What is it about?

Small unmanned aerial vehicles (UAVs) can be utilized acquire data of highway sections with potential safety risks. A double grid flight is proposed to obtain an adequate three-dimensional 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.

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Why is it important?

UAVs facilitate data acquisition very soon after identifying an issue, enabling rapid decision making.


This research highlights the importance of using ground control points (GCPs) when referencing a point cloud derived from a UAV-based survey.

Dr. César De Santos-Berbel
Universidad Politecnica de Madrid

Read the Original

This page is a summary of: Using Small Unmanned Aerial Vehicle in 3D Modeling of Highways with Tree-Covered Roadsides to Estimate Sight Distance, Remote Sensing, November 2019, MDPI AG,
DOI: 10.3390/rs11222625.
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