Efficient Building Inventory Extraction from Satellite Imagery for Megacities

被引:1
作者
Lo, Edmond Yat-Man [1 ,2 ]
Lin, En-Kai [3 ]
Daksiya, Velautham [1 ]
Shao, Kuo-Shih [3 ]
Chuang, Yi-Rung [3 ]
Pan, Tso-Chien [1 ,2 ]
机构
[1] Nanyang Technol Univ, Inst Catastrophe Risk Management, Block N1, Level B1b, 50 Nanyang Ave, Singapore 639798, Singapore
[2] Nanyang Technol Univ, Sch Civil & Environm Engn, Block N1,50 Nanyang Ave, Singapore 639798, Singapore
[3] Sinotech Engn Consultants Inc, 171 Sec 5,Nanking E Rd, Taipei, Taiwan
关键词
DIGITAL SURFACE MODEL; FOOTPRINT EXTRACTION; RISK-ASSESSMENT; RECONSTRUCTION; GENERATION; SCENES;
D O I
10.14358/PERS.21-00053R2
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Accurate building inventories are essential for city planning and disaster risk management. Traditionally generated via census or selected small surveys, these suffer from data quality and/or resolu-tion. High-resolution satellite imagery with object segmentation provides an effective alternative, readily capturing large extents. This study develops a highly automated building extraction method-ology for location-based building exposure data from high (0.5 m) resolution satellite stereo imagery. The development relied on Taipei test areas covering 13.5 km2 before application to the megacity of Jakarta. Of the captured Taipei buildings, 48.8% are at one-to-one extraction, improving to 71.9% for larger buildings with total floor area > 8000 m2, and to 99% when tightly-spaced building clusters are further included. Mean absolute error in extracted footprint area is 16% for these larger buildings. The extraction parameters are tuned for Jakarta buildings using small test areas before cover-ing Jakarta's 643 km2 with over 1.247 million buildings extracted.
引用
收藏
页码:643 / 652
页数:10
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