Spatio Temporal Dynamics of an Urban Area and Its Impact on Land Surface Temperature

Abstract

The present study is conducted in Dehradun Planning Area(DPA), located in Uttarakhand state of India. After becoming the intermittent capital of Uttarakhand state in the year 2000, DPA has experienced unprecedented urban growth, which has resulted in higher Land Surface Temperature (LST), increased pollution levelsand threats to ecosystem functions due to transformation of arable land, forests and water bodies to urban uses.The first objective of the present study investigates the spatio-temporal urban dynamics followed by the simulation of urban growth. Land cover maps of three years (i.e. 2000, 2010 and 2019) were generated from Landsat images using supervised Maximum Likelihood Classifier. The accuracy of the three maps was 89.3%, 90.1% and 90.6% respectively.Images of winter season were used for the analysis of land cover. Built-up area in the year 2029 was simulated using Simweight algorithm. The second objective discusses the efficacy of different LST retrieval algorithms (i.e. radiative transfer equation, single channel algorithm and mono window algorithm) using remote sensing data sets. LST values were retrieved from thermal data of winter and summer season of three years. Subsequently validation of LST results was done using regression-based downscaling of MODIS data. Among all, mono window algorithm was found optimum for the retrieval of LST. The third objective deliberates the investigation of the causable relationship between LST (winter and summer) and landscape patterns, delineation of LST urban hotspots and thermal comfort zones. The fourth objective discusses the LST trends over simulated urban area and suggestions for the mitigation measures. Artificial Neural Network (ANN) was used for predicting LST values over simulated built-up areas of year 2029. The results of the study would be helpful for the governing bodies to understand the level of urbanization, in preparing and implicating mitigation strategies for urban heat island effect and will contribute towards the sustainable development.