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A platform for research: civil engineering, architecture and urbanism
Land Use Land Cover Change Modeling and Future Simulation in Mumbai City by Integrating Cellular Automata and Artificial Neural Network
The rapid urbanization driven by population growth and economic development has led to a drastic transformation of urban landscape in the cities of developing countries. As a result, large-scale changes in the urban land use land cover (LULC) pattern have been noted in recent decades. The present study is intended to study the LULC changes in the financial capital of India that is Mumbai city from 1991 to 2018 as well as forecast LULC changes for 2030. The Landsat datasets has been used for the LULC mapping of 1991, 2001, 2011 and 2018. For the LULC classification, unsupervised classification has been used employing K means clustering technique. The kappa coefficient has been applied for examining the accuracy of classified LULC maps. The LULC changes have been forecasted for 2030 by integrating artificial neural networks (ANN) and cellular automata (CA). The results of the study show large-scale changes in all LULC categories. The built-up area of the Mumbai city has increased from 28 to 57% of the total area of the city from 1991 to 2018. The vegetation, crop land and open land have witnessed considerable decline in the coverage area from 1991 to 2018. The results of LULC forecasting shows that the built-up will increase from 55 to 66% of the total area in Mumbai by 2030. At the same time, the area under open land and vegetation will reduce from 10.26 to 3.79% and 23.33 to 21.19%, respectively, by 2030. The finding of this study may be utilized in the urban planning of Mumbai city and its adjacent areas.
Land Use Land Cover Change Modeling and Future Simulation in Mumbai City by Integrating Cellular Automata and Artificial Neural Network
The rapid urbanization driven by population growth and economic development has led to a drastic transformation of urban landscape in the cities of developing countries. As a result, large-scale changes in the urban land use land cover (LULC) pattern have been noted in recent decades. The present study is intended to study the LULC changes in the financial capital of India that is Mumbai city from 1991 to 2018 as well as forecast LULC changes for 2030. The Landsat datasets has been used for the LULC mapping of 1991, 2001, 2011 and 2018. For the LULC classification, unsupervised classification has been used employing K means clustering technique. The kappa coefficient has been applied for examining the accuracy of classified LULC maps. The LULC changes have been forecasted for 2030 by integrating artificial neural networks (ANN) and cellular automata (CA). The results of the study show large-scale changes in all LULC categories. The built-up area of the Mumbai city has increased from 28 to 57% of the total area of the city from 1991 to 2018. The vegetation, crop land and open land have witnessed considerable decline in the coverage area from 1991 to 2018. The results of LULC forecasting shows that the built-up will increase from 55 to 66% of the total area in Mumbai by 2030. At the same time, the area under open land and vegetation will reduce from 10.26 to 3.79% and 23.33 to 21.19%, respectively, by 2030. The finding of this study may be utilized in the urban planning of Mumbai city and its adjacent areas.
Land Use Land Cover Change Modeling and Future Simulation in Mumbai City by Integrating Cellular Automata and Artificial Neural Network
GIScience & Geo-environmental Modelling
Rahman, Atiqur (editor) / Sen Roy, Shouraseni (editor) / Talukdar, Swapan (editor) / Shahfahad (editor) / Naikoo, Mohd Waseem (author) / Shahfahad (author) / Talukdar, Swapan (author) / Das, Tanmoy (author) / Ahmad, Mansoor (author) / Asif (author)
2023-03-04
17 pages
Article/Chapter (Book)
Electronic Resource
English
Effect of Land Use–Land Cover Change on Runoff Characteristics in Mumbai City
| Springer Verlag | 2019