Résumé des résultats (Abstract)
(Allemand)
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The objective of this project is to develop methods and operational software for:
- The quality evaluation of Digital Elevation Models (DEMs) and especially generation of improved
DEMs based on the fusion of DEMs produced by various technologies (optical images, Synthetic
Aperture Radar (SAR) interferometry, laser scanning etc.). The quality evaluation of single DEMs is
important as such data are very widely used for the most diverse applications. However, the
accuracy of these datasets is often unknown, inhomogeneous, while almost always for their quality
description only a global measure (root mean square error, standard deviation) is given. The fusion
of DEMs is even more important, as it allows generation of new DEMs with higher point density,
higher accuracy and better currency. Furthermore, fusion can help to fill-in gaps (like in the SRTM
global DEM) or extend the area coverage of DEMs. A secondary aim within this objective is the
detection of above-terrain objects (e.g. buildings, trees), which will facilitate the fusion of Digital
Terrain Models (DTMs) with Digital Surface Models (DSMs) This is necessary as some DEM
generation technologies (laser scanning, L-band and P-band SAR interferometry) can penetrate
tree canopy and measure the terrain, while others like C- and X-band SAR interferometry and
automated matching of optical images measure more or less the top visible surface, i.e. the tree
canopy. By detecting above-terrain objects, they can be excluded from the fusion process, which
should be performed using only the common information describing the terrain.
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Résumé des résultats (Abstract)
(Anglais)
|
The objective of this project is to develop methods and operational software for:
- The quality evaluation of Digital Elevation Models (DEMs) and especially generation of improved
DEMs based on the fusion of DEMs produced by various technologies (optical images, Synthetic
Aperture Radar (SAR) interferometry, laser scanning etc.). The quality evaluation of single DEMs is
important as such data are very widely used for the most diverse applications. However, the
accuracy of these datasets is often unknown, inhomogeneous, while almost always for their quality
description only a global measure (root mean square error, standard deviation) is given. The fusion
of DEMs is even more important, as it allows generation of new DEMs with higher point density,
higher accuracy and better currency. Furthermore, fusion can help to fill-in gaps (like in the SRTM
global DEM) or extend the area coverage of DEMs. A secondary aim within this objective is the
detection of above-terrain objects (e.g. buildings, trees), which will facilitate the fusion of Digital
Terrain Models (DTMs) with Digital Surface Models (DSMs) This is necessary as some DEM
generation technologies (laser scanning, L-band and P-band SAR interferometry) can penetrate
tree canopy and measure the terrain, while others like C- and X-band SAR interferometry and
automated matching of optical images measure more or less the top visible surface, i.e. the tree
canopy. By detecting above-terrain objects, they can be excluded from the fusion process, which
should be performed using only the common information describing the terrain.
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