The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-4/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W4, 117–122, 2017
https://doi.org/10.5194/isprs-archives-XLII-4-W4-117-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W4, 117–122, 2017
https://doi.org/10.5194/isprs-archives-XLII-4-W4-117-2017

  26 Sep 2017

26 Sep 2017

LAND USE ANALYSIS ON LAND SURFACE TEMPERATURE IN URBAN AREAS USING A GEOGRAPHICALLY WEIGHTED REGRESSION AND LANDSAT 8 IMAGERY, A CASE STUDY: TEHRAN, IRAN

A. Karimi1, P. Pahlavani1, and B. Bigdeli2 A. Karimi et al.
  • 1School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran
  • 2School of Civil Engineering, Shahrood University of Technology, Shahrood, Iran

Keywords: Land Surface Temperature, Geographically Weighted Regression, Urban land use, Landsat 8

Abstract. Due to urbanization and changes in the urban thermal environment and because the land surface temperature (LST) in urban areas are a few degrees higher than in surrounding non-urbanized areas, identifying spatial factors affecting on LST in urban areas is very important. In this regard, due to the unique properties of spatial data, in this study, a geographically weighted regression (GWR) was used to identify effective spatial factors. The GWR is a suitable method for spatial regression issues, because it is compatible with two unique properties of spatial data, i.e. the spatial autocorrelation and spatial non-stationarity. In this study, the Landsat 8 satellite data on 18 August 2014 and Tehran land use data in 2006 was used for determining the land surface temperature and its effective factors. As a result, R2 value of 0.765983 was obtained by taking the Gaussian kernel. The results showed that the industrial,military, transportation, and roads areas have the highest surface temperature.