ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume IV-3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 225–232, 2018
https://doi.org/10.5194/isprs-annals-IV-3-225-2018
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-3, 225–232, 2018
https://doi.org/10.5194/isprs-annals-IV-3-225-2018

  23 Apr 2018

23 Apr 2018

A SEMI-EMPIRICAL TOPOGRAPHIC CORRECTION MODEL FOR MULTI-SOURCE SATELLITE IMAGES

Sa Xiao1, Xinpeng Tian1, Qiang Liu1,2, Jianguang Wen2,3, Yushuang Ma1, and Zhenwei Song1 Sa Xiao et al.
  • 1College of Global Change and Earth System Science,Beijing Normal University,China
  • 2State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100875, China
  • 3Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, Beijing 100101, China

Keywords: Remote sensing, Topographic correction, Mountain areas, DEM, multi-source data, 6S

Abstract. Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.