{"title":"A seasonal relationship between land surface temperature and normalized difference bareness index","authors":"S. Guha, H. Govil","doi":"10.4314/sajg.v10i2.12","DOIUrl":null,"url":null,"abstract":"The present study analyzes the seasonal variability of the relationship between the land surface temperature (LST) and normalized difference bareness index (NDBaI) on different land use/land cover (LULC) in Raipur City, India by using sixty-five Landsat images of four seasons (pre-monsoon, monsoon, post-monsoon, and winter) of 1991-1992, 1995-1996, 1999-2000, 2004-2005, 2009-2010, 2014-2015, and 2018-2019. The results show that the post-monsoon season indicates the best correlation (0.59), followed by the monsoon (0.56), pre-monsoon (0.47), and winter (0.44) season. The water bodies reflect a strongly positive correlation in all the four seasons (0.65 in pre-monsoon, 0.51 in monsoon, 0.53 in post-monsoon, and 0.62 in winter). On green vegetation, this correlation is also strongly positive in monsoon (0.57), post-monsoon (0.62), and winter (0.55), whereas it is moderate positive in pre-monsoon (0.37) season. The built-up area and bare land build a moderate positive correlation in all the four seasons (0.35 in pre-monsoon, 0.43 in monsoon, 0.48 in post-monsoon, and 0.39 in winter). 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 beneficial for land use and environmental planning of any city under similar climatic conditions.","PeriodicalId":43854,"journal":{"name":"South African Journal of Geomatics","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2022-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"South African Journal of Geomatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4314/sajg.v10i2.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0
Abstract
The present study analyzes the seasonal variability of the relationship between the land surface temperature (LST) and normalized difference bareness index (NDBaI) on different land use/land cover (LULC) in Raipur City, India by using sixty-five Landsat images of four seasons (pre-monsoon, monsoon, post-monsoon, and winter) of 1991-1992, 1995-1996, 1999-2000, 2004-2005, 2009-2010, 2014-2015, and 2018-2019. The results show that the post-monsoon season indicates the best correlation (0.59), followed by the monsoon (0.56), pre-monsoon (0.47), and winter (0.44) season. The water bodies reflect a strongly positive correlation in all the four seasons (0.65 in pre-monsoon, 0.51 in monsoon, 0.53 in post-monsoon, and 0.62 in winter). On green vegetation, this correlation is also strongly positive in monsoon (0.57), post-monsoon (0.62), and winter (0.55), whereas it is moderate positive in pre-monsoon (0.37) season. The built-up area and bare land build a moderate positive correlation in all the four seasons (0.35 in pre-monsoon, 0.43 in monsoon, 0.48 in post-monsoon, and 0.39 in winter). 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 beneficial for land use and environmental planning of any city under similar climatic conditions.