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Abstract
<p><strong>Abstract.</strong> A significant advantage of OpenStreetMap data is its up-to-dateness. However, for rural and city planning, it is also of importance to access historical data and to compare the changes between new and old versions of the same area. This paper first introduces into a differentiated classification of changes on OpenStreetMap data sets. Then a methodology for an automated database-supported analysis of changes is presented. Beyond the information already provided from the OpenStreetMap server, we present a more detailed analysis with derived information. Based on this approach it is possible to identify objects with attributive or geometric changes and to find out how they exactly differ from their previous versions. The analysis shows in which regions mappers were active during a certain time interval. Furthermore, a time based approach based on various parameters to determine the quality of the data is presented. It provides a guideline of data quality and works without any reference data. Therefore, an indication about the development of OpenStreetMap in terms of completeness and correctness of the data in different regions is given. Finally, a conclusion and an outlook on open research questions are presented.</p>
Document type: Article
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The different versions of the original document can be found in:
- https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W5/535/2019 under the license https://creativecommons.org/licenses/by/4.0/deed.de
- https://publikationen.bibliothek.kit.edu/1000096306/33952148,
- https://doi.org/10.5445/IR/1000096306 under the license cc-by
- https://doaj.org/toc/2194-9042,
- https://doaj.org/toc/2194-9050 under the license https://creativecommons.org/licenses/by/4.0/
- https://ui.adsabs.harvard.edu/abs/2019ISPAn42W5..535M/abstract,
- https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-2-W5/535/2019,
- https://publikationen.bibliothek.kit.edu/1000096306/33952148,
- https://publikationen.bibliothek.kit.edu/1000096306,
- https://academic.microsoft.com/#/detail/2947230508
DOIS: 10.5445/ir/1000096306 10.5194/isprs-annals-iv-2-w5-535-2019
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Published on 01/01/2019
Volume 2019, 2019
DOI: 10.5445/ir/1000096306
Licence: Other
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