{"title":"地表温度与归一化差异裸露指数的季节关系","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":"{\"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}","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}
A seasonal relationship between land surface temperature and normalized difference bareness index
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.