Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1203-1208, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1203-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1203-1208, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-1203-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

A METHOD OF GENERATING DEM FROM DSM BASED ON AIRBORNE INSAR DATA

W. Lu1,2, J. Zhang1,2, G. Xue1,2, and C. Wang1,2 W. Lu et al.
  • 1Shan dong University of Science and Technology, Qingdao 266590, China
  • 2Key Laboratory of Geo-Informatics of State Bureau of Surveying and Mapping, Chinese Academy of Surveying and Mapping, Beijing 100830, China

Keywords: InSAR, DSM, Adaptive Threshold Segmentation, DEM, Filtering

Abstract. Traditional methods of terrestrial survey to acquire DEM cannot meet the requirement of acquiring large quantities of data in real time, but the DSM can be quickly obtained by using the dual antenna synthetic aperture radar interferometry and the DEM generated by the DSM is more fast and accurate. Therefore,it is most important to acquire DEM from DSM based on airborne InSAR data. This paper aims to the method that generate DEM from DSM accurately. Two steps in this paper are applied to acquire accurate DEM. First of all, when the DSM is generated by interferometry, unavoidable factors such as overlay and shadow will produce gross errors to affect the data accuracy, so the adaptive threshold segmentation method is adopted to remove the gross errors and the threshold is selected according to the coherence of the interferometry. Secondly DEM will be generated by the progressive triangulated irregular network densification filtering algorithm. Finally, experimental results are compared with the existing high-precision DEM results. The results show that this method can effectively filter out buildings, vegetation and other objects to obtain the high-precision DEM.