Building Change Detection Using Old Aerial Images and New LiDAR Data
AbstractBuilding change detection is important for urban area monitoring, disaster assessment and updating geo-database. 3D information derived from image dense matching or airborne light detection and ranging (LiDAR) is very effective for building change detection. However, combining 3D data from different sources is challenging, and so far few studies have focused on building change detection using both images and LiDAR data. This study proposes an automatic method to detect building changes in urban areas using aerial images and LiDAR data. First, dense image matching is carried out to obtain dense point clouds and then co-registered LiDAR point clouds using the iterative closest point (ICP) algorithm. The registered point clouds are further resampled to a raster DSM (Digital Surface Models). In a second step, height difference and grey-scale similarity are calculated as change indicators and the graph cuts method is employed to determine changes considering the contexture information. Finally, the detected results are refined by removing the non-building changes, in which a novel method based on variance of normal direction of LiDAR points is proposed to remove vegetated areas for positive building changes (newly building or taller) and nEGI (normalized Excessive Green Index) is used for negative building changes (demolish building or lower). To evaluate the proposed method, a test area covering approximately 2.1 km2 and consisting of many different types of buildings is used for the experiment. Results indicate 93% completeness with correctness of 90.2% for positive changes, while 94% completeness with correctness of 94.1% for negative changes, which demonstrate the promising performance of the proposed method. View Full-Text
Scifeed alert for new publicationsNever miss any articles matching your research from any publisher
- Get alerts for new papers matching your research
- Find out the new papers from selected authors
- Updated daily for 49'000+ journals and 6000+ publishers
- Define your Scifeed now
Du, S.; Zhang, Y.; Qin, R.; Yang, Z.; Zou, Z.; Tang, Y.; Fan, C. Building Change Detection Using Old Aerial Images and New LiDAR Data. Remote Sens. 2016, 8, 1030.
Du S, Zhang Y, Qin R, Yang Z, Zou Z, Tang Y, Fan C. Building Change Detection Using Old Aerial Images and New LiDAR Data. Remote Sensing. 2016; 8(12):1030.Chicago/Turabian Style
Du, Shouji; Zhang, Yunsheng; Qin, Rongjun; Yang, Zhihua; Zou, Zhengrong; Tang, Yuqi; Fan, Chong. 2016. "Building Change Detection Using Old Aerial Images and New LiDAR Data." Remote Sens. 8, no. 12: 1030.
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.