Automatic building rooftop extraction using a digital surface model derived from aerial stereo images. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Wu, Bin; Wu, Siyuan; Li, Yong; Wu, Jianping; Huang, Yan; Chen, Zuoqi; Yu, Bailang
• Is Part Of: Journal of spatial science. Volume 67:Issue 1(2022)
• Page Start: 21
• Page End: 40
• Publication Date: 2022-01-02
• Subjects: Building rooftop -- digital surface model -- large urban area -- dilation reconstruction -- region growing and merging; Geographic information systems -- Periodicals; Cartography -- Periodicals; Surveying -- Periodicals; Geodesy -- Periodicals; Photogrammetry -- Periodicals; Cartography; Geodesy; Geographic information systems; Photogrammetry; Surveying; Periodicals; 526.05
• DOI: 10.1080/14498596.2020.1720836
• Languages: English
• ISSNs: 1449-8596

Abstract

ABSTRACT: 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.