The ongoing transformation of natural landscapes into human-dominated environments has resulted in substantial changes in Land Use and Land Cover (LULC) patterns across the globe. The primary drivers of LULC change are the transformation of natural landscape into artificial landscape which includes rapid urbanization, agricultural intensification, deforestation, and infrastructural development. These activities significantly alter the Earth's surface properties, leading to changes in albedo, evapotranspiration rates, and the heat storage capacity of the land, all of which influence local and regional climate patterns and contribute to rising temperatures. The current issue of Sahyadri e-news (Issue XCII) reports the interplay of land cover changes with land surface temperature (LST) patterns across all agroclimatic zones in India. LULC analysis spanning 2001 to 2022, using MODIS data, reveals agriculture as the dominant land use class in ten of the fifteen agroclimatic zones, while built-up areas are rapidly expanding in select zones. Agroclimatic zone classification employs a Machine Learning non-parametric supervised classification algorithm, Random Forest, recognized for its effectiveness in heterogeneous landscapes. The study assesses the LST response to changing LULC dynamics within Indian agroclimatic zones, finding an overall increase in LST from 2001 to 2022. The relationship between land cover, as indicated by Normalized Difference Vegetation Index (NDVI), and LST is examined. It highlights a negative correlation, demonstrating that increasing NDVI values are associated with decreased LST, except in regions with snow cover. Additionally, a micro-level analysis of Bengaluru City, Karnataka, showcases how LST patterns change concerning the transition from vegetation to urban areas. As vegetation cover decreases and urban areas expand, the LST range widens, indicating the local impact of land transformation on temperature dynamics. This research provides valuable insights into the complex interplay between land use changes, land cover dynamics, and LST patterns, enhancing our understanding of environmental and climate processes in diverse agroclimatic zones.