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Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model

1
Centre of Studies in Resources Engineering, IIT Bombay, Mumbai 400076, India
2
Department of Development Technology, Graduate School for International Development and Cooperation (IDEC), Hiroshima University, Hiroshima 739-8529, Japan
3
Transdisciplinary Science and Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima 739-8529, Japan
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(2), 471; https://doi.org/10.3390/su13020471
Received: 10 December 2020 / Revised: 31 December 2020 / Accepted: 31 December 2020 / Published: 6 January 2021
(This article belongs to the Section Sustainable Urban and Rural Development)
In this study, prediction of the future land use land cover (LULC) changes over Mumbai and its surrounding region, India, was conducted to have reference information in urban development. To obtain the historical dynamics of the LULC, a supervised classification algorithm was applied to the Landsat images of 1992, 2002, and 2011. Based on spatial drivers and LULC of 1992 and 2002, the multiple perceptron neural network (MLPNN)-based Markov chain model (MCM) was applied to simulate the LULC in 2011, which was further validated using kappa statistics. Thereafter, by using 2002 and 2011 LULC, MLPNN-MCM was applied to predict the LULC in 2050. This study predicted the prompt urban growth over the suburban regions of Mumbai, which shows, by 2050, the Urban class will occupy 46.87% (1328.77 km2) of the entire study area. As compared to the LULC in 2011, the Urban and Forest areas in 2050 will increase by 14.31% and 2.05%, respectively, while the area under the Agriculture/Sparsely Vegetated and Barren land will decline by 16.87%. The class of water and the coastal feature will experience minute fluctuations (<1%) in the future. The predicted LULC for 2050 can be used as a thematic map in various climatic, environmental, and urban planning models to achieve the aims of sustainable development over the region. View Full-Text
Keywords: LULC; Markov chain model; multiple perceptron neural network; urban growth; urbanization LULC; Markov chain model; multiple perceptron neural network; urban growth; urbanization
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MDPI and ACS Style

Vinayak, B.; Lee, H.S.; Gedem, S. Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model. Sustainability 2021, 13, 471. https://doi.org/10.3390/su13020471

AMA Style

Vinayak B, Lee HS, Gedem S. Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model. Sustainability. 2021; 13(2):471. https://doi.org/10.3390/su13020471

Chicago/Turabian Style

Vinayak, Bhanage, Han S. Lee, and Shirishkumar Gedem. 2021. "Prediction of Land Use and Land Cover Changes in Mumbai City, India, Using Remote Sensing Data and a Multilayer Perceptron Neural Network-Based Markov Chain Model" Sustainability 13, no. 2: 471. https://doi.org/10.3390/su13020471

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