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Geospatial Analysis of Urban Sprawl Patterns in Amritsar City, Punjab, India

Minakshi, Shivani Singh, Brijendra Pateriya

International Journal of Applied Information Systems
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Minakshi, Shivani Singh, Brijendra Pateriya
10.5120/ijais2017451636
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  1. Minakshi, Shivani Singh and Brijendra Pateriya. Geospatial Analysis of Urban Sprawl Patterns in Amritsar City, Punjab, India. International Journal of Applied Information Systems 11(8):8-14, January 2017. URL, DOI BibTeX

    @article{10.5120/ijais2017451636,
    	author = "Minakshi and Shivani Singh and Brijendra Pateriya",
    	title = "Geospatial Analysis of Urban Sprawl Patterns in Amritsar City, Punjab, India",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "January 2017",
    	volume = 11,
    	number = 8,
    	month = "Jan",
    	year = 2017,
    	issn = "2249-0868",
    	pages = "8-14",
    	numpages = 7,
    	url = "http://www.ijais.org/archives/volume11/number8/957-2017451636",
    	doi = "10.5120/ijais2017451636",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

Amritsar is the largest and most important city in northern Punjab. Amritsar serves as a major commercial, cultural, and transportation hub with Golden Temple & Raja Sansi international airport. It lies about 25 km east of the border with Pakistan and gateway for travelers coming to India on the overland route from central Asia. The present study attempts to understand, detect and quantify the spatial pattern of Amritsar urban sprawl using Shannon’s entropy and multi-temporal satellite images acquired for the period from 1972 to 2015. Shannon’s entropy has been used to model the city’s urban sprawl, trend and spatial change. The entropy values for the different grids were modeled and the interpolation function in ArcGIS is used to obtain an entropy surface for each acquired temporal image. The entropy surface index indicates the spatial pattern of the urban sprawl and facilitates to visual assess the entropy phenomenon in all the grids. The value of Shannon’s entropy index increased from (0.40) in year 1972 to (0.97) in year 2015, indicating more dispersed urban growth, an indication of urban sprawl. Results obtained from entropy indices help in understanding the sprawl patterns and dynamics among different grids and provide a visual comparison which facilitates the decision makers and city planners for measuring the urban sprawl required for mega cities.

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Keywords

Shannon’s Entropy, Urban Growth, Sprawl Patterns, Remote Sensing & GIS