Aerial laser scanning and imagery data fusion for road detection in city scale

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Title: Aerial laser scanning and imagery data fusion for road detection in city scale
Authors: Vo, Anh-Vu
Truong-Hong, Linh
Laefer, Debra F.
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Date: 31-Jul-2015
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%.
Funding Details: European Research Council
Type of material: Conference Publication
Publisher: IEEE
Copyright (published version): 2015 IEEE
Keywords: Aerial laser scanningAerial imageryData fusionRoad detectionMachine learningHybrid indexing
DOI: 10.1109/IGARSS.2015.7326746
Language: en
Status of Item: Not peer reviewed
Conference Details: 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy, 26 - 31 July 2015
Appears in Collections:Earth Institute Research Collection
Civil Engineering Research Collection

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