Volume III-3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, 249-255, 2016
https://doi.org/10.5194/isprs-annals-III-3-249-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-3, 249-255, 2016
https://doi.org/10.5194/isprs-annals-III-3-249-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

  03 Jun 2016

03 Jun 2016

AUTOMATIC EXTRACTION OF DTM FROM LOW RESOLUTION DSM BY TWOSTEPS SEMI-GLOBAL FILTERING

Yanfeng Zhang, Yongjun Zhang, Yi Zhang, and Xin Li Yanfeng Zhang et al.
  • School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

Keywords: DTM, DSM, Slope map, Semi-Global Filtering, Segmentation, Classification

Abstract. Automatically extracting DTM from DSM or LiDAR data by distinguishing non-ground points from ground points is an important issue. Many algorithms for this issue are developed, however, most of them are targeted at processing dense LiDAR data, and lack the ability of getting DTM from low resolution DSM. This is caused by the decrease of distinction on elevation variation between steep terrains and surface objects. In this paper, a method called two-steps semi-global filtering (TSGF) is proposed to extract DTM from low resolution DSM. Firstly, the DSM slope map is calculated and smoothed by SGF (semi-global filtering), which is then binarized and used as the mask of flat terrains. Secondly, the DSM is segmented with the restriction of the flat terrains mask. Lastly, each segment is filtered with semi-global algorithm in order to remove non-ground points, which will produce the final DTM. The first SGF is based on global distribution characteristic of large slope, which distinguishes steep terrains and flat terrains. The second SGF is used to filter non-ground points on DSM within flat terrain segments. Therefore, by two steps SGF non-ground points are removed robustly, while shape of steep terrains is kept. Experiments on DSM generated by ZY3 imagery with resolution of 10-30m demonstrate the effectiveness of the proposed method.