Abstract
The use of accurate 3D spatial network models can enable substantial improvements in vehicle routing. Notably, such models enable eco-routing, which reduces the environmental impact of transportation. We propose a novel filtering and lifting framework that augments a standard 2D spatial network model with elevation information extracted from massive aerial laser scan data and thus yields an accurate 3D model. We present a filtering technique that is capable of pruning irrelevant laser scan points in a single pass, but assumes that the 2D network fits in internal memory and that the points are appropriately sorted. We also provide an external-memory filtering technique that makes no such assumptions. During lifting, a triangulated irregular network (TIN) surface is constructed from the remaining points. The 2D network is projected onto the TIN, and a 3D network is constructed by means of interpolation. We report on a large-scale empirical study that offers insight into the accuracy, efficiency, and scalability properties of the framework.
Originalsprog | Engelsk |
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Artikelnummer | 6569130 |
Tidsskrift | Proceedings - IEEE International Conference on Mobile Data Management |
Vol/bind | 1 |
Sider (fra-til) | 137-146 |
Antal sider | 10 |
ISSN | 1551-6245 |
DOI | |
Status | Udgivet - 11 sep. 2013 |
Begivenhed | 14th International Conference on Mobile Data Management, MDM 2013 - Milan, Italien Varighed: 3 jun. 2013 → 6 jun. 2013 |
Konference
Konference | 14th International Conference on Mobile Data Management, MDM 2013 |
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Land/Område | Italien |
By | Milan |
Periode | 03/06/2013 → 06/06/2013 |
Sponsor | IEEE, IEEE Computer Society, University of Milan, ST life.augmented, IBM |