Header

UZH-Logo

Maintenance Infos

Enrichment of OpenStreetMap data completeness with sidewalk geometries using data mining techniques


Mobasheri, Amin; Huang, Haosheng; Degrossi, Lívia; Zipf, Alexander (2018). Enrichment of OpenStreetMap data completeness with sidewalk geometries using data mining techniques. Sensors, 18(2):509.

Abstract

Tailored routing and navigation services utilized by wheelchair users require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is not present in current versions of crowdsourced mapping databases including OpenStreetMap. CAP4Access European project aimed to use (and enrich) OpenStreetMap for making it fit to the purpose of wheelchair routing. In this respect, this study presents a modified methodology based on data mining techniques for constructing sidewalk geometries using multiple GPS traces collected by wheelchair users during an urban travel experiment. The derived sidewalk geometries can be used to enrich OpenStreetMap to support wheelchair routing. The proposed method was applied to a case study in Heidelberg, Germany. The constructed sidewalk geometries were compared to an official reference dataset (“ground truth dataset”). The case study shows that the constructed sidewalk network overlays with 96% of the official reference dataset. Furthermore, in terms of positional accuracy, a low Root Mean Square Error (RMSE) value (0.93 m) is achieved. The article presents our discussion on the results as well as the conclusion and future research directions.

Abstract

Tailored routing and navigation services utilized by wheelchair users require certain information about sidewalk geometries and their attributes to execute efficiently. Except some minor regions/cities, such detailed information is not present in current versions of crowdsourced mapping databases including OpenStreetMap. CAP4Access European project aimed to use (and enrich) OpenStreetMap for making it fit to the purpose of wheelchair routing. In this respect, this study presents a modified methodology based on data mining techniques for constructing sidewalk geometries using multiple GPS traces collected by wheelchair users during an urban travel experiment. The derived sidewalk geometries can be used to enrich OpenStreetMap to support wheelchair routing. The proposed method was applied to a case study in Heidelberg, Germany. The constructed sidewalk geometries were compared to an official reference dataset (“ground truth dataset”). The case study shows that the constructed sidewalk network overlays with 96% of the official reference dataset. Furthermore, in terms of positional accuracy, a low Root Mean Square Error (RMSE) value (0.93 m) is achieved. The article presents our discussion on the results as well as the conclusion and future research directions.

Statistics

Citations

Dimensions.ai Metrics
7 citations in Web of Science®
7 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

21 downloads since deposited on 18 Dec 2018
21 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Language:English
Date:8 February 2018
Deposited On:18 Dec 2018 16:12
Last Modified:18 Dec 2018 16:13
Publisher:MDPI Publishing
ISSN:1424-8220
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.3390/s18020509

Download

Download PDF  'Enrichment of OpenStreetMap data completeness with sidewalk geometries using data mining techniques'.
Preview
Content: Published Version
Language: English
Filetype: PDF
Size: 3MB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)