Retrieval of the land surface temperature using thermal remote sensing and its relationship with hydrometeorological variables, Sabarmati Basin, Gujarat, India

Abstract

Climatic variation and land-atmosphere interaction affect the natural resources, particularly in the arid/ semi-arid regions. The present research work has been carried out in the Sabarmati basin to quantify Land surface temperature (LST), factors and their impact on hydrometeorology and biophysical parameters. LST and indices were estimated using Landsat 5, 7 and 8 images on a decadal basis using thermal and spectral bands. The monthly TRMM (Tropical Rainfall Measuring Mission) data was used to analyse the rainfall pattern in the study area. Different indices such as normalised difference vegetation index (NDVI), normalised difference moisture index (NDMI), and normalised difference water index (MNDWI) were calculated. Results suggests that from 1990 to 2020, the maximum LST increased by 4.36°C and the minimum LST increased by 5.90°C. In 2020, high LST zones (areas above the mean LST) increased by 8085.51 sq. km compared to 1990. The study finds a negative correlation coefficient of LST with Vegetation Index (NDVI) (r = −0.41), MNDWI (r = −0.54), and Moisture Index (NDMI) (r = −0.69), whereas a moderate positive correlation exists with elevation (r = 0.33). The surface water body area increased significantly in 2020 compared to 1990 due to the formation of new reservoirs and water channels, as well as increased rainfall during the 2019 monsoon season in the river basin. This study provides valuable insights into climate change impacts, aiding urban planning. It also emphasizes the importance of preserving green spaces and water bodies and expanding vegetation in barren lands to combat LST intensification.