Please use this identifier to cite or link to this item: https://doi.org/10.1111/tgis.12186
Title: Automatic Update of Road Attributes by Mining GPS Tracks
Authors: van Winden K.
Biljecki F. 
van der Spek S.
Issue Date: 2016
Publisher: Blackwell Publishing Ltd
Citation: van Winden K., Biljecki F., van der Spek S. (2016). Automatic Update of Road Attributes by Mining GPS Tracks. Transactions in GIS 20 (5) : 664-683. ScholarBank@NUS Repository. https://doi.org/10.1111/tgis.12186
Rights: Attribution-NonCommercial 4.0 International
Abstract: Despite advances in cartography, mapping is still a costly process which involves a substantial amount of manual work. This article presents a method for automatically deriving road attributes by analyzing and mining movement trajectories (e.g. GPS tracks). We have investigated the automatic extraction of eight road attributes: directionality, speed limit, number of lanes, access, average speed, congestion, importance, and geometric offset; and we have developed a supervised classification method (decision tree) to infer them. The extraction of most of these attributes has not been investigated previously. We have implemented our method in a software prototype and we automatically update the OpenStreetMap (OSM) dataset of the Netherlands, increasing its level of completeness. The validation of the classification shows variable levels of accuracy, e.g. whether a road is a one- or a two-way road is classified with an accuracy of 99%, and the accuracy for the speed limit is 69%. When taking into account speed limits that are one step away (e.g. 60 km/h instead of the classified 50 km/h) the classification increases to 95%, which might be acceptable in some use-cases. We mitigate this with a hierarchical code list of attributes. © 2016 John Wiley & Sons Ltd
Source Title: Transactions in GIS
URI: http://scholarbank.nus.edu.sg/handle/10635/148044
ISSN: 13611682
DOI: 10.1111/tgis.12186
Rights: Attribution-NonCommercial 4.0 International
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