Estimating the seasonal relationship between land surface temperature and normalized difference bareness index using Landsat data series

Authors : Subhanil GUHA, Himanshu GOVİL

Pages : 9-16

Doi:10.26833/ijeg.833260

View : 18 | Download : 21

Publication Date : 2022-02-15

Article Type : Research Paper

Abstract :The present study analyzes the seasonal variability of the relationship between the land surface temperature insert ignore into journalissuearticles values(LST); and normalized difference bareness index insert ignore into journalissuearticles values(NDBaI); on different land use/land cover insert ignore into journalissuearticles values(LULC); in Raipur City, India by using sixty-five Landsat images of four seasons insert ignore into journalissuearticles values(pre-monsoon, monsoon, post-monsoon, and winter); of 1991-1992, 1995-1996, 1999-2000, 2004-2005, 2009-2010, 2014-2015, and 2018-2019. The mono-window algorithm was used to retrieve LST and Pearson`s correlation coefficient was used to generate the LST-NDBaI relationship. The post-monsoon season builds the best correlation insert ignore into journalissuearticles values(0.59); among the four seasons. The water bodies builds a moderate to strong positive correlation insert ignore into journalissuearticles values(>0.50); in all the four seasons. On green vegetation, this correlation is moderate to strong positive insert ignore into journalissuearticles values(>0.54); in the three seasons, except the pre-monsoon season. The built-up area and bare land generate a moderate positive correlation insert ignore into journalissuearticles values(>0.34); in all the four seasons. Among the four seasons, the post-monsoon season builds the best correlation for all LULC types, whereas the pre-monsoon season has the least correlation. This research work is useful for environmental planning of other citieswith similar climatic conditions.
Keywords : Landsat, LST, LULC, NDBal, Raipur