REMOTE SENSING OF LAND SURFACE TEMPERATURE VARIABILITY: TECHNIQUES, TRENDS, AND APPLICATIONS IN PAKISTAN

Abstract

Land Surface Temperature (LST) is a critical parameter in climate studies, urban heat island (UHI) assessments, and hydrological modeling. With advancements in satellite remote sensing, LST can be effectively monitored at spatial and temporal scales across varied terrains. This study focuses on remote sensing techniques for analyzing LST variability using MODIS and Landsat data in Pakistan's arid, semi-arid, and urbanized regions. Spatiotemporal LST trends from 2000 to 2024 reveal significant increases in urban zones such as Lahore and Karachi, attributed to anthropogenic heat and land-use changes. Furthermore, the study highlights the role of vegetation indices, emissivity corrections, and climate feedback mechanisms in refining LST estimations. Remote sensing tools thus offer a viable framework for environmental monitoring, sustainable urban planning, and climate resilience strategies in Pakistan