【摘 要】
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This case study evaluates the seasonal variability of the Pearson\'s linear correlation coefficient of land surface temperature (LST) with some spectral indices like NDVI,NDWI,NDBI,and NDBal by using a series of Landsat images for 1991-92,1995-96,1999-0
【机 构】
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Department of Applied Geology,National Institute of Technology Raipur,India;Department of Remote Sen
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This case study evaluates the seasonal variability of the Pearson\'s linear correlation coefficient of land surface temperature (LST) with some spectral indices like NDVI,NDWI,NDBI,and NDBal by using a series of Landsat images for 1991-92,1995-96,1999-00,2004-05,2009-10,2014-15,and 2018-19.The results from the average correlation of the entire period of all-season show that the LST builds a positive correlation with NDBI (0.71) and NDBaI (0.52) while it builds a negative correlation with NDVI (0.44).The LST-NDWI correlation is insignificant,The best correlation is noticed in the post-monsoon period,while the least correlation is observed in the winter season.This study can support the environmental planning to build a sustainable city under a similar environment.
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