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Effects of Green Space Spatial Distribution on Land Surface Temperature:Implications for Land Cover Change as Environmental Indices


Affiliations
1 Department of Environmental Science & Engineering, Indian Institute of Technology (ISM), Dhanbad-826004, Jharkhand, India
 

This research presents the study for the evaluation of Land surface temperature (LST) and Vegetation relationship of the Noamundi Iron ore mines areas, West Singhbhum district. The authors are utilizing a geographic information system (GIS) and advance Remote sensing technique to estimate the land surface emissivity (LSE), Normalized Difference Vegetation Index (NDVI) and LST. LST is strongly influenced by the ability of the LSE, depends on Surface vegetation cover (SVC). The experiment has carried out on Landsat ETM+ satellite images for the studies. The maximum LST of the study area are 32.1°c and mean values are 23.99°c as the period of December is winter season but the LST may increase in summer season. Other side the distribution of NDVI values are varying from -0.378 to 0.516. Due to some active surface mines or some non-vegetated surface are situated in the area, indicating high LST. The statistics indicates the strong negative correlation of 0.932 between NDVI and LST. Further, this analysis may use as a part of sustainability model or environmental sustainability Index (ESI) and Human comfort analysis.

Keywords

Land Surface Temperature, NDVI, Land Surface Emissivity, TIR and Linear Correlation.
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  • Effects of Green Space Spatial Distribution on Land Surface Temperature:Implications for Land Cover Change as Environmental Indices

Abstract Views: 169  |  PDF Views: 135

Authors

Surajit Panda
Department of Environmental Science & Engineering, Indian Institute of Technology (ISM), Dhanbad-826004, Jharkhand, India
Manish Kumar Jain
Department of Environmental Science & Engineering, Indian Institute of Technology (ISM), Dhanbad-826004, Jharkhand, India

Abstract


This research presents the study for the evaluation of Land surface temperature (LST) and Vegetation relationship of the Noamundi Iron ore mines areas, West Singhbhum district. The authors are utilizing a geographic information system (GIS) and advance Remote sensing technique to estimate the land surface emissivity (LSE), Normalized Difference Vegetation Index (NDVI) and LST. LST is strongly influenced by the ability of the LSE, depends on Surface vegetation cover (SVC). The experiment has carried out on Landsat ETM+ satellite images for the studies. The maximum LST of the study area are 32.1°c and mean values are 23.99°c as the period of December is winter season but the LST may increase in summer season. Other side the distribution of NDVI values are varying from -0.378 to 0.516. Due to some active surface mines or some non-vegetated surface are situated in the area, indicating high LST. The statistics indicates the strong negative correlation of 0.932 between NDVI and LST. Further, this analysis may use as a part of sustainability model or environmental sustainability Index (ESI) and Human comfort analysis.

Keywords


Land Surface Temperature, NDVI, Land Surface Emissivity, TIR and Linear Correlation.