4.7 Article

Monitoring of land use land cover dynamics and prediction of urban growth using Land Change Modeler in Delhi and its environs, India

期刊

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
卷 29, 期 47, 页码 71534-71554

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s11356-022-20900-z

关键词

Land use land cover; Change detection; Urban growth; Predictive modelling; Land Change Modeler; Cellular automata; Markov chain

资金

  1. Indira Gandhi National Open University

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This study examines the land use and land cover changes in Delhi and its surroundings using satellite images. The results show an increase in urban and open areas, a decrease in crop land, and an increase in forest area. Future urban growth was also predicted, indicating further expansion. These findings have important implications for decision-makers and planners in formulating sustainable policies and plans.
In the recent decades, cities have been expanding at a great pace which changes the landscape rapidly as a result of inflow of people from rural areas and economic progression. Therefore, understanding spatiotemporal dynamics of human induced land use land cover changes has become an important issue to deal with the challenges for making sustainable cities. This study aims to determine the rate of landscape transformations along with its causes and consequences as well as predicting urban growth pattern in Delhi and its environs. Landsat satellite images of 1989, 2000, 2010 and 2020 were used to determine the changes in land use land cover using supervised maximum likelihood classification. Subsequently, Land Change Modeler (LCM) module of TerrSet software was used to generate future urban growth for the year 2030 based on 2010 and 2020 dataset. Validation was carried out by overlaying the actual and simulated 2020 maps. The change detection results showed that urban and open areas increased by 13.44% and 2.40%, respectively, with a substantial decrease in crop land (10.88%) from 1989 to 2020 and forest area increased by 3.48% in 2020 due to restoration programmes Furthermore, the simulated output of 2030 predicted an increase of 24.30% in urban area and kappa coefficient 0.96. Thus, knowledge of the present and predicted changes will help decision-makers and planners during the process of formulating new sustainable policies, master plans and economic strategies for rapidly growing cities with urban blue-green infrastructures.

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