Influence of mobile light detecting and ranging data quality in road runoff evaluation

Abstract. A mobile light detecting and ranging (LiDAR) system is used to provide point cloud datasets as a topographic base for runoff studies. The point clouds are rasterized to evaluate road runoff using the D8 algorithm. Gaussian noise is artificially induced in the point cloud to simulate inaccuracies in geopositioning and determine its influence in the evaluation of runoff direction. Accuracy in the determination of flow direction decreases with the increase of Gaussian noise. Accuracy also decreases with the decrease of the cell size of the raster dataset. Flow direction shows inaccuracies up to 47 deg with a cell resolution of 0.5 m and Gaussian noise of 0.15 m (standard deviation). On the other hand, cell resolutions of 5 m show a maximum difference of 15 deg with the same noise.

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