Volume XLII-3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 211-216, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-211-2018
© 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, 211-216, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-211-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  30 Apr 2018

30 Apr 2018

ROAD DAMAGE EXTRACTION FROM POST-EARTHQUAKE UAV IMAGES ASSISTED BY VECTOR DATA

Z. Chen and A. Dou Z. Chen and A. Dou
  • Institute of Earthquake Forecasting, China Earthquake Administration, Beijing 100036, China

Keywords: Road damage extraction, Damage assessment, Earthquake, UAV images, Object-oriented classification, Threshold detection

Abstract. Extraction of road damage information after earthquake has been regarded as urgent mission. To collect information about stricken areas, Unmanned Aerial Vehicle can be used to obtain images rapidly. This paper put forward a novel method to detect road damage and bring forward a coefficient to assess road accessibility. With the assistance of vector road data, image data of the Jiuzhaigou Ms7.0 Earthquake is tested. In the first, the image is clipped according to vector buffer. Then a large-scale segmentation is applied to remove irrelevant objects. Thirdly, statistics of road features are analysed, and damage information is extracted. Combining with the on-filed investigation, the extraction result is effective.