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Using Small Unmanned Aerial Vehicle in 3D Modeling of Highways with Tree-Covered Roadsides to Estimate Sight Distance

1
Departamento de Ingeniería Geológica y Minera, Universidad Politécnica de Madrid, 28003 Madrid, Spain
2
Departamento de Estructuras y Física de Edificación, Universidad Politécnica de Madrid, 28040 Madrid, Spain
3
Departamento de Ingeniería del Transporte, Territorio y Urbanismo, Universidad Politécnica de Madrid, 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(22), 2625; https://doi.org/10.3390/rs11222625
Received: 9 October 2019 / Revised: 30 October 2019 / Accepted: 7 November 2019 / Published: 10 November 2019
(This article belongs to the Section Engineering Remote Sensing)
The safe and efficient operation of highways largely depends on the adequate provision of sight distance. Small unmanned aerial vehicles (UAVs) can be utilized to efficiently complete data acquisition very soon after identifying an issue when searching for potential highway safety risks. A double grid flight is proposed to obtain an adequate three-dimensional (3D) recreation of the road environment, ensuring an unbiased sight distance output. Then, a dense cloud point is derived through a Structure from Motion Multi-View Stereo process. The point cloud is classified to produce both a terrain model, characterized by its resolution, and a 3D-object model, characterized by the maximum edge length of the entities. The resulting road environment model is utilized to calculate sight distance in a geographic information system. The results enabled the detection of accident-prone locations caused by sight distance limitations. Moreover, the impact of the 3D modeling parameters on the results was assessed. View Full-Text
Keywords: unmanned aerial vehicles; Structure from Motion; 3D modeling; road safety unmanned aerial vehicles; Structure from Motion; 3D modeling; road safety
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MDPI and ACS Style

Iglesias, L.; De Santos-Berbel, C.; Pascual, V.; Castro, M. Using Small Unmanned Aerial Vehicle in 3D Modeling of Highways with Tree-Covered Roadsides to Estimate Sight Distance. Remote Sens. 2019, 11, 2625.

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