Multi-level building change detection based on the DSM and DOM generated from UAV images
CHAI Jiaxing1(), ZHANG Yunsheng1,2,3(), YANG Zhen1, CHEN Siyang1, LI Haifeng1
1. School of Geosciences and Info-physics, Central South University, Changsha 410012, China 2. Hunan Provincial Key Laboratory of Key Technology on Hydropower Development, Power China Zhongnan Engineering Co., Ltd., Changsha 410021, China 3. Key Laboratory of Ecological Environment Protection of Space Information Application of Henan, Zhengzhou 450046, China
The continuous advancement of urbanization in China leads to frequently changing urban buildings. Hence, grasping the change information of urban buildings duly and accurately holds critical significance for urban management, investigation of unauthorized construction, and disaster assessment. This study proposed a multi-level building change detection method combined with the digital surface model (DSM) and digital orthophoto map (DOM) generated from unmanned aerial vehicle (UAV) images. The proposed method consists of four steps: ① The dense point cloud and DOM generated from UAV images were pre-processed to generate differential normalized DSM (dnDSM) and extract vegetation zones; ② Candidate change zones were extracted using multi-level height difference thresholds, with vegetation and smaller zones eliminated; ③ The connected component analysis was conducted for lower-level candidate change zones. For connected objects, their higher-level change detection results were used to eliminate false detection results in the lower level; ④ The quantitative relationship between positive and negative height difference values of change objects was statistically analyzed to determine the change types. As demonstrated by experimental results, the proposed method can retain the change information of low-rise buildings detected through the lower height difference thresholds while ensuring correct and complete change information of high-rise buildings.
柴佳兴, 张云生, 杨振, 陈斯飏, 李海峰. 联合无人机影像生成DSM和DOM的多层次建筑物变化检测[J]. 自然资源遥感, 2024, 36(2): 80-88.
CHAI Jiaxing, ZHANG Yunsheng, YANG Zhen, CHEN Siyang, LI Haifeng. Multi-level building change detection based on the DSM and DOM generated from UAV images. Remote Sensing for Natural Resources, 2024, 36(2): 80-88.
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2024, Vol. 36 
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