Land use and land surface temperature both plays a crucial role in the global climate change studies, as a little fluctuation in these, can bring about a dramatic impact on the regional as well as global environment. With rapid urbanization many regions across the world are altering the existing land use/land cover (LULC), which is significantly raising the land surface temperature (LST). The present study aims to estimate the land use change and land surface temperature and what changes does both bring about in a span of 20 years over Faridabad MC. Faridabad being a part of Delhi NCR has seen rapid growth of population in last two decades which has severely impacted its Land cover. Landsat imagery of 2002, 2013 and 2022 has been used for estimating both the LULC and LST of the city. Supervised classification with Maximum likelihood Classification (MLC) which is basically a machine learning based algorithm has been adopted for LULC classification and Mono window algorithm has been used for the retrieval of LST. UTFVI (Urban Thermal Field Variance Index) has also been calculated which showed different Urban heat islands across the city. The results reveal a rapid increase in the built-up area and reduction in the vegetation and agricultural land. Similarly, Land surface temperature was highest in highly dense built-up areas as well in the barren area of Faridabad, compared to this LST was comparatively lower over the agriculture and vegetation and least of water bodies. There were several UHI hotspots over the city area, mostly located in the densely populated and industrial parts of city.