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Title
Cross-track satellite stereo for 3D modelling of urban areas
AuthorKrauß, Thomas ; DAngelo, Pablo ; Wendt, Lorenz
Published in
European Journal of Remote Sensing, London, 2018, Vol. 2018, page 1-10
PublishedLondon : Taylor & Francis, 2018
LanguageEnglish
Document typeJournal Article
Keywords (EN)Photogrammetry / digital elevation model / satellite image / cross stereo / stereo processing / remote sensing
ISSN2279-7254
URNurn:nbn:at:at-ubs:3-10977 Persistent Identifier (URN)
DOI10.1080/22797254.2018.1551069 
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 The work is publicly available
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Cross-track satellite stereo for 3D modelling of urban areas [2.13 mb]
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Abstract (English)

Stereo imagery from very high-resolution satellite series can be used to create high-resolution digital surface models (DSMs) with sub-meter spatial resolution. Especially when in-orbit tri-stereo acquisitions are available as provided by the Pléiades constellation, buildings can be reconstructed well even in dense city centres. Unfortunately, such high-quality stereo data are often not available in the image archives and, thus, need to be newly acquired in most cases, leading to long delays and high cost. Especially for rapid mapping or crisis-response applications, high-resolution DSMs would be helpful for tasks such as city modelling and ultimately population estimation. In this work, we test the feasibility of producing DSMs by pairing two archive images, which were not acquired on the same day, in the same orbit or by the same satellite. We tested this approach for 14 images from Port-au-Prince, Haiti, and 12 images from Salzburg, Austria, from which we calculated a total of 136 DSMs. These were evaluated against Lidar DSMs. The resulting DSMs reach a completeness of up to 60%, and partly Median Absolute Deviation values comparable to in-orbit stereo pairs. For best results, the stereo convergence angle should be between 5 and 15, and the difference in sun angles between the two images should be below 2530.

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CC-BY-License (4.0)Creative Commons Attribution 4.0 International License