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ISPRS Int. J. Geo-Inf. 2017, 6(2), 45; doi:10.3390/ijgi6020045

A Road Map Refinement Method Using Delaunay Triangulation for Big Trace Data

State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
Shenzhen Key Laboratory of Spatial Smart Sensing and Services, College of Civil Engineering, Shenzhen University, Shenzhen 518060, China
Author to whom correspondence should be addressed.
Received: 28 October 2016 / Accepted: 13 February 2017 / Published: 15 February 2017
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With the rapid development of urban transportation, people urgently need high-precision and up-to-date road maps. At the same time, people themselves are an important source of road information for detailed map construction, as they can detect real-world road surfaces with GPS devices in the course of their everyday life. Big trace data makes it possible and provides a great opportunity to extract and refine road maps at relatively low cost. In this paper, a new refinement method is proposed for incremental road map construction using big trace data, employing Delaunay triangulation for higher accuracy during the GPS trace stream fusion process. An experiment and evaluation were carried out on the GPS traces collected by taxis in Wuhan, China. The results show that the proposed method is practical and improves upon existing incremental methods in terms of accuracy. View Full-Text
Keywords: big trace data; road map refinement; trace data fusion; Delaunay triangulation big trace data; road map refinement; trace data fusion; Delaunay triangulation

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Tang, L.; Ren, C.; Liu, Z.; Li, Q. A Road Map Refinement Method Using Delaunay Triangulation for Big Trace Data. ISPRS Int. J. Geo-Inf. 2017, 6, 45.

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