Automatic building rooftop extraction using a digital surface model derived from aerial stereo images

作者：Wu, Bin; Wu, Siyuan; Li, Yong; Wu, Jianping; Huang, Yan; Chen, Zuoqi; Yu, Bailang^*

来源：Journal of Spatial Science, 2022, 67(1): 21-40.

DOI：10.1080/14498596.2020.1720836

• Building rooftop
• digital surface model
• large urban area
• dilation reconstruction
• region growing and merging

Automatic building rooftop extraction is of great importance to many applications including building reconstruction, solar energy supply, and disaster management. This study proposes a building rooftop extraction method using DSM data generated from aerial stereo images and vegetation cover vector data. The method consists of five steps: noise filtering, dilation reconstruction, vegetation and terrain region removal, region growing and merging, and post-processing. We applied the proposed method to the centre of Shanghai, China, a typical urban area. Experimental results show that the proposed method can successfully extract building rooftops, with an approximately 82.6% quality percentage and 96.2% matched overlay.

• 单位
  福州大学