Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 715-718, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-715-2018
© 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, 715-718, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-715-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

BUILDING EXTRACTION BASED ON OPENSTREETMAP TAGS AND VERY HIGH SPATIAL RESOLUTION IMAGE IN URBAN AREA

L. Kang1,2, Q. Wang3, and H. W. Yan1,2 L. Kang et al.
  • 1Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
  • 2Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China
  • 3School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China

Keywords: Building extraction, OpenStreetMap, Very High Spatial Resolution, Tag-based, Automatic interpretation, urban area

Abstract. How to derive contour of buildings from VHR images is the essential problem for automatic building extraction in urban area. To solve this problem, OSM data is introduced to offer vector contour information of buildings which is hard to get from VHR images. First, we import OSM data into database. The line string data of OSM with tags of building, amenity, office etc. are selected and combined into completed contours; Second, the accuracy of contours of buildings is confirmed by comparing with the real buildings in Google Earth; Third, maximum likelihood classification is conducted with the confirmed building contours, and the result demonstrates that the proposed approach is effective and accurate. The approach offers a new way for automatic interpretation of VHR images.