Open AccessAutomatic Building Reconstruction with Satellite Images and Digital Maps
Author(s) -
Lee DongCheon,
Yom JaeHong,
Shin Sung Woong,
Oh Jaehong,
Park Kisurk
Publication year - 2011
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.11.1610.0020
Subject(s) - computer vision , computer science , digital elevation model , artificial intelligence , matching (statistics) , terrain , remote sensing , epipolar geometry , satellite , geography , image (mathematics) , mathematics , cartography , engineering , statistics , aerospace engineering
This paper introduces an automated method for building height recovery through the integration of high‐resolution satellite images and digital vector maps. A cross‐correlation matching method along the vertical line locus on the Ikonos images was deployed to recover building heights. The rational function models composed of rational polynomial coefficients were utilized to create a stereopair of the epipolar resampled Ikonos images. Building footprints from the digital maps were used for locating the vertical guideline along the building edges. The digital terrain model (DTM) was generated from the contour layer in the digital maps. The terrain height derived from the DTM at each foot of the buildings was used as the starting location for image matching. At a preset incremental value of height along the vertical guidelines derived from vertical line loci, an evaluation process that is based on the cross‐correlation matching of the images was carried out to test if the top of the building has reached where maximum correlation occurs. The accuracy of the reconstructed buildings was evaluated by the comparison with manually digitized 3D building data derived from aerial photographs.