Analysis of land use and land cover changes and their impact on temperature using landsat satellite imageries

Rubeena Vohra () and K. C. Tiwari
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Rubeena Vohra: Bharati Vidyapeeth’s College of Engineering (BVCOE)
K. C. Tiwari: Delhi Technological University

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 8, No 50, 8623-8650

Abstract: Abstract Urban growth and the changing scenario of Land Use and Land Cover (LULC) have been an increasing trend in both towns and cities. The higher rate of transformation from non-built up land to the impervious area becomes a warning symbol of Land surface temperature variations. In this study, an attempt has been made to determine the transition of natural land area and its impact on Land surface temperature (LST) in Vellore district, Tamil Nadu, India. According to the current statistics, the study area records the hottest climate crossing 40° mark in recent years. This is mainly due to the minimum rainfall, the ground level is 200 m just above the sea level, and the pollution caused by tanneries. Landsat imageries are collected for three different years 1994, 2002, and 2018 that map the LULC into agricultural, water bodies, built-up land, and barren land classes. The major purpose of this research is to (i) analyze changes of LULC in and around Vellore city, (ii) categorize the images into various classes like vegetative and non-vegetative land, (iii) Assessment of Spatio-temporal variations in LST and link with classes and urbanization growth using satellite images. The LULC impact on LST is analyzed with the widely used Getis–Ord statistics. The simulation result shows that the built-up area raises to 81%, vegetation land decline by about −65% for the years 1994–2018 respectively. It is observed that LST has attained the highest degree in the built-up class due to the unplanned LULC changes and the conversion of built-up areas. The overall accuracy is achieved at about 92, 89, and 91% for three different years respectively. Based on the obtained result, this can be adopted for the development of rural, and urban areas in the coming future.

Keywords: Land surface temperature; Land use; Land cover; Remote sensing; Normalized differential vegetation index (NDVI); Change detection (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02416-1

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