Abstract
Volunteered Geographic Information (VGI) such as data derived from the OpenStreetMap (OSM) project is a popular data source for freely available geographic data. Normally, untrained contributors gather these data. This fact is frequently a cause of concern regarding the quality and usability of such data. In this study, the quality of OSM land use and land cover (LULC) data is investigated for an area in southern Germany. Two spatial data quality elements, thematic accuracy and completeness are addressed by comparing the OSM data with an authoritative German reference dataset. The results show that the kappa value indicates a substantial agreement between the OSM and the authoritative dataset. Nonetheless, for our study region, there are clear variations between the LULC classes. Forest covers a large area and shows both a high OSM completeness (97.6%) and correctness (95.1%). In contrast, farmland also covers a large area, but for this class OSM shows a low completeness value (45.9%) due to unmapped areas. Additionally, the results indicate that a high population density, as present in urbanized areas, seems to denote a higher strength of agreement between OSM and the DLM (Digital Landscape Model). However, a low population density does not necessarily imply a low strength of agreement.
Highlights
OpenStreetMap (OSM) is a collaborative mapping project founded in London (UK) in 2004
This study addresses the quality of OSM land use and land cover data by comparing the data with the authoritative data set ATKIS Base DLM version 6.0
Completeness is an element of spatial data quality [38] and this study addresses the completeness of objects
Summary
OpenStreetMap (OSM) is a collaborative mapping project founded in London (UK) in 2004. Private citizens create freely accessible spatial data, which can present an alternative to official data [1]. User-generated or crowdsourced geoinformation, known as Volunteered Geographic Information (VGI) [4], can enhance geographic data and the knowledge about or understanding of the environment. Concerns about the quality and value of these data exist [5]. The contributors of VGI are non-experts; they may be unqualified, untrained volunteers focusing on their fields of interest, and in case of OSM, the users can modify or edit features immediately after registration [1,5,6,7]
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