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TitleError Tracking of Radargrammetric DEM from RADARSAT Images
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LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorToutin, Th
SourceIEEE Transactions on Geoscience and Remote Sensing (Institute of Electrical and Electronics Engineers) vol. 37, issue 5, 1999 p. 2227-2238, https://doi.org/10.1109/36.789619
Year1999
Alt SeriesEarth Sciences Sector, Contribution Series 20042646
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
Subjectsremote sensing; RADARSAT; SAR imagery; radargrammetry; algorithms; ground control points (GCP); image matching; computer assisted visual matching; automatic matching
Illustrationsdiagrams; satellite imagery; tables; graphs
AbstractIn the 1960's, stereoscopic methods were first applied to radar images to derive ground elevation. Unfortunately, research uncovered contradictions between error propagation theory and practical results, particularly over high relief areas. These contradictions combined with the lack of stereo radar pairs led to the decline of radargrammetry. The launch in 1995 of Canada's first earth observation satellite, RADARSAT with its various operating modes and specific geometric characteristics has turned the tide. The error propagation of the radargrammetric DEM generated from different RADARSAT stereo configurations is then quantitatively evaluated along the full processing chain (stereo model set-up with GCPs, image matching and 3D intersection). Two matching algorithms are used: automatic and computer-assisted visual matching. The GCP collection method using stereoscopic plotting is a requisite to achieve the best results for the stereo model and DEM. The automatic matching gives slightly better results than the computer-assisted visual matching, except when the radiometric disparities in the stereo images are too large. Since the geometric advantage (not involved in the automatic matching) can compensate for the radiometric disadvantage, visual matching, which combines both aspects, is a better algorithm in these conditions. Consequently, these two algorithms can be used in two-step method to generate the best DEM whatever the stereo configuration. Since the relief is an important parameter in the final accuracy, geometric versus radiometric disparity tradeoffs and general guidelines are suggested for selecting RADARSAT stereo pairs for DEM generation as a function of terrain relief.
GEOSCAN ID219448

 
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