Spatiotemporal mapping of Land Use/Land Cover dynamics using Remote Sensing and GIS approach: a case study of Prayagraj City, India (1988–2018)

Md. Omar Sarif () and Rajan Dev Gupta ()
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Md. Omar Sarif: Motilal Nehru National Institute of Technology Allahabad
Rajan Dev Gupta: Motilal Nehru National Institute of Technology Allahabad

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2022, vol. 24, issue 1, No 36, 888-920

Abstract: Abstract Prayagraj City is one the biggest cities in the State of Uttar Pradesh which has been selected as Smart City by Ministry of Housing and Urban Affairs, Government of India, in 2015. This city has rapidly evolved in the last three decades due to the urbanization process. This study has used multispectral imageries of Landsat Thematic Mapper and Operational Land Imager/Thermal Infrared Sensor of four different time points at the interval of ~ 10 years, i.e., 1988, 1997, 2008, and 2018. These images have been preprocessed and then classified through supervised classification using Maximum Likelihood Classifier in ERDAS IMAGINE version 2014. The overall accuracy achieved is more than 88% in all the four time points. The periodical change results have revealed that all land use/land cover (LU/LC) classes has altered in all periods, i.e., 1988–1997, 1997–2008, 2008–2018, and 1988–2018 with remarkable trends, patterns, and magnitudes. The growth of Built-up land is a major concern. The results of the change matrix (1988–2018) have indicated that the most expanded class was built-up land which has evolved into 64.52% at the cost of Agriculture land by 24.41%, Forest land by 10.56%, and Barren land by 6.01%. The above results of LU/LC dynamics can help in making planning and policy development for restoring and enhancing the carrying capacity of land and sustainability of the environment in a city landscape.

Keywords: Supervised classification; MLC; Periodical change; Change matrix; LU/LC dynamics; Carrying capacity; City landscape (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10668-021-01475-0

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