OpenStreetMap'teki Bina Ayak İzi Verileri İçin Kalite Değerlendirmesi

Özet (abstract)

AbstractIn the past two years, several applications of generating three-dimensional (3D) buildings from OpenStreetMap (OSM) have been made available, for instance, OSM-3D, OSM2World, OSM Building, etc. In these projects, 3D buildings are reconstructed using the buildings' footprints and information about their attributes, which are documented as tags in OSM. Therefore, the quality of 3D buildings relies strongly on the quality of the building footprints data in OSM. This article is dedicated to a quality assessment of building footprints data in OSM for the German city of Munich, which is one of the most developed cities in OSM. The data are evaluated in terms of completeness, semantic accuracy, position accuracy, and shape accuracy by using building footprints in ATKIS (German Authority Topographic–Cartographic Information System) as reference data. The process contains three steps: finding correspondence between OSM and ATKIS data, calculating parameters of the four quality criteria, and statistical analysis. The results show that OSM footprint data in Munich have a high completeness and semantic accuracy. There is an offset of about four meters on average in terms of position accuracy. With respect to shape, OSM building footprints have a high similarity to those in ATKIS data. However, some architectural details are missing; hence, the OSM footprints can be regarded as a simplified version of those in ATKIS data.Keywords: OpenStreetMapquality assessmentbuilding footprintVGI FundingThis work is supported by NSFC (National Natural Science Foundation of China) projects No: 41101443 and 41201425, and the Klaus Tschira Foundation (KTS) in Germany.Notes1. The field of building name in AKTIS is 100% filled. However, only about 5.24% of the buildings in Munich have individual names, while most of them have a value of 'nameless' for the attribute field.

Yazarların özeti; kaynağından alınmıştır. International Journal of Geographical Information Systems, 2014 · DOI ↗