SPACE BASED SPATIO-TEMPORAL ASSESSMENT OF LAND SURFACE TEMPERATURE IN KARUNAGAPPALLY MUNICIPALITY, A FAST GROWING CITY IN THE WESTERN COAST OF INDIA
- 1Department of Chemistry, Amrita Viswa Vidyapeetham, Amritapuri Campus, Kerala, India
- 2Dr. R. Satheesh Centre for Remote Sensing and GIS, Mahatma Gandhi University, Kerala, India
Keywords: Landsat, Thermal Band, Brightness Temperature, Karunagappally, Land Surface Temperature, Spatio-Temporal
Abstract. Urbanization is the process by which towns and cities are formed and become larger as more and more people begin living and working in central areas. According to 2001 census, the urban population of the country was 286.11 million, living in 5161 towns, which constitutes 27.81% of the total country’s population. However, the same as per 2011 census has risen to 377.16 million viz. 32.16% of the total country’s population and the number of towns has gone up to 7935. The rate of urban growth in the country is very high as compared to developed countries, and the large cities are becoming larger mostly due to continuous migration of population to these cities. India’s current urban population exceeds the whole population of the United States, the world’s third largest country. By 2050, over half of India’s population is expected to be urban dwellers. This creates enormous pressure on existing urban infrastructure.
Urbanization trend in the State of Kerala shows marked peculiarities. The main reason for urban population growth is the increase in the number of urban areas and urbanization of the peripheral areas of the existing major urban centers. However, unlike the other parts of the country the Urbanization in Kerala is not limited to the designated cities and towns. The difference between rural and urban agglomerations is very negligible as far as Kerala is concerned. The Kerala society by and large can be termed as urbanized. Kerala has been witnessing rapid urbanization since 1980.
The present study, is an attempt to analyses the extent of land use/ land cover changes in the Municipality over the years from 2012 to 2017 and land surface variation over the years from 2000 to 2017.The land use/ land cover pattern of 2012 to 2017 was extracted from High resolution images of the study area were downloaded from Google Earth API and the Land Surface Temperature changes were analyzed from the thermal bands of the Landsat Imageries.