ESTIMATING HEIGHTS OF BUILDINGS FROM GEOTAGGED PHOTOS FOR DATA ENRICHMENT ON OPENSTREETMAP

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...

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Main Authors: Y. Wang, H. Fan, W. Jiao
Format: Article
Language:English
Published: Copernicus Publications 2020-08-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B4-2020/631/2020/isprs-archives-XLIII-B4-2020-631-2020.pdf
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author Y. Wang
Y. Wang
H. Fan
W. Jiao
W. Jiao
author_facet Y. Wang
Y. Wang
H. Fan
W. Jiao
W. Jiao
author_sort Y. Wang
collection DOAJ
description 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.
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spelling doaj.art-782bd3d03d4a4a11b12ed993efac35402022-12-22T01:58:24ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B4-202063163710.5194/isprs-archives-XLIII-B4-2020-631-2020ESTIMATING HEIGHTS OF BUILDINGS FROM GEOTAGGED PHOTOS FOR DATA ENRICHMENT ON OPENSTREETMAPY. Wang0Y. Wang1H. Fan2W. Jiao3W. Jiao4LIESMARS, Wuhan Universi ty, Wuhan, ChinaDepartment of Civil and Environmental Engineering, Faculty of Engineering, Norwegian University of Science and Technology, Trondheim, NorwayDepartment of Civil and Environmental Engineering, Faculty of Engineering, Norwegian University of Science and Technology, Trondheim, NorwayDepartment of Civil and Environmental Engineering, Faculty of Engineering, Norwegian University of Science and Technology, Trondheim, NorwaySchool of Remote Sensing and Information Engineering, Wuhan University, Wuhan, ChinaTo 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.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B4-2020/631/2020/isprs-archives-XLIII-B4-2020-631-2020.pdf
spellingShingle Y. Wang
Y. Wang
H. Fan
W. Jiao
W. Jiao
ESTIMATING HEIGHTS OF BUILDINGS FROM GEOTAGGED PHOTOS FOR DATA ENRICHMENT ON OPENSTREETMAP
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title ESTIMATING HEIGHTS OF BUILDINGS FROM GEOTAGGED PHOTOS FOR DATA ENRICHMENT ON OPENSTREETMAP
title_full ESTIMATING HEIGHTS OF BUILDINGS FROM GEOTAGGED PHOTOS FOR DATA ENRICHMENT ON OPENSTREETMAP
title_fullStr ESTIMATING HEIGHTS OF BUILDINGS FROM GEOTAGGED PHOTOS FOR DATA ENRICHMENT ON OPENSTREETMAP
title_full_unstemmed ESTIMATING HEIGHTS OF BUILDINGS FROM GEOTAGGED PHOTOS FOR DATA ENRICHMENT ON OPENSTREETMAP
title_short ESTIMATING HEIGHTS OF BUILDINGS FROM GEOTAGGED PHOTOS FOR DATA ENRICHMENT ON OPENSTREETMAP
title_sort estimating heights of buildings from geotagged photos for data enrichment on openstreetmap
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B4-2020/631/2020/isprs-archives-XLIII-B4-2020-631-2020.pdf
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