. At global level, it is required for global change
research, modelling the global studies on environment and framing and
implementing the international polices (McConnell and Moran, 2002). It varies
from days (in case of forest fire, tidal variations) to millennia (green house effect).
For studying (observations and monitoring) the large area at regional to global
level, remote sensing with its synoptic and repetitive capabilities is a logical
solution. Any remote sensing product in picture form is basically first hand land
use landcover information. Land cover and land use studies using aerial
photographs have a long history and well described in the Manual for
Photographic Interpretation (Colwell, 1960). Most of studies using satellite data
were carried out with moderate spatial resolution ranging 30 - 80 m (Cihlar,
2000). These studies were at local to regional level. Land use I land cover
mapping over a large area at national or global scale were not attempted
because of high cost of data, requirement of user community, technical
limitations like resolution, swath and other parameters, for global level analysis,
and availability of landusellandcover data sets compiled from ground survey and
national sources (Mathews et al. 1983). Ground based system has its own
limitations, due to number of sources of error, consistent definition of land cover
type and data with variable reliability and national policies of landuse/landcover
map availability (De Fries, 1994, 2000, Townshend et al 1991 ). The importance of
role of land use/ landcover in regulating climate, illustrated by studies of land
cover change with general circulation models (Shukla et al. 1990, Henderson -
seller, 1993). Satellite data because of consistent and repetitive nature, provides
a good source of landcover information. In additio-.to this, there are many other
factors which are discussed in detail by De Fries (2000), boost the new interest in
the landuse/landcover studies. These factors are mainly
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1. Recognisation that accurate landusellandcover information is an essential
requisite for science and policy applications:
As discussed previously, accurate landcover information is very essential in
climate models at regional and global level. In addition to this, landcover
change information is included in international agreements such as Kyoto
protocol to the United Nations framework convention on climate change
(IGBP 1998).
Following are the important articles of the Kyoto Protocol.
i) Article 3: Change in carbon stocks resulting from human
induced landuse changes and forestry activities.
ii) Article 12: Monitoring human induced landuse changes
and forecasting activities under the clean development
mechanism.
iii) Article 6 &7: Monitoring of the transformation of emission
reduction limits resulting from projects, which enhances
anthropogenic removal by sink.
iv) Article 10: systematic observation and the development of
data archives to reduce uncertainties related to climate
system.
2. Improved computing capabilities and analysis techniques:
Large. storage and computational complexity were the limiting factor in the
past for the satellite data analysis. The development in computer field made it
possible now to compute the complex problem on single PC based software.
In addition to these new technologies like GIS, Neural network, fussy logic,
end-member analysis, etc. are making best out of the satellite data.
3. Availability of processed data set:
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AVHRR data with 1km resolution onboard NOAA satellite became the most
reliable source for global database (IGBP, 1992). Processed dataset at
global and regional level are available and well discussed by Skidmore
(Skidmore, 2002). A list of the data product is available from IJRS ( DeFries
and Belward, 2000)). Additional landuse/landcover studies are compiled in
special issue of IJRS vol. 21,No. 6&7, 2000, pp. 1083, 1089, 1093, 1115,
1121,1159,1313,1433.
Landuse/landcover studies assume more importance in the coastal area for
following reasons.
a. Limited availability of the land, as we have seen World's
coastline is approximately 4,40,000 km long, but more
than half the population stay in the coastal zone
(lindbhom, 2002).
b. Multiple use of land ranging from resource exploitation,
industry, habitation, recreational activities, pollution,
port development, fisheries, etc.
c. Increase in the world trade through sea route.
d. Exploitation and depletion of natural resources.
e. Developmental activities at the natural buffer zone (like
in mud-flat) make them vulnerable to natural hazards
and calamities and perturbing the natural coastal eco
systems.
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f. Limited studies has been carried out for coast
compared to other land based studies. Despite having
very important source for natural resources, shelter
place, basic route for international trade, coastal area
has attracted very few scientific researches. Thus,
reliable databases of coastal resources and landuse
land cover inventories, landuse/landcover changes,
processes which produce changes and effects of these
changes on environment are not widely known and
available. Because of lack of this information, framing
polices, having coastal zone management in integrated
manner is not possible.
An International Geosphere Biosphere Programme (IGBP) report (IGBP, 1992)
put the stress on requirement of land data for many IGBP projects. This data is to
be used as baseline data, monitoring and for numerical modelling, which
represent complex interaction in ecosystem of the earth (Hall et al 1995). To
prepare the reliable global level model, scientific data are required. Remote
sensing with various spatial, spectral and temporal resolutions and because of its
repetitive and synoptic nature facilitate this need. In IGBP projects, for global
scale modelling, most models require data covering large area. AVHRR data has
been used since last two decades for various land - atmosphere interaction
models, ecosystem processing models and hydrological models. G!obal
databases are mainly available for various disciplines like vegetation, hydrology
and soil, snow and ice, ocean, radiation and clouds for modelling. The
encouraging results from the AVHRR study in the field of landcover (Loveland et
al, 2000, Mucher et al, 2000, Hansen et al.2000) and the derivation of biophysical
parameter form landcover further facilitate improved large area sensors, such as
SPOT4, Vegetation and MODIS (Muchoney et al. 2000, Zhan et al. 2000) etc.
Skidmore described the exhaustive details of models and data set available at
global level (Skidmore, 2002).
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Thus, global models provide the vital inputs to understand the global processes
and environmental studies but they have their own limitations. The courser
spatial resolution and availability and accuracy of region specific aspatial data
made the global model fail to explain regional processes. For modelling regional
processes basic requirement is high-resolution remote sensing data, detailed in
situ data and constant monitoring to understand the interconnectivity with other
ecosystems. Thus, regional models can be compliment and supplement both to
the global models to improve the accuracy of model and better understanding of
the processes.
2.4 Modelling in coastal zone
Hsu and Silvester (1996) has defined Coastal Zone (as per the Carter, 1988), as
an area, resulting from the interaction between different physical, ecological and
cultural components. He has given the overview of different type of models
resulting from the beach processes. They have broadly classified them in four
topics of shoreline changes, beach profile variation, dune erosion and
topographic changes. They have not touched other coastal and ecological
issues, such as near shore current circulation, storm surge, coastal flooding,
waste disposal, etc.
According them, physical models have been used by coastal scientist for the
study of wave propagation, wave force on maritime structure, pollutant dispersion
and sediment transport. For problem involving sediment movement, location of
harbour entrance, and beach erosion and accretion, moveable bed scale model
have been utilized. Mathematical models mainly with deterministic approach, with
conservation of land momentum are applied. Models with the equations in the
form of Laplace or Navier-Stokes with continuity equations are set up for the
prediction of wave motions, density or transport of pollutants and near-shore
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current velocity. Beach profile study equations and Littoral drift equations are
discussed in detail.
Lakhan & Trenhaile (1989) cited the Miller for describing the characteristics of a
system. Based on that, he has identified coast as a system that "a set of
interacting units with relationship (both in term of structure and processes)
among them. The state of each unit is constrained by or dependent on other
state of other units." The coastal system can be seen as complex, dynamic,
large-scale system with an integrated arrangement of separate units or
components, which vary in morphological form, pattern and configuration. The
structures of a system deal with the spatial and temporal arrangement of its sub
systems and components, whereas processes concerned with change in matter,
energy and functioning of a system.
Lakhan & Trenhaile are defining the coastal system as a complex, de-compos
able, large-scale system. It is a composition of interacting component system and
associated sub-systems. The coast, with its component systems, will display vast
differences in morphology, physical states, and also various type of equilibrium.
In modelling the coastal system these characteristics of coast should be kept in
mind during demarcation and specifications of the boundary conditions.
According to them, it is very difficult to understand the complex, inter-dependent
and large-scale system using limited time studies. As it has interrelated
parameters, varying in time and space, the best way to study it using models and
sub-models. There are various kinds of models and different class of models as
described previously. These models can be classified in variety of manner
(Skidmore 2002, Fasol & Jorgl 1980, Fox 1985). Physical and mathematical
models are most successful in study of the natural system.
2.4.1 Physical models
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A model said to be physical when the representation is physical and tangible and
model elements are made up of materials and hardware. It is suitable in coastal
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studies and description can be found in text edited by Dalrymple (1985).
Svendsen (1985) describe the objectives for model to be considered as physical
model.
a) To seek quantitative insights in to a phenomenon not yet described.
b) To obtain measurements to verify the theoretical results.
Though, physical models are useful for understanding the interactions in coastal
systems, they do not describe hydrodynamics and sedimentary processes in
coastal system. In coastal system the processes, which are uncontrolled and
unpredictable in time and magnitude, cannot be explained fully by physical
models. So, results from physical models should be validated properly. (Rekhow
and Chapra, 1983).
2.4.2 Mathematical models
According to Hsu and Silvester (1996) the first mathematical model for coastal
sedimentation theory for shoreline change was given by Pelnard-Considere in
1956. This was basic concept has been used by many coastal engineers with
improvement to use the predicting the long-term evolution of a beach in the
vicinity of man made structures (Komar 1973, Rea and Komar 1975, Dean 1991).
Komar was first to give Drift equations (Komar, 1991 ).
The mathematical models are general and flexible in nature. It can be used for
very simple system to complex systems. In literature various types of
mathematical models have been described (Jacoby et al 1980, Blackwell, 1968).
Assumptions and facts are sharply stated and can be properly manipulated. They
provide formulation of hypothesis and provide guideline for the design of
experiments.
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deterministic or stochastic.
Static models are time independent. Dynamic models are time dependent and
phenomenon with temporal variations can be studied using dynamic models.
Models can be discrete or continuous representation of system depending on
how time is treated in the model. Analytical and numerical models can be
discriminated based on the technique used to solve the model. Analytical model
has limited values for coastal system modelling as many linear and non-linear
equations need to be solved. Analytical models can be successfully developed
for the system with linear characteristics. Numerical models can be solved both
linear and non-linear problems. To solve the equations of the model, numerical
methods involving computational procedures has to be used. Numerical
methods can be used successfully to study various aspects of the coastal system
as they allows both linear and non-linear type complex equations. In deterministic
models, output is determined totally in term of the input. These models are
therefore based on notion of exactly predictable relationship between
independent and dependent variables. These models contain no random variable
and use only expected value for all parameters and variables. They are not
suitable for exploring behavior of coastal systems, which are governed by several
random processes. Stochastic model have one or more random variables that it
takes on value in accordance with a probability distribution. The probability
distribution may either vary or remain constant with time (Franta, 1977).
Stochastic models deals with systems, which allow statistical laws for
formulations. It can be applied to study the coastal system where coastal
processes are having random components. Coastal systems have large number
of interacting components that can not be described individually and in detail.
Coastal systems those governed by external forcing conditions can not be
defined except in probabilistic terms.
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- -- .- J
for accuracy. Data collection is difficult in the coastal system. So, large numbers
of data are not available, Moreover, coastal systems are dynamic in nature. For
example, In littoral drift computations the wave conditions change hourly at any
location. So, for long-term study you have to take average only. Also, the mass .. movement of the suspended material also varies in very short time. The energy
varies with the depth.
2.4.3 Statistical and probabilistic models
Deterministic models, which characterise fixed input and output does not work for
coastal processes and landuse modelling. If actual development takes place in
mode other than predicted, it can lead to a wrong output. If we took probabilistic
approach, we can give more or various options to our model to give our model
more acceptability. In statistical methods, physical laws have been overlooked
sometime. So, we have to apply trial and error method before we reach to a
suitable goal.
2.4.4 Numerical models
Coastal processes are complex in nature and a number of parameters are acting
on it. So, when we select the differential equations for numerical models, success
depend upon the number of elements being considered.
2.4.5 Cellular Automata
The rules of cellular automata give another alternative form of conceptulisation.
Its widespread applications has until recently been constrained by the
construction of a computer designed specifically for their manipulations. It has
been claimed to be more appropriate to represent the fundamental laws of
Physics then the classical terms of differential calculus (Toffoli, 1984). Cellular
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automata models can be used both for process view model and entity view
model. Phipps (1992) suggested testing these cellular automata models
concurrently with well-known models.
Feoli and Giacomich (2003) has shown an application of a simulation model for
land cover changes based on cellular automata model for predicting landcover
changes due to tourism in Goa, suggested by llachiniski ( 2001) and combined
cellular automata with Markov model and MCE (Multicriteria evaluation) as
suggested by Eastman (2001 ).
2.5 Coastal studies in India
Noronha (2003) identified and addressing stakeholder concern and include
various groups to develop future scenario for tourism at Goa. According to her,
associating stakeholder in identifying future is reduced the interest conflict and
allow better management of coastal resources.
Sonak (2003) developed a framework, called DPSIR (Driver-Pressure-State
Impact-Response) framework. It connects driving forces to various coastal
ecosystems and resources trough pressure and pathways. He developed three
multi-domain (social, ecological, administrative) indicators to study the tourism
impact for monitor and managing sustainable use of coast. Indicators help to
capture the dynamics of ecosystem by communicating information about
conditions, change and trends over time. Mehra et al. (2003) developed a model
to delineate the linkage between socio-economic drivers and their impact on the
coastal ecosystems for tourism activities.
COSTED and NRSA has made an attempt in preparing meta-data directory for 4
coastal work in India. It was complied by Raghavswamy, (1999) who developed a
comprehensive database of thematic information prepared using remote sensing
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data and many socio-economic data available at discrete places. For preparing
models to understand process that governs landuse/landcover changes and the
impact of landuse/landcover changes on climate, locally and globally.
Raghavswamy has given case studies of landuse change dynamics. He has
given abstracts of the important work done and also given a list of similar studies
being carried out in the country on Indian coastal zone.
Sunder (2004) has explained the process of erosion of a coast as " a coast is
said to be eroding when the loss of material due to various reason exceeds the
material supplied to it." He has discussed various natural and man-made
problems causing coastal erosion. In natural processes he emphasised the steep
storm waves as a main reason and explained that the long shore currents are
mainly responsible for the transport of sediment along the shore and it is called
sediment transport. The wave crest reaching the shore are generally not parallel
to coast in many cases and making some oblique angle when reaches to the
coast. This effect cause two components of third velocity, of which, one along the
direction parallel to the coast is called long shore current. Any man-made
structure to prevent the coastal erosion or for other purpose, if not properly
designed, disturb the existing equilibrium of the coast and further aggravate the
situation of erosion. Thus, he discussed merits and demerits of various shore
protection measures like sea walls, groins, revetment and designing of jetties. He
also discussed artificial nourishment and offshore breakwaters with examples in
the Indian coastal region.
Chandrashekhar lyer (2004) has given the status of coastal erosion and
protection and discussed the issues state wise and for the country. In Gujarat, he
pointed out that the coastal erosion problem is experienced mainly in the district
of Valsad, Surat and Bharuch.
Jan Van de Graff (2001) explained the coastal erosion, possible causes of
coastal erosion and protection measures to prevent this erosion. He explained
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that how breakwater or jetties interrupt the longshore sediment transport and
accretion occurs on the up drift side whereas severe erosion on the lee ward
side. In this article he stressed the importance of strong coastal zone
management with legal backing. Also, he emphasized coastal zone manager has
to see judicious and long term integrated planning to avoid these type of
vulnerability of the coast.
Sa nil Kumar et al (2001) have measured nearshore processes like wave
breaking, longshore and onshore - offshore currents, littoral sediment transport,
accretion of beach sediments and found the annual gross transport ranging from
0.201 x 106 m3/year to 0.078 x 106 m3/year for their study area at the Karnataka
coast. They observed that general pattern of net sediment transport is toward the
south.
Dange and Ghose (2001) measured the longshore current (velocity along the
west coast of India, at Mangalore port, Mirya bay and Muldwarka. They have
measured longshore current based on method given by Shore Protection Manual
(Shore Protection Manual) and calculated velocity ranging 0.11 to 0.61 m/ sec.
2.6 Scope of the research
Thus as we see the literature, globally and locally, regarding landuse modelling it
comprises global models based on NOAA AVHRR data. These studies and other
works mainly carried out with objective of studying global climate and land use
changes in agriculture and forestry. As we have seen, to further improve the
accuracy of these models, local or regional studies with accurate and scientific
data with additional local component are needed. This can be stand-alone study
describing and addressing local ecological and processes related problems with
detail field data, spatial and non-spatial database, and, if required, it can be
complimented with existing global models. Ocean and land interaction plays an
important role in influencing the global climate, various man-made activities and
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other reasons cited above coastal zone assumes great importance. But, scientific
research in the coastal zone mainly confined with the studying the coastal
processes and impact of man-made structures on the coastal zone regarding the
erosion and depositional activities. Various anthropogenic activities influence the
coastal ecosystems and it assumes great importance to understand the effects of
these activities on the coastal land use and coastal processes for sustainable
development. Thus, present study is an attempt to study the effect of landuse/
landcover changes on the various coastal ecosystems and coastal processes
using remote sensing data. Non-spatial data have been integrated using GIS
and model has been developed which can be useful to the planner for developing
coastal zone in integrated sustainable manner.
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