Removing outliers (noise) from Lidar (point cloud) data in large datasets

02-08-2021 08:33 PM
New Contributor


I'm processing a LAS dataset with 1,200+ tiles and about 500gb. ArcGIS Pro is doing fine creating rasters based on models (e.g., DSM, DEM, etc.). However, I need to remove outliers from this dataset. When testing different tools, the "Classify LAS Noise" produced the best results. My project area is mostly covered with forest, so my understanding is that "Isolation" is the most adequate method here. The problem is that this operation is taking a massive amount of time. Perhaps more than weeks if I let it run for all tiles (my computer is top-notch). Do you have any suggestions on how to proceed? Is this the only approach to properly remove outliers in a systematic way for the full area?

Please, see some images of the outliers. Most of the area is fine, with a few outliers here and there. These areas of the images are the worst by far.

Thank you very much!

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