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TitleDTM generation from IKONOS in-track stereo images using a 3D physical model
DownloadDownloads (Preprint)
LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorToutin, T
SourcePhotogrammetric Engineering and Remote Sensing vol. 70, no. 6, 2004 p. 695-702,
Alt SeriesEarth Sciences Sector, Contribution Series 20043182
PublisherAmerican Society for Photogrammetry and Remote Sensing
Mediapaper; on-line; digital
File formatpdf
Subjectsgeophysics; remote sensing; radar imagery; mapping techniques; modelling; Digital Elevation Model (DEM)
Illustrationssatellite images; histograms; flow charts; tables; graphs
AbstractA digital elevation model (DEM) extracted from IKONOS in-track stereo images using a 3D physical model developed at the Canada Centre for Remote Sensing, Natural Resources Canada was evaluated. About 10 accurate ground control points were enough to set-up the stereo photogrammetric bundle adjustment: the 3D physical model was stable over the full stereo model and filtered out the errors of the input data. The DEM was then generated using an area-based multi-scale image matching method and 3D semi-automatic editing tools and then compared to lidar elevation data with to 0.2-m accuracy. Since the DEM is in fact a digital terrain surface model where the elevation of land covers (trees, houses) is included, the accuracy varies depending on the land cover types. Using 3D visual classification of the stereo IKONOS images, different classes (forests, residential, bare soil, lakes) were generated to take into account the elevation of the surface (natural and human-made) in the accuracy evaluation. A general error of 6.4 m (68% confidence level, LE68) was achieved over the full area, but the best results (1.5 m LE68) were normally obtained for bare soil and lake areas. 5-m contour lines could thus be derived, compliant with the highest topographic standard. On the other hand, LE68 of 2.5 m to 6.6 m were obtained depending on the land cover types and its surface elevation. For the residential areas, the surface elevation did not affect the errors very much (2.5-m LE68) when compared to bare soil/lakes results because 1-2-storey houses were sparse in the test area. Since the images were acquired in wintertime and the lidar data in summertime, elevation errors (LE68 and bias) also depended on the type of forests (deciduous, coniferous, mixed, sparse). An evaluation based on terrain slope and azimuth showed that the DEM error was linearly correlated with the slopes and that the elevations in sun-facing slopes were 1-m more accurate than the elevations in slopes facing away from the sun.

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