@inproceedings{68a8349d3f1b41ef91ae7143abbb6b2a,
title = "Aerial laser scanning and imagery data fusion for road detection in city scale",
abstract = "This paper presents a workflow including a novel algorithm for road detection from dense LiDAR fused with high-resolution aerial imagery data. Using a supervised machine learning approach point clouds are firstly classified into one of three groups: building, ground, or unassigned. Ground points are further processed by a novel algorithm to extract a road network. The algorithm exploits the high variance of slope and height of the point data in the direction orthogonal to the road boundaries. Applying the proposed approach on a 40 million point dataset successfully extracted a complex road network with an F-measure of 76.9%.",
keywords = "aerial imagery, aerial laser scanning, data fusion, hybrid indexing, machine learning, road detection",
author = "Vo, {Anh Vu} and Linh Truong-Hong and Laefer, {Debra F.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 ; Conference date: 26-07-2015 Through 31-07-2015",
year = "2015",
month = nov,
day = "10",
doi = "10.1109/IGARSS.2015.7326746",
language = "English (US)",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4177--4180",
booktitle = "2015 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2015 - Proceedings",
}