Assessment of Land Surface Temperature Dynamics of Chamoli District Using Landsat Data: Implications for Vegetation Cover Monitoring

Abstract

Thermal infrared remote sensing data is vital for analyzing and mapping Land Surface Temperature (LST), allowing for the capture of apparent surface temperature through radiant energy. The use of ArcGIS software simplifies the calculation of LST. Landsat-8, and Thermal Infrared Sensor (TIRS) data with 100 m resolution have been used for the calculation of LST of the study area. Landsat 5-8 data has been taken to understand the seasonal comparison and yearly changes in LST. OLI Band 4, and  5 have been used for the calculation of the Normalized Difference Vegetation Index (NDVI). The ultimate result shows that the surface temperature was low in the densely vegetated areas, while it was high for the barren land. Satellite data from 2000 to 2025 for winter, summer, and monsoon was compared to assess the changes in the surface emissivity. An integrated approach has been taken for the mapping and monitoring of forest resources of the study area with the help of LST data and other indices, i.e., NDVI and NDWI. This integrated approach enables the identification of areas susceptible to stressors like drought, pest infestation, and land degradation, facilitating proactive management interventions.