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Fusion of Multi-Sensor-Derived Heights and OSM-Derived Building Footprints for Urban 3D Reconstruction

1
Signal Processing in Earth Observation, Technical University of Munich, 80333 Munich, Germany
2
Remote Sensing Technology Institute, German Aerospace Center, 82234 Wessling, Germany
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(4), 193; https://doi.org/10.3390/ijgi8040193
Received: 28 February 2019 / Revised: 5 April 2019 / Accepted: 9 April 2019 / Published: 18 April 2019
(This article belongs to the Special Issue Multi-Source Geoinformation Fusion)
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Abstract

So-called prismatic 3D building models, following the level-of-detail (LOD) 1 of the OGC City Geography Markup Language (CityGML) standard, are usually generated automatically by combining building footprints with height values. Typically, high-resolution digital elevation models (DEMs) or dense LiDAR point clouds are used to generate these building models. However, high-resolution LiDAR data are usually not available with extensive coverage, whereas globally available DEM data are often not detailed and accurate enough to provide sufficient input to the modeling of individual buildings. Therefore, this paper investigates the possibility of generating LOD1 building models from both volunteered geographic information (VGI) in the form of OpenStreetMap data and remote sensing-derived geodata improved by multi-sensor and multi-modal DEM fusion techniques or produced by synthetic aperture radar (SAR)-optical stereogrammetry. The results of this study show several things: First, it can be seen that the height information resulting from data fusion is of higher quality than the original data sources. Secondly, the study confirms that simple, prismatic building models can be reconstructed by combining OpenStreetMap building footprints and easily accessible, remote sensing-derived geodata, indicating the potential of application on extensive areas. The building models were created under the assumption of flat terrain at a constant height, which is valid in the selected study area. View Full-Text
Keywords: 3D building reconstruction; building model; OpenStreetMap (OSM); building foot prints; multi-sensor fusion; digital elevation models (DEM); LOD1; SAR-optical stereogrammetry 3D building reconstruction; building model; OpenStreetMap (OSM); building foot prints; multi-sensor fusion; digital elevation models (DEM); LOD1; SAR-optical stereogrammetry
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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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Bagheri, H.; Schmitt, M.; Zhu, X. Fusion of Multi-Sensor-Derived Heights and OSM-Derived Building Footprints for Urban 3D Reconstruction. ISPRS Int. J. Geo-Inf. 2019, 8, 193.

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