Monitoring forest cover changes and its impact on land surface temperature using geospatial technique in Talra Wildlife Sanctuary, Shimla, India

Pawan Kumar Thakur (), Sher Singh Samant (), Raj Kumar Verma (), Atul Saini () and Monika Chauhan ()
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Pawan Kumar Thakur: ICFRE-Himalayan Forest Research Institute
Sher Singh Samant: ICFRE-Himalayan Forest Research Institute
Raj Kumar Verma: ICFRE-Himalayan Forest Research Institute
Atul Saini: Delhi School of Climate Change & Sustainability, Institution of Eminence, University of Delhi
Monika Chauhan: ICFRE-Himalayan Forest Research Institute

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2025, vol. 27, issue 5, No 51, 11087-11116

Abstract: Abstract Forest cover change plays a crucial role in impacting the ecological environment, while land surface temperature (LST) serves as a significant indicator for assessing the effects on Earth's climate system. This research aims to identify spatiotemporal transformations in forest cover and retrieve the LST of Talra Wildlife Sanctuary (TWLS) in Shimla, India, using thermal infrared sensors (TIRS). The retrieval of LST involved the implementation of the Single-Channel (SC) algorithm for Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM), as well as the Split-Window (SW) algorithm for Landsat Operational Land Imager (OLI) data from 2000 to 2021. Geospatial techniques were employed to extract spatiotemporal changes in forest cover, normalized difference vegetation index (NDVI), and land surface emissivity (LSE). The analysis of forest cover change (FCC) revealed a significant decline (− 5.59%) in dense forest areas within the sanctuary. Over the period from 2000 to 2021, there was a decrease in forest cover, while pasture and non-forest areas exhibited notable increases of 7.25% and 0.22%, respectively. Comparative examination of LST across different forest cover types indicated an average difference of ± 1 Kelvin (K) between 2000 and 2021. The retrieval of LST using SC and SW algorithms demonstrated a negative correlation coefficient with NDVI, resulting in R2 values of 0.79 in 2000, 0.75 in 2011, and 0.65 in 2021. Through the integration of thermal and field data, this study identified long-term changes in LST associated with forest cover modifications within the sanctuary. Urgent implementation of new policies is imperative to prevent further decline in forest cover in the near future. The findings of this study provide valuable insights for forest conservation efforts in TWLS.

Keywords: Land surface temperature; Normalized difference vegetation index; Land surface emissivity; Split window; Correlation coefficient (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10668-023-04347-x

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