{"title":"Spatiotemporal Analysis of Land Surface Temperature in Tainan City by using Landsat 5 & Landsat 8","authors":"R. Rahmad, Zhiyu Gong, Zhaohui Yang, Meijun Guo","doi":"10.24114/jg.v15i1.37183","DOIUrl":null,"url":null,"abstract":"Taiwan is a subtropic-tropic island with densely populated in the coastal plains surrounding its mountains. In recent years, due to global warming and the urban heat island effect, the surface temperature has continued to rise, and the seasonal temperature changes are also very different. Increased surface temperatures, particularly in cities, are a major environmental issue that intensifies urban heat islands (UHIs). Decadal time-series analysis has historically relied on meteorological data. Due to the limited availability of remote sensing technology, decadal analysis of land surface temperature has been a serious concern. However, according to advanced technologies in remote sensing methods and sophisticated GIS software, Land Surface Temperature (LST) now can be estimated using thermal bands. The objective of this study is to monitor the spatiotemporal changes of the land surface temperature using Landsat 5 and Landsat 8. Tainan city, which is a highly developed city in southern Taiwan, is selected as the research area. The changes in the land surface temperature are assessed between the years 2007 and 2021. It simply requires applying a set of equations through a raster image calculator using ArcGIS. The LST of any Landsat satellite image can be retrieved by following steps: 1) Top of Atmospheric Spectral Radiance; 2) Conversion of Radiance to At-Sensor Temperature; 3) Calculating NDVI; 4) Calculating the Proportion of Vegetation; 5) Determination of ground emissivity, and 6) Calculating Land Surface Temperature. Near Infra-red are used to obtain Normalized Different Vegetation Index (NDVI). The results show that the average surface temperature of Tainan City increased slightly by 1.1 0C. The most significant increase in temperature was in the northern region of Tainan City which was the agricultural area that was in the post-harvest period.Keywords: Land Surface Temperature (LST), Landsat 5, Landsat 8, Tainan City, GIS","PeriodicalId":31787,"journal":{"name":"Jurnal Geografi","volume":"24 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Geografi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24114/jg.v15i1.37183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Taiwan is a subtropic-tropic island with densely populated in the coastal plains surrounding its mountains. In recent years, due to global warming and the urban heat island effect, the surface temperature has continued to rise, and the seasonal temperature changes are also very different. Increased surface temperatures, particularly in cities, are a major environmental issue that intensifies urban heat islands (UHIs). Decadal time-series analysis has historically relied on meteorological data. Due to the limited availability of remote sensing technology, decadal analysis of land surface temperature has been a serious concern. However, according to advanced technologies in remote sensing methods and sophisticated GIS software, Land Surface Temperature (LST) now can be estimated using thermal bands. The objective of this study is to monitor the spatiotemporal changes of the land surface temperature using Landsat 5 and Landsat 8. Tainan city, which is a highly developed city in southern Taiwan, is selected as the research area. The changes in the land surface temperature are assessed between the years 2007 and 2021. It simply requires applying a set of equations through a raster image calculator using ArcGIS. The LST of any Landsat satellite image can be retrieved by following steps: 1) Top of Atmospheric Spectral Radiance; 2) Conversion of Radiance to At-Sensor Temperature; 3) Calculating NDVI; 4) Calculating the Proportion of Vegetation; 5) Determination of ground emissivity, and 6) Calculating Land Surface Temperature. Near Infra-red are used to obtain Normalized Different Vegetation Index (NDVI). The results show that the average surface temperature of Tainan City increased slightly by 1.1 0C. The most significant increase in temperature was in the northern region of Tainan City which was the agricultural area that was in the post-harvest period.Keywords: Land Surface Temperature (LST), Landsat 5, Landsat 8, Tainan City, GIS