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Building Change Detection Using a Shape Context Similarity Model for LiDAR Data

by 1, 2 and 3,*
1
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
2
NASG Key Laboratory of Land Environment and Disaster Monitoring, China University of Mining and Technology, Xuzhou 221116, China
3
Department of Land Surveying and Geo-Informatics, Smart Cities Research Institute, The Hong Kong Polytechnic University, Hong Kong 999077, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2020, 9(11), 678; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9110678
Received: 4 September 2020 / Revised: 26 October 2020 / Accepted: 13 November 2020 / Published: 15 November 2020
In this paper, a novel building change detection approach is proposed using statistical region merging (SRM) and a shape context similarity model for Light Detection and Ranging (LiDAR) data. First, digital surface models (DSMs) are generated from LiDAR acquired at two different epochs, and the difference data D-DSM is created by difference processing. Second, to reduce the noise and registration error of the pixel-based method, the SRM algorithm is applied to segment the D-DSM, and multi-scale segmentation results are obtained under different scale values. Then, the shape context similarity model is used to calculate the shape similarity between the segmented objects and the buildings. Finally, the refined building change map is produced by the k-means clustering method based on shape context similarity and area-to-length ratio. The experimental results indicated that the proposed method could effectively improve the accuracy of building change detection compared with some popular change detection methods. View Full-Text
Keywords: DSM; SRM; shape context similarity model; building change detection DSM; SRM; shape context similarity model; building change detection
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MDPI and ACS Style

Lyu, X.; Hao, M.; Shi, W. Building Change Detection Using a Shape Context Similarity Model for LiDAR Data. ISPRS Int. J. Geo-Inf. 2020, 9, 678. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9110678

AMA Style

Lyu X, Hao M, Shi W. Building Change Detection Using a Shape Context Similarity Model for LiDAR Data. ISPRS International Journal of Geo-Information. 2020; 9(11):678. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9110678

Chicago/Turabian Style

Lyu, Xuzhe, Ming Hao, and Wenzhong Shi. 2020. "Building Change Detection Using a Shape Context Similarity Model for LiDAR Data" ISPRS International Journal of Geo-Information 9, no. 11: 678. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi9110678

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