The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-8
https://doi.org/10.5194/isprsarchives-XL-8-1447-2014
https://doi.org/10.5194/isprsarchives-XL-8-1447-2014
23 Dec 2014
 | 23 Dec 2014

Remote Sensing Based Analysis of the Role of Land Use/Land Cover on Surface Temperature and Temporal Changes in Temperature; a Case Study of Ajmer District, Rajasthan

A. Hussain, P. Bhalla, and S. Palria

Keywords: Surface temperature, Processing, Analysis, Correlation, Comparison, Sampling, Satellite, Temporal

Abstract. An attempt has been made in this research to analyze temporal variations in surface temperature in Ajmer District Rajasthan. The research is carried out to assess the relationship between the land surface temperatures (LST) and land cover (LC) changes both in quantitative and qualitative ways in Ajmer District area using Landsat TM/ETM+ data over the period 1989 to 2013.in this period we used three temporal TM/ETM data 1989, 2001 and 2013. Remote sensing of Land surface temperature (LST) has traditionally used the Normalized Difference Vegetation Index (NDVI) as the indicator of vegetation abundance to estimate the land surface temperature (LST)–vegetation relationship. Unsupervised classification methods have been taken to prepare the LC map. LST is derived from the thermal band of Landsat TM/ETM+ using the calibration of spectral radiance and emissivity correction of remote sensing. NDVI is derived from the NIR & RED Band using image enhancement technique (Indices). Arc-GIS have been utilized for data visualization. This procedure allowed analyzing whether LULC classes match LST classes. However, the results of such overlaying are hard to interpret. LST and LULC maps of these areas give the understanding on how the classes and corresponding LST have changed from one date to the other. Another option is to collect statistical data. it was impossible to calculate linear regression between LULC map and LST map. A solution to that matter is to use Normalized Vegetation Index (NDVI) instead of LULC classification result.