Prediction of Urban Sprawl Using Remote Sensing, GIS and Multilayer Perceptron for the City Jaipur

被引:1
|
作者
Sisodia, Pushpendra Singh [1 ]
Tiwari, Vivekanand [1 ]
Dahiya, Anil Kumar [1 ]
机构
[1] Manipal Univ Jaipur, Jaipur Ajmer Express Highway,Near GVK Toll Plaza, Jaipur 303007, Rajasthan, India
关键词
Remote sensing; GIS; MLP; Urban sprawl;
D O I
10.1007/978-3-319-23036-8_35
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The population of India has rapidly increased from 68.33 million to 121.01 million from 1981 to 2011, respectively. It is estimated that by the year 2028 India will hold the largest population of the world. The prompt upsurge of the Indian population will force people to migrate from the rural area to the mega cities, to avail basic amenities. The enormous migration will increase the demand for more space to live in mega cities and will lead to a situation of unauthorized, unplanned, uncoordinated, and uncontrolled growth, and this condition called as urban sprawl. The key challenge for a planner is to achieve sustainable development and to predict the future urban sprawl in the city. Unfortunately, conventional techniques that predict urban sprawl are expensive and time consuming. In this paper, we have proposed a novel technique to predict the future urban sprawl. We have used an integrated approach of Remote Sensing, GIS, and Multilayer perceptron to predict the future urban sprawl for the city Jaipur up to 2021. We have compared our results with existing techniques like Linear Regression and Gaussian Process and found that the Multilayer perceptron gives better results than other existing techniques.
引用
收藏
页码:403 / 410
页数:8
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