Using OSM for LBS – An Analysis of Changes to Attributes of Spatial Objects

Mooney, Peter; Corcoran, Padraig

doi:10.1007/978-3-642-24198-7_11

Cited by 14 publications

(9 citation statements)

References 24 publications

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“…This will form a useful basis for future work to investigate if this behaviour extends to other OSM regions and communities. The uncertainty introduced by frequent changes to "name" or "highway" attributes has implications for the development of gazetteers from OSM and location-based services (LBS) which will need to be evaluated [56]. In Over et al [8] the authors comment that the quality control of OSM differs fundamentally from professionally edited maps.…”

Section: Discussionmentioning

confidence: 99%

Characteristics of Heavily Edited Objects in OpenStreetMap

2012

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This paper describes the results of an analysis of the OpenStreetMap (OSM) database for the United Kingdom (UK) and Ireland (correct to April 2011). 15; 640 OSM ways (polygons and polylines), resulting in 316; 949 unique versions of these objects, were extracted and analysed from the OSM database for the UK and Ireland. In our analysis we only considered “heavily edited” objects in OSM: objects which have been edited 15 or more times. Our results show that there is no strong relationship between increasing numbers of contributors to a given object and the number of tags (metadata) assigned to it. 87% of contributions/edits to these objects are performed by 11% of the total 4128 contributors. In 79% of edits additional spatial data (nodes) are added to objects. The results in this paper do not attempt to evaluate the OSM data as good/poor quality but rather informs potential consumers of OSM data that the data itself is changing over time. In developing a better understanding of the characteristics of “heavily edited” objects there may be opportunities to use historical analysis in working towards quality indicators for OSM in the future

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Section: Discussionmentioning

confidence: 99%

Characteristics of Heavily Edited Objects in OpenStreetMap

2012

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“…Others again describe it as Collaborative Mapping [18] or the Wikification of GIS [19]. The successful development of user generated content in recent years had an increasing impact on a variety of research fields and particularly OSM has been the focus of many new developments such as routing applications, 3D city models and Location-Based Services (LBS) [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007–2011

2011

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Abstract:The OpenStreetMap (OSM) project is a prime example in the field of Volunteered Geographic Information (VGI). Worldwide, several hundred thousand people are currently contributing information to the -free‖ geodatabase. However, the data contributions show a geographically heterogeneous pattern around the globe. Germany counts as one of the most active countries in OSM; thus, the German street network has undergone an extensive development in recent years. The question that remains is this: How does the street network perform in a relative comparison with a commercial dataset? By means of a variety of studies, we show that the difference between the OSM street network for car navigation in Germany and a comparable proprietary dataset was only 9% in June 2011. The results of our analysis regarding the entire street network showed that OSM even exceeds the information provided by the proprietary dataset by 27%. Further analyses show on what scale errors can be reckoned with in the topology of the street network, and the completeness of turn restrictions and street name information. In addition to the analyses conducted over the past few years, projections have additionally been made about the point in time by which the OSM dataset for Germany can be considered -complete‖ in relative comparison to a commercial dataset. OPEN ACCESSFuture Internet 2012, 4 2

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“…OSM data represent physical features (objects) on the ground, and their tags (i.e., labels) are used to describe the objects (i.e., class description). The OSM data include a variety of physical feature types, with land use, natural features, waterways, amenities, and highways being the most commonly represented [51]. Feature descriptions can be found on the OSM wiki page (https://wiki.openstreetmap.org/wiki/Map_Features).…”

Section: The Osm Dataset and History Filementioning

confidence: 99%

The Value of OpenStreetMap Historical Contributions as a Source of Sampling Data for Multi-Temporal Land Use/Cover Maps

Viana

Encalada

Rocha

2019

IJGI

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OpenStreetMap (OSM) is a free, open-access Volunteered geographic information (VGI) platform that has been widely used over the last decade as a source for Land Use Land Cover (LULC) mapping and visualization. However, it is known that the spatial coverage and accuracy of OSM data are not evenly distributed across all regions, with urban areas being likelier to have promising contributions (in both quantity and quality) than rural areas. The present study used OSM data history to generate LULC datasets with one-year timeframes as a way to support regional and rural multi-temporal LULC mapping. We evaluated the degree to which the different OSM datasets agreed with two existing reference datasets (CORINE Land Cover and the official Portuguese Land Cover Map). We also evaluated whether our OSM dataset was of sufficiently high quality (in terms of both completeness accuracy and thematic accuracy) to be used as a sampling data source for multi-temporal LULC maps. In addition, we used the near boundary tag accuracy criterion to assesses the fitness of the OSM data for producing training samples, with promising results. For each annual dataset, the completeness ratio of the coverage area for the selected study area was low. Nevertheless, we found high thematic accuracy values (ranged from 77.3% to 91.9%). Additionally, the training samples thematic accuracy improved as they moved away from the features’ boundaries. Features with larger areas (> 10 ha), e.g., Agriculture and Forest, had a steadily positive correlation between training samples accuracy and distance to feature boundaries

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Using OSM for LBS – An Analysis of Changes to Attributes of Spatial Objects

Cited by 14 publications

References 24 publications

Characteristics of Heavily Edited Objects in OpenStreetMap

Characteristics of Heavily Edited Objects in OpenStreetMap

The Street Network Evolution of Crowdsourced Maps: OpenStreetMap in Germany 2007–2011

The Value of OpenStreetMap Historical Contributions as a Source of Sampling Data for Multi-Temporal Land Use/Cover Maps

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