BYMR. SUYOG PRAMOD PATWARDHAN

MR. PRASAD VIVEK GANDHI

UNDER THE GUIDENCE OF

Mr. Vishal. R. Malave

ASSISTANT PROFESSORINPOST GRADUATE DEPARTMENT OF GEOINFORMATICSParavtibai Chowgule College Margao, Goa

Introduction

Aims and objective

Data base and Methodology

Study region

Limitations

Density analysis of ATM centers

Site suitability analysis

Findings

Conclusion

references

GIS plays vital role in decision making process Location convenience is very important in the service

sector. Time, cost of transport, convenient place, service

provided by consumers, suitability of sites etc. are crucial factors in service sector.

Suitability analysis used to give best sites for new ATM sites

Margao is commercial capital of Goa. Density of existing ATM centers and new sites for

proposing ATM mapped.

To assess the density of ATM centers in Margao city

To give site suitability for new ATM center with the help of GIS

Data based on primary and secondary form

Primary data collected from GPS points of all ATM centers, customer details, card holders of each banks

Secondary data based on satellite images, Toposheet, research articles and magazines etc

GPS data points imported to GIS software

Sample survey methods for each banks using questioner format. Questions such as Number of customer

Number of Account Holder

Number of Account Holder with ATM

Approximately percentage of Card holders of that area

Vector operations are as follows used in this work

Georeferenceand Digitizing ward boundry

Import all GPS data

Mosaic and Georeference

of satellite image

Clip image with village boundery

Digitization of Road and Settlement

Digitization of land use

and land cover

Prepare Land use and land

cover Map

Prepare Exisiting ATM centers map

Final map of ATM, Roads, Settlement

and Land use and Cover

Raster operation for site suitability analysis are as follows

Extract by Mask of satellite Image

Multple Ring Buffer

of ATM

Kernel Density

Estimation

Euclidean distance of

Road

Reclassify of All raster Layer

Weighted Overlay

analysis of Slope, ATM,

Road and Landuse

weighted Overlay

Index

Selecting optimum New sites For ATM

Final output

Map

Introduction to Margao

Commercial Capital of goa

Covering nearly 24 sq.km area

More service sector

Nearness to tourist places, better transport and communication facilities creates scope for banking activities

Nearly 25-30 banks having 52 ATM centers

Market area having more density of ATM centers

Difficult to get customer data from banks

Very few works done in India

2011 census data not yet published thus used 2001 census data for demographic factors

Each banks have different policies to construct the New ATM

Density of each ATM points calculate

Kernel density estimation used

calculates the density of features in a neighborhood around those features.

To estimate density categories given such as Very High Density High Density Medium Density Low Density Very Low Density

Distance from first class to second class is nearly 300-400Mt

Market area and KTC area shows highest density and power house , Dowerlim, Fatorda shows the lowest density

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30000

Number of Customer

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f A

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Percentage of customer using ATM

Site suitability analysis used to give new sites for the ATM centers

For site suitability following methods are used Multiple ring buffer Reclassification Slope Distance Density

Weighted overlay Conditional operators using CON Optimal site selection from settlement and road buffer

The purpose of reclassification is to create new raster layer by changing the attributes value of the cell of the input layer.

This usually takes one of the following forms that used either logical or arithmetic operators

Ascending the values to classes or range of old value with the purpose of reducing the number of the classes in the original input layer or to group value into categories in a new classification.

Weighted Overlay is a technique for applying a common measurement scale of values to diverse and dissimilar inputs to create an integrated analysis.

Geographic problems often require the analysis of many different factors.

For instance, choosing the site for a new housing development means assessing such things as land cost, proximity to existing services, slope, and flood frequency.

Within a single raster layer, you must usually prioritize values.

For example, a value of 1 represents slopes of 0 to 5 degrees, a value of 2 represents slopes of 5 to 10 degrees, and a value of 3 represents slopes of 10 to 15 degrees.

If slope is a criteria in finding a new site, for example, and your evaluation scale is from 1 to 9 by 1, you might give a scale value of 9 to the input value of 1 (the most suitable areas with least steep slopes), a scale value of 6 to the input value of 2 (the second most suitable slopes), and a scale value of 3 to the input value of 3 (the least suitable, steepest slopes).

If it was decided that slopes greater than 15 degrees would not be considered, all input values greater than 3 would be assigned a scale value of restricted to exclude them.

Site selection based on following criteria Influence of Land use and Land cover such as Barren

land, Settlement, Open Land etc

Distance from the Road ( 30-50 Mt)

Density pattern of existing ATM

Settlement

Number of bank customer and Number of card holders

Buffering from settlement and intersecting Road

With the help of site suitability analysis we can give best suitable sites for recreational sites

SBI, HDFC, ICICI, kotak mahindra, union bank having highest number of ATM

BOI having more customer nearly 20000-30000 in Fatorda, Aquem area but no ATM centers

BOM and IDBI banks also having low frequency of ATM

Doverlim and Power House ,ravanpond, Pajifond area having very low frequency of ATM centers though this area having highest population

Location convenience is an important factor when customers select a financial institution.

Doverlim, PowerHouse, Sonsodo, Gogol, Fatordaarea have potential for constructing the new sites for the ATM centers

BOI, BOM, IDBI banks have great potential to settled the New ATM centers in Gogol, Fatorda, Powerhouse and Dowerlim area because of highest number of customer and population

Books- Geographic Information Systems and Science by Longely Paul A, Goodchild Mike

Websites- www.anastasia-fp6.org/.../BNSC%20presentations%20-%20C%20Swiftbr... https://www.tenders.gov.au/?category...closed...ATM. ec.europa.eu/transport/.../2012_10_23_atm_master_plan_ed2oct2012.pdf www.esri.com/industries/banking www.instantsiteintelligence.com/.../WhitePaper-MarketForte-GISinBanki www.cjrs-rcsr.org/archives/24-3/macdonald.pdf www.pbinsight.com/files/resource-library/resource.../yankee-group.pdf www.saudigis.org/.../SaudiGISArchive/2ndGIS/.../15_E_BilalFarhan_US... financialservices.gov.in/GIS/Usermanual.pdf www.gisdevelopment.net/application/business/ma03075pf.htm

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