DocumentCode
1357479
Title
Digital surface models and building extraction: a comparison of IFSAR and LIDAR data
Author
Gamba, Paolo ; Houshmand, Bijan
Author_Institution
Dipartimento di Elettronica, Pavia Univ., Italy
Volume
38
Issue
4
fYear
2000
fDate
7/1/2000 12:00:00 AM
Firstpage
1959
Lastpage
1968
Abstract
The task of extracting significant built structure in digital surface models (DSM) is analyzed. The original data are obtained by means of interferometric SAR or LIDAR techniques and have different resolution and noise characteristics. This work aims to make a comparison of what (and how precisely) it is possible to detect and extract starting from these models, taking into account their differences but applying to them the same planar approximation approach. To this aim, data over Los Angeles and Denver is considered and evaluated. The results show that LIDAR data provide a better shape characterization of each building, and not simply because of their higher resolution. Indeed, less accurate results obtained starting from radar data are mainly due to shadowing/layover effects, which can be only partially corrected by means of the segmentation procedures. However, better results than those already presented in the literature could be achieved by using the IFSAR data correlation map
Keywords
cartography; feature extraction; geophysical signal processing; geophysical techniques; radar imaging; remote sensing by laser beam; remote sensing by radar; synthetic aperture radar; terrain mapping; IFSAR; LIDAR; building extraction; buildings; built structure; cartography; city; digital surface model; feature extraction; geophysical measurement technique; image processing; interferometric SAR; land surface; laser remote sensing; radar imaging; radar remote sensing; remote sensing; synthetic aperture radar; terrain mapping; town; urban area; Buildings; Data mining; Helium; Laboratories; Laser radar; Propulsion; Shadow mapping; Shape; Spatial resolution; Synthetic aperture radar interferometry;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing, IEEE Transactions on
Publisher
ieee
ISSN
0196-2892
Type
jour
DOI
10.1109/36.851777
Filename
851777
Link To Document