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Open AccessFeature PaperArticle

Automatic 3-D Building Model Reconstruction from Very High Resolution Stereo Satellite Imagery

1
Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), 82234 Wessling, Germany
2
Institute for Computer Graphics and Vision, Graz University of Technology, 8010 Graz, Austria
3
Institute for Applied Computer Science, Bundeswehr University, 85577 Neubiberg, Germany
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(14), 1660; https://doi.org/10.3390/rs11141660
Received: 27 May 2019 / Revised: 22 June 2019 / Accepted: 9 July 2019 / Published: 11 July 2019
(This article belongs to the Special Issue 3D Reconstruction Based on Aerial and Satellite Imagery)
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Abstract

Recent advances in the availability of very high-resolution (VHR) satellite data together with efficient data acquisition and large area coverage have led to an upward trend in their applications for automatic 3-D building model reconstruction which require large-scale and frequent updates, such as disaster monitoring and urban management. Digital Surface Models (DSMs) generated from stereo satellite imagery suffer from mismatches, missing values, or blunders, resulting in rough building shape representations. To handle 3-D building model reconstruction using such low-quality DSMs, we propose a novel automatic multistage hybrid method using DSMs together with orthorectified panchromatic (PAN) and pansharpened data (PS) of multispectral (MS) satellite imagery. The algorithm consists of multiple steps including building boundary extraction and decomposition, image-based roof type classification, and initial roof parameter computation which are prior knowledge for the 3-D model fitting step. To fit 3-D models to the normalized DSM (nDSM) and to select the best one, a parameter optimization method based on exhaustive search is used sequentially in 2-D and 3-D. Finally, the neighboring building models in a building block are intersected to reconstruct the 3-D model of connecting roofs. All corresponding experiments are conducted on a dataset including four different areas of Munich city containing 208 buildings with different degrees of complexity. The results are evaluated both qualitatively and quantitatively. According to the results, the proposed approach can reliably reconstruct 3-D building models, even the complex ones with several inner yards and multiple orientations. Furthermore, the proposed approach provides a high level of automation by limiting the number of primitive roof types and by performing automatic parameter initialization. View Full-Text
Keywords: automatic methods; 3-D building model reconstruction; digital surface model; exhaustive search; hybrid methods; satellite imagery automatic methods; 3-D building model reconstruction; digital surface model; exhaustive search; hybrid methods; satellite imagery
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Partovi, T.; Fraundorfer, F.; Bahmanyar, R.; Huang, H.; Reinartz, P. Automatic 3-D Building Model Reconstruction from Very High Resolution Stereo Satellite Imagery. Remote Sens. 2019, 11, 1660.

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