International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Volume XLII-3/W10
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 831–837, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-831-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W10, 831–837, 2020
https://doi.org/10.5194/isprs-archives-XLII-3-W10-831-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  08 Feb 2020

08 Feb 2020

EXTRACTION OF HOUSES FROM POINT CLOUD LIDAR: PROBLEMS AND CHALLENGE

G. Q. Zhou1 and W. Q. Di2 G. Q. Zhou and W. Q. Di
  • 1Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, 12 Jian’gan Road, Guilin, Guangxi 541004, China
  • 2College of Earth Sciences, China

Keywords: Image Processing, Aerial Image, LiDAR, Extraction, House, Urban

Abstract. Although many efforts have been made on the extraction of houses from LiDAR (Light Detection and Ranging) and/or aerial imagery and/or their fusion, little investigation using co-registration between the orthoimage map and LiDAR on the basis of geodetic coordinates as element for house extraction. For this reason, this paper first overviews the advances of LiDAR and investigates the advantages and disadvantages of LiDAR system vs. traditional photogrammetry, and then indicates that LiDAR technology has not yet resolved all existing problems that traditional photogrammetry remained so far, such as texture information, LiDAR point cloud density. A comprehensive comparison in extraction of houses (feature information) from LiDAR data set and from aerial imagery are also presented. It has been widely accepted and admitted that full automation for extraction of houses (feature information in city area) from LiDAR point cloud has still been difficult. Therefore, this paper proposes a human-computer interaction operation for houses extraction through combination of LiDAR point cloud and the orthorectified high-resolution aerial imagery. The real data is utilized for validation of the proposed method.