Problems and limitations of satellite image orientation for determination of height models

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Jacobsen, K.: Problems and limitations of satellite image orientation for determination of height models. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 42 (2017), Nr. 1W1, S. 257-264. DOI: https://doi.org/10.5194/isprs-archives-XLII-1-W1-257-2017

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/1730

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Abstract: 
The usual satellite image orientation is based on bias corrected rational polynomial coefficients (RPC). The RPC are describing the direct sensor orientation of the satellite images. The locations of the projection centres today are without problems, but an accuracy limit is caused by the attitudes. Very high resolution satellites today are very agile, able to change the pointed area over 200km within 10 to 11 seconds. The corresponding fast attitude acceleration of the satellite may cause a jitter which cannot be expressed by the third order RPC, even if it is recorded by the gyros. Only a correction of the image geometry may help, but usually this will not be done. The first indication of jitter problems is shown by systematic errors of the y-parallaxes (py) for the intersection of corresponding points during the computation of ground coordinates. These y-parallaxes have a limited influence to the ground coordinates, but similar problems can be expected for the x-parallaxes, determining directly the object height. Systematic y-parallaxes are shown for Ziyuan-3 (ZY3), WorldView-2 (WV2), Pleiades, Cartosat-1, IKONOS and GeoEye. Some of them have clear jitter effects. In addition linear trends of py can be seen. Linear trends in py and tilts in of computed height models may be caused by limited accuracy of the attitude registration, but also by bias correction with affinity transformation. The bias correction is based on ground control points (GCPs). The accuracy of the GCPs usually does not cause some limitations but the identification of the GCPs in the images may be difficult. With 2-dimensional bias corrected RPC-orientation by affinity transformation tilts of the generated height models may be caused, but due to large affine image deformations some satellites, as Cartosat-1, have to be handled with bias correction by affinity transformation. Instead of a 2-dimensional RPC-orientation also a 3-dimensional orientation is possible, respecting the object height more as by 2-dimensional orientation. The 3-dimensional orientation showed advantages for orientation based on a limited number of GCPs, but in case of poor GCP distribution it may cause also negative effects. For some of the used satellites the bias correction by affinity transformation showed advantages, but for some other the bias correction by shift was leading to a better levelling of the generated height models, even if the root mean square (RMS) differences at the GCPs were larger as for bias correction by affinity transformation. The generated height models can be analyzed and corrected with reference height models. For the used data sets accurate reference height models are available, but an analysis and correction with the free of charge available SRTM digital surface model (DSM) or ALOS World 3D (AW3D30) is also possible and leads to similar results. The comparison of the generated height models with the reference DSM shows some height undulations, but the major accuracy influence is caused by tilts of the height models. Some height model undulations reach up to 50% of the ground sampling distance (GSD), this is not negligible but it cannot be seen not so much at the standard deviations of the height. In any case an improvement of the generated height models is possible with reference height models. If such corrections are applied it compensates possible negative effects of the type of bias correction or 2-dimensional orientations against 3-dimensional handling.
License of this version: CC BY 3.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2017
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
total perc.
1 image of flag of Germany Germany 92 22.38%
2 image of flag of United States United States 62 15.09%
3 image of flag of China China 46 11.19%
4 image of flag of India India 31 7.54%
5 image of flag of United Kingdom United Kingdom 22 5.35%
6 image of flag of No geo information available No geo information available 12 2.92%
7 image of flag of Canada Canada 9 2.19%
8 image of flag of Australia Australia 9 2.19%
9 image of flag of Japan Japan 7 1.70%
10 image of flag of Italy Italy 7 1.70%
    other countries 114 27.74%

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