Spatiotemporal Changes of Forest Cover and Land Surface Temperature Using Geo-Spatial Techniques in Talra Wildlife Sanctuary, Shimla, North-Western Himalaya

Abstract

Abstract Geophysical parameter such as Land Surface Temperature (LST) plays an important role in studies related to hydrological processes, climate change, Forest Cover Change (FCC) detections, soil moisture estimations, vegetation water stress, etc. Thermal Infrared Sensors (TIRS) for several FCC categories are measured heat signatures. Deforestation, forest fire, grazing, and anthropogenic activities were witnessed in Protected Areas (PAs) forests. For the Single Channel (SC) algorithm and the Split Window (SW) algorithm. The Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper Plus (ETM+), and Landsat-8 Operational Land Imager (OLI) several time-series satellite data have been employed. The overall analysis of FCC showed a significant reduction (-5.59%) in dense forest areas. Despite an overall decrease in pasture and non-forest areas of about 2.99 Km2 between 2000 and 2021, there was a significant increase in these areas between 2000 and 2021 of 7.25% and 0.22%, respectively. The relative comparison of the LST on various FCC categories obtained from SC and SW algorithms revealed a ± 1 Kelvin (K) average difference in the years 2000, 2011, and 2021. The LST retrieved using the SC algorithm shows a strong negative correlation coefficient with Normalized Difference Vegetation Index (NDVI) of R2 = 0.791 in the year 2000 with ⍴ a value of -0.889, 0.750 with ⍴ the value of -0.866 in the year 2011, respectively, whereas the LST obtained using the SW algorithm exhibited a perfect negative Correlation Coefficient (R2 = 0.646 with a ⍴ value of -0.804) with the NDVI for the year 2021.