Urbanization and its related environmental problem in Srirangam Island, Tiruchirappalli district of Tamil Nadu, India-Thermal Remote Sensing and GIS approach

Abstract

A standard mathematical equation was adapted in this study to estimate the land surface temperature (LST) using thermal band from Landsat ETM+ and Landsat TIRS for Srirangam Island of Tiruchirappalli district, Tamilnadu. Temporal variation of LST for the year 2001 and 2013 has been analyzed and correlated with respect to Urbanization which indicates that the land surface temperature of the Srirangam River Island has been significantly raised up to 1.1°C within a period of 13 years. LST range varies from 24.1 to 34.8 °C for the year of 2001 and from 24.7 to 35.9 °C for 2013. The comparison of 2001 and 2013 LST variation with land use land cover of the respective period indicates that transforming of land cover to built-up land might have played a major role in the temperature change. LST shows increasing trend around the urban settlement near SE of Mutharasanallur, S of Pichchandar Kovil and river sand exposed along the Cauvery and Coleroon River bed. Interestingly, the eastern side along the Cooleran River shows decreasing trend in temperature which may be due to development in agricultural and sand mining activities. Vegetation cover, wet land and water body zones exhibit relatively low temperature due to heat sink nature which indicates that the change in land use pattern has higher impact on the LST variation. Therefore, it is very important to identify the relation between LST and vegetation variation. For this type of study, NDVI is the most widely used technique. However, in this present study, NDVI along with Tasseled Cap transformation (brightness, greenness and wetness) has been performed and observed that the LST has significant relation with NDVI, brightness, greenness and wetness. Visual interpretation, N-S profiles and scatter plot of LST against NDVI, greenness and wetness have shown negative correlation and brightness gives positive relation which clearly indicates that the vegetation cover and water bodies have reduced the temperature; however, built-up land and sand area is increased in temperature. The present study revealed the potential of the thermal infrared remote sensing for LST estimation, variation and change deduction with respect to urbanization.