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Retrieval of Land SurfaceTemperature based on High Resolution Landsat 8 Satellite Data
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  • Journal title : Korean Journal of Remote Sensing
  • Volume 32, Issue 2,  2016, pp.171-183
  • Publisher : The Korean Society of Remote Sensing
  • DOI : 10.7780/kjrs.2016.32.2.9
 Title & Authors
Retrieval of Land SurfaceTemperature based on High Resolution Landsat 8 Satellite Data
Jee, Joon-Bum; Kim, Bu-Yo; Zo, Il-Sung; Lee, Kyu-Tae; Choi, Young-Jean;
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 Abstract
Land Surface Temperature (LST) retrieved from Landsat 8 measured from 2013 to 2014 and it is corrected by surface temperature observed from ground. LST maps are retrieved from Landsat 8 calculate using the linear regression function between raw Landsat 8 LST and ground surface temperature. Seasonal and annual LST maps developed an average LST from season to annual, respectively. While the higher LSTs distribute on the industrial and commercial area in urban, lower LSTs locate in surrounding rural, sea, river and high altitude mountain area over Seoul and surrounding area. In order to correct the LST, linear regression function calculate between Landsat 8 LST and ground surface temperature observed 3 Korea Meteorological Administration (KMA) synoptic stations (Seoul(ID: 108), Incheon(ID: 112) and Suwon(ID: 119)) on the Seoul and surrounding area. The slopes of regression function are 0.78 with all data and 0.88 with clear sky except 5 cloudy pixel data. And the original Landsat 8 LST have a correlation coefficient with 0.88 and Root Mean Square Error (RMSE) with . After LST correction, the LST have correlation coefficient with 0.98 and RMSE with and the slope of regression equation improve the 0.95. Seasonal and annual LST maps represent from urban to rural area and from commercial to industrial region clearly. As a result, the Landsat 8 LST is more similar to the real state when corrected by surface temperature observed ground.
 Keywords
Landsat 8;Land Surface Temperature;Ground Surface Temperature;Seoul;Linear Regression Function;
 Language
Korean
 Cited by
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