The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLIII-B4-2020
25 Aug 2020
 | 25 Aug 2020


Y. Wang, H. Fan, and W. Jiao

Keywords: OpenStreetMap, Volunteered geographic information (VGI), image rectification, image matching, data enrichment

Abstract. To reconstruct 3D building models, building footprints and heights are essential information. From OpenStreetMap (OSM), we can easily obtain footprints. However, building height is usually missing. In order to yield the height information of building in OSM, this paper proposes a geometric method to estimate building height from geotagged photographs. This method explores the geometric relationship between the perspective centre of geotagged photos and buildings. Through matching photos and OSM, building height can be estimated according to the ratio of height to width of building. The proposed method can be divided into three parts. First, automatic geometric correction of photos is realized by using vanishing point tracking. After that, a semi-automatic scene search method is proposed to match the geotagged photograph and OSM. In this step, geographic coordinates of photos are used to locate a photographic scene. According to the edge of the building in the photos, corresponding footprints in OSM can be found. Finally, based on the length of the associated edge in the building footprint in OSM, the height of building can be calculated. Using Flickr photos and OSM in London, we experiment with the proposed method. The robustness of the geometric model has been verified. Experiments show that the proposed method is pertinent as the estimated height has expressed a proper ratio with its width, which is the same as the corrected photos. In particular for automatic geometric correction, which can achieve the same good results as the correction of manual operation.