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

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.

On the Reliable Generation of 3D City Models from Open Data

“…The recently available satellite-derived elevation datasets provide an opportunity for data fusion by incorporating the elevation data with open-licensed 2D building data to generate 3D models. Indeed Bagheri et al generated LOD1 height values using multisensor and multimodal DEM fusion techniques-TanDEM-X DEM and Cartosat-1 DEM data were joined with OpenStreetMap building footprints [24]. This study confirmed that simple, prismatic building models can be reconstructed by combining OpenStreetMap building footprints with remote sensing-derived geodata.…”

“…To the authors' knowledge, this is the first attempt at combining OSM data with AW3D data to generate 3D models. We built upon previous studies that fused OSM with satellite-derived elevation data [24], however in our study, we provided a method to generate 3D models for both flat and undulated terrain using open data, which makes it feasible to replicate globally with any kind of terrain. Our study also demonstrated ways to increase the accuracy of the generated 3D city models using a sample high resolution DSM and DTM data.…”

“…Using OSM in combination with AW3D-30 DSM data has substantial potential for future scientific research due to the former's ever-growing size and the latter's global coverage [24,[34][35][36]47]. Studies have reported that there has been a considerable increase in OSM building data in recent years.…”

“…With a total area of 6340 km 2 , it is one of the fastest economically growing and most densely populated cities in East Asia. In 2014, it had a population of more than 24 million. The average elevation of the city varies between 3 to 5 m above mean sea level.…”

Multi-Source Geo-Information Fusion in Transition: A Summer 2019 Snapshot

“…The sources are the Istanbul Metropolitan authority, OSM, TomTom and Basarsoft (both of the latter are private navigation data). 3D Reconstruction [34]: prismatic 3D building models are built by adding height values to a 2D footprint (source: OSM). The heights are computed with two different approaches, depending on the availability of sources providing a sufficient high-resolution spatial coverage at an urban scale.…”