The current study analyses the satellite retrieved Land Surface Temperature (LST), LULC change in the National Capital Region (NCR) of India. A well-known parametric Maximum Likelihood Classifier algorithm (MLC) was employed for supervised spectral signature extraction of all Landsat images for five LULC classes such as Built-up area, Water body, Green vegetation, Rocky area and Bare land. After post-classification, results showed significant increase in area has been noticed from 2003 to 2009 with 75.68, and 26.72 % for Built-up area and Green vegetation, respectively while the Rocky area and Bare land decreased by 35.25% and 03.73%, respectively. In between 2009 to 2014 Built-up area and Green vegetation area cover further increases by 14.81 and 34.20% respectively while the Rocky area decreases by 50.17%. The mono-window algorithm has been used to retrieve LST map from the thermal band of Landsat level 1 data. The local pattern of LST was classified into four broad class (Lower, Moderate, High and Extreme) based on standard deviation. Results showed significant spatio-temporal change in LST in relation to different LULC types. Green vegetation, Built-up area and Rocky areas belong to Lower, Moderate and High LST class respectively. Similarly increasing trend has been observed for Built-up area and Green vegetation with area covered under Lower and Moderate class during studied period in NCR.