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Measuring and Monitoring Urban Sprawl of Jaipur City using Remote Sensing and GIS

Measuring and Monitoring Urban Sprawl of Jaipur City using Remote Sensing and GIS

Pushpendra Singh Sisodia, Vivekanand Tiwari, Anil Kumar Dahiya
Copyright: © 2015 |Volume: 6 |Issue: 2 |Pages: 20
ISSN: 1941-868X|EISSN: 1941-8698|EISBN13: 9781466676909|DOI: 10.4018/ijissc.2015040104
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MLA

Sisodia, Pushpendra Singh, et al. "Measuring and Monitoring Urban Sprawl of Jaipur City using Remote Sensing and GIS." IJISSC vol.6, no.2 2015: pp.46-65. http://doi.org/10.4018/ijissc.2015040104

APA

Sisodia, P. S., Tiwari, V., & Dahiya, A. K. (2015). Measuring and Monitoring Urban Sprawl of Jaipur City using Remote Sensing and GIS. International Journal of Information Systems and Social Change (IJISSC), 6(2), 46-65. http://doi.org/10.4018/ijissc.2015040104

Chicago

Sisodia, Pushpendra Singh, Vivekanand Tiwari, and Anil Kumar Dahiya. "Measuring and Monitoring Urban Sprawl of Jaipur City using Remote Sensing and GIS," International Journal of Information Systems and Social Change (IJISSC) 6, no.2: 46-65. http://doi.org/10.4018/ijissc.2015040104

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Abstract

The world's population increased drastically and forced people to migrate from rural area to major cities in search of basic amenities. The majority of the World's population are already living in the major cities and it is continuously increasing. The increase in population forced the major cities to expand. Expansion of cities acclaimed more unplanned settlement that leads unplanned growth. This is a global phenomenon that has a direct impact on natural resources. It is the biggest challenge for urban planners to achieve sustainable development. Developing countries like India, where the population is increasing at an alarming pace, require more attention towards this problem. In this study, an attempt has been made to measure and monitor urban sprawl in Jaipur (Capital, State of Rajasthan, India). Built-up area with corresponding population has been analysed over a period of 41 years (1972-2013). Remotely sensed images of 1972-2013 (MSS, TM and ETM+) have been classified using Supervised Maximum Likelihood Classification (MLC) for digital image processing. Shannon's entropy has been used to quantify the degree of urban sprawl, and eight landscape metrics have also been used to quantify urban sprawl and its pattern.

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