GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD

Rashidi, P.; Rastiveis, H.

Separating point clouds into ground and non-ground points is a necessary step to generate digital terrain model (DTM) from LiDAR dataset. In this research, a new method based on multi-scale analysis of height difference threshold is proposed for ground filtering of LiDAR data. The proposed method utilizes three windows with different sizes in small, average and large to cover the entire LiDAR point clouds, then with a height difference threshold, point clouds can be separated to ground and non-ground in each local window. Meanwhile, the best threshold values for size of windows are considered based on physical characteristics of the ground surface and size of objects. Also, the minimum of height of object in each window selected as height difference threshold. In order to evaluate the performance of the proposed algorithm, two datasets in rural and urban area were applied. The overall accuracy in rural and urban area was 96.06% and 94.88% respectively. These results of the filtering showed that the proposed method can successfully filters non-ground points from LiDAR point clouds despite of the data area.

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Rashidi, P. / Rastiveis, H.: GROUND FILTERING LiDAR DATA BASED ON MULTI-SCALE ANALYSIS OF HEIGHT DIFFERENCE THRESHOLD. 2017. Copernicus Publications.

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Rechteinhaber: P. Rashidi

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