An assessment of land surface temperature dynamics due to urbanization in national capital region of india

Author: 
Kumar Anandam., Krishan Kumar., Deepak Singh., Amit Kumar and Vinod Kumar Jain

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.

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DOI: http://dx.doi.org/10.24327/ijcar.2017.8179.1305