Interurban visibility diagnosis from point clouds

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Abstract

We present an approach for automatic visibility analysis in interurban roads from point clouds. The methodology is based on a ray-tracing algorithm followed by an occlusion detection to identify potential obstacles between the driver and the theoretical position of pedestrians and cyclists. As a result, the area of visibility from each driver position is obtained. The method compares the performance and suitability of point clouds acquired from both Airborne and Mobile Laser Scanning. The methodology is tested in six real case studies. In most cases, results obtained from MLS are more accurate since the point clouds are acquired from a perspective similar to driver and they have higher resolution.

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Iglesias, Ó., Díaz-Vilariño, L., González-Jorge, H., & Lorenzo, H. (2016). Interurban visibility diagnosis from point clouds. European Journal of Remote Sensing, 49, 673–690. https://doi.org/10.5721/EuJRS20164935

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