Using Moran's I and GIS to study the spatial pattern of land surface temperature in relation to land use/cover around a thermal power plant in Singrauli district, Madhya Pradesh, India

Abstract

Fast emerging energy hub of India – Singrauli, Madhya Pradesh is undergoing a drastic transformation in its land use and land cover (LU/LC) owing to the mega power projects coming up in the area. Once densely covered with forests, the study area has changed through cleared land to thermal power plant and related infrastructure from 2005 to 2015. A sharp descent is observed in the forest cover while wasteland has increased during the study period. With the upsurge of thermal power plants in the area, the ambient temperatures have also increased leading to urban heat island effect. In the present study, changes in Land Surface Temperature (LST) around 10 km2 of Sasan Ultra Mega Thermal Power Plant is studied for three years 2005, 2010 and 2015, respectively using Moran's I geostatistics in GIS environment. Spatial autocorrelation is a characteristic property of most ecological parameters and can be seen at all spatial scales. Spatial clustering of LST in an ecosystem can play a vital role in evaluating land use/cover dynamics. The Moran's I reveal a high positive spatial autocorrelation or highly clustered pattern of obtained LST values for all the three years. The spatial variation of LST is also observed to be related to the LU/LC of the study site during the different study periods.