Lalu Saheb K M.E- Infrastructure Senior Professor Engineering & … · 2016-04-19 · BITS Pilani,...

BITS Pilani Pilani Campus

Facility Location - Allocation using

ArcGIS:

A case study of Amaravati City,

Andhra Pradesh

Dr. Rajiv Gupta Senior Professor

Lalu Saheb K M.E- Infrastructure Engineering & Management

BITS Pilani, Pilani Campus

• Quantification of given facilities by location-allocation analysis

and OD cost matrix analysis in ArcGIS.

• By using OD cost matrix analysis, calculated accessibility

index for each origin and destination points.

• As per the accessibility index values, replaced the locations of

facilities in prioritizing order taken from questionnaires.

Aim and scope:


Introduction:

• Andhra Pradesh is building a new Capital City named

Amaravati.

• The Andhra Pradesh State Government has assigned a 7,325

km2 area for Capital Region.

• Amaravati is to be built in 391 square kilometres in Guntur

district, on the bank of the Krishna River.

• It will be 12 km north-west of vijayawada city and 20 km north-

east of Guntur city. It would comprise 33 villages in three

mandalas.

• The master plan is given by Singapore and The Japanese

companies are ready to associate in construction.


Study Area:

Andhra capital city (Amaravati)


Study Area:

Source: CRDA, Government of Andhra Pradesh


Specifications in the capital region:

Area 391 km2

Longitude 16.5662

Latitude 80.6160

Altitude 36m above the M.S.L

Annual rainfall 51.66 mm /year average

Monsoon July-September

Temperature Winter min(Nov-Jan)-110-190 Summer max(April-July)-200-300

Prevalent winds From north west to south east in Winter and

reverse in Summer

Total villages 33

Inhabited 33

Un-inhabited 0

Panchayats 27

Population 108746

Density population/ sq.km 891.5

Birth rate(1000 persons) 19.03

Death rate(1000 persons) 10.03

Infant mortality(1000 persons) 41.43

Sex ratio(female per 1000 males) 903

Decennial population growth literacy rate 39.04

Literacy rate 59.32


Agencies responsible for the plan preparation:

Land use planning and zoning

• Land use planning and

zoning (Under respective

T&CP Acts)

• Municipalities

• Development Authorities

• Town & country planning

agency

Transportation planning

• Multiple agencies (Urban

roads, public transport,

railways, metro, traffic

management)

• National, State level &

Local level


Incremental Phase I Phase 2 Phase 3

Employment (10 Years) (10 - 20 years) (20-35 years)

Government 46,096 4,432 11,524

IT / ITeS 51,062 58,422 1,56,542

Corporate Complex 24,692 31,727 1,06,931

Financial Hub 41,153 52,879 1,78,218

Start-up/Innovation hub 6,273 18,818 2,439

Education Hub 5,934 7,625 25,698

Industrial sectors 18,001 30,082 82,152

Indirect Employment 1,58,409 1,75,550 4,84,242

Total 3,51,620 3,79,534 10,47,747

Forecasted Population :

Table : Incremental employment

Population

in Million

Year 0 Phase 1

(10 years)

Phase 2

(10 -20 years)

Phase 3

(20-25 years)

Incremental Population 0.38 0.86 0.90 2.34

Total Population

(cumulative)

0.38 1.24 2.15 4.49

Cumulative population:

Source: CRDA, Government of Andhra Pradesh

Total projected population is 4.5 million and having population density of 10664 per sqkm,

Considered Employment vs population ratio 44.77.


This study integrates GIS and geospatial analytical methods

based on location allocation & OD cost matrix models with

the following objectives:

• To evaluate and assess the locations of facilities given in

approved master plan of new capital city.

• To find which part of the city might be seriously uncovered

and inaccessible from facilities within the standard

response distance.

• To find out if new facilities should be established in

strategic locations to under coverage or reallocation.

• Find optimal locations and reallocate facilities.

Methodology:


Framework for Optimal Facility Allocation:

Data Collection

Data Analysis

Defining

zones/ Locations

Quantification of

Facilities

Quantification Survey -1 Quantification Survey -2

Optimal Locations

and Re-allocation

of facilities

Origin –

Destination Cost

Matrix Analysis

Accessibility

Index

Re-allocation of

facilities

Network Analysis


Questioner results:

S.no. Facilities Ranking Preferred Distance (KM)

1 Hospitals 1 3

2 Schools 2 3

3 Colleges 4 5

4 Civic facilities 3 4

5 Fire station 5 4

6 Sports 10 2

7 Industries 8 12

8 Commercial 6 4

9 Safety management 7 4.5

10 Parks / Recreation 9 2


Framework for OD cost matrix analysis:

OD cost matrix layer created

Residential zones (shape files)

were loaded into the origin

point class

Priority

Ranking in

Questioner-1

Facilities (shape files) were

loaded into the destination

class

Run OD cost matrix analysis to get travel impedance measurement via

spatial analysis

Export Attribute tables to Excel sheets

OD matrices

Calculation of accessibility

index values

Graphical representation of

accessibility values

Reallocate the facilities as per

the ranking in questioner - 1


Road network:


Consider :

Origins – Residential high (127 locations)

Destinations – Medical centres (126 locations)

Network lines – 127x126 = 16002 lines.

New OD cost matrix analysis:


Final O-D network:


• Here, I have exported the attribute table values I.e. origin

– destination distances for residential high to Medical

centres.

• In such a way that, exported 3 tables for below O-D’s:

• - Residential medium to medical centres

• - Residential low to medical centres

• - Residential mix to medical centres.

• Same procedure done for other facilities and exported

attribute tables in excel sheets.

• Finally got 32 maps & tables (4 Origins x 8 Destinations).

Conti…


Final O-D networks:


Definition : Accessibility refers to the ability to reach desired

goods, services, activities and destinations Or measure of

the relative access of an area or zone to population,

employment, opportunities, and community services.

Accessibility Index:

Individuals, based

at home

Desired activities

at destinations

Link between

Individual & activity


• Considered preferred distance value shown in table.

• Distance Ratio = Preferred distance/Existing distance.

• Accessibility Index = Distance Ratio/Max. distance ratio

value.

• Next insert pivot table. In this add origin and accessibility

index values.

• Then we can get final accessibility index values for each

origin point i.e. sum of each origin point to all destination

point distances.

• Same way find out for all other facilities.

Calculations:


Calculations : (Eg.-Residential High to Hospitals):

ObjectI

D Name

Origin

ID

Destinat

io

Destinat

_1

Total_Len

g Act-dist Ratio Accessi

Row

Labels

Sum of

Accessi

1 Location 1 - Location 119 1 119 1 17.58110 3000 170.63782 0.106634 1600.219 1 0.266600301

2 Location 1 - Location 120 1 120 2 23.85659 3000 125.751426 0.078584 2 0.437608189




















• Take all the pivot tables in a single sheet and calculate

overall sum of all other facilities i.e. each origin point to

all the destination points of all the types of facilities.

• Continue the same for residential medium , residential

low & residential mix locations.

• We got the final accessibility index values for each

location.

Conti…


Residential - High:


Residential – Medium:


Residential – Low:


• Calculated accessibility index values to all the destination

points followed the same procedure.

• But here considered average preferred distance by

weighted average method.

Average preferred distance= 186/45 = 4.3 km

Conti…


Conti..

• Then take all the pivot tables in a single excel file. And

sort out in a single column in ascending order of

accessibility values.

• Next replace the facility locations as per the priority

ranking wise taken in questionnaire – l


• In this case, all residential locations (origin) taken in a

single shape file (append) and all facility (Destination)

location shape files merged in a separate append shape

file.

• Then loaded these shape files to the OD cost matrix origin

& destination classes.

• Continue the same procedure described above and

consider average preferred distance by weighted average

method.

• Here 452 habitants loaded into the origin class and facility

append file having 652 locations loaded into the facility

point class.

Result - II:


Residential - append:


Reallocation of facilities:

Row Labels Sum of Accessi New id Relocate Row Labels Sum of Accessi New id Relocate Row Labels

Sum of Accessi New id

School-115 83035.31331 0 Hospital Medical-54 6695.404 21 Hospital School-133 5358 43

School-44 64871.33998 1 Hospital Recreation-4 6486.528 22 Hospital Civ-52 5344 44

School-54 39450.78842 2 Hospital Comme-88 6334.798 23 Hospital School-31 5274 45

Comme-69 35957.02627 3 Hospital School-13 6213.658 24 Hospital Civ-53 5270 46

Medical-124 19150.24393 4 Hospital School-131 6105.874 25 Hospital School-145 5236 47

School-116 14522.77526 5 Hospital School-118 5954.447 26 Hospital Civ -46 5129 48

School-126 11802.91009 6 Hospital School-42 5950.746 27 Hospital Comme-29 5126 49


Sports-30 10570.33163 8 Hospital Comme-79 5848.667 29 Hospital School-43 4978 51

School-57 10374.80088 9 Hospital Civ -54 5823.921 30 Hospital School-142 4945 52

School-104 9974.52543 10 Hospital Medical-122 5807.438 31 Hospital School-125 4909 53

School-9 9162.615504 11 Hospital Civ -47 5794.932 32 Hospital School-6 4822 54

School-86 9106.234126 12 Hospital School-55 5675.643 33 Hospital School-36 4818 55

Medical-56 9089.22659 13 Hospital Civ-39 5652.144 34 Hospital Civ-3 4767 56

School-120 8454.751443 14 Hospital School-78 5641.86 35 Hospital Comme-9 4747 57


School-155 7996.716942 16 Hospital Colleges-1 5554.045 37 Hospital Medical-123 4653 59

School-81 7566.523186 17 Hospital Medical-41 5477.904 38 Hospital Comme-2 4646 60

School-79 7289.894539 18 Hospital Medical-42 5454.202 39 Hospital Civ -50 4631 61

Medical-36 6768.587767 19 Hospital School-64 5404.398 40 Hospital Colleges-19 4609 62

School-35 6754.243245 20 Hospital Colleges-3 5391.01 41 Hospital Comme-18 4597 63

Medical-54 6695.404038 21 Hospital School-15 5385.158 42 Hospital School-83 4575 64


• In this research study, accessibility is the main object but

population density not considered.

• If we consider population densities along with

accessibility index value methodology, then we can get

better accurate results.

• As per these values, we can find the habitants which are

not serving by the particular facility or too far from facility

then subsequently increase the number of facility

locations or reallocate the facilities to bridge the gaps.

Recommendations:


• In this study, we are suggesting a better facility allocation.

• Considered quantification for all the facilities and habitants

at a time rather than considering single facility, because

facilities to be reallocated in a prioritizing order.

• Bus stops, WTP, water distribution plants, electrical power

plants locations not considered because special surveys

to be done for those locations9529318296.

Conclusion:

BITS Pilani Pilani Campus

THANK YOU

Lalu Saheb K M.E- Infrastructure Senior Professor Engineering & … · 2016-04-19 · BITS Pilani,...

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