I see a company in California is using AI to extract Lidar data.. Geospatial data is collected rapidly through LiDAR surveys, yet processing this data continues to be slow and tedious. Civil Maps is disrupting the geospatial industry by launching an streamlined solution for extracting and classifying features from 3D laser scans for export to popular GIS software. By leveraging proprietary Artificial Intelligence graph search powered by a supercomputer, Civil Maps is reduces turnaround times by 75% and more accurate than traditional human-based processing, providing a streamlined approach to asset management and planning...Is anyone using this technique or leasing super computer time to do extractions? I have looked at Sablo and Amazon but want to know if it's feasible to...Just fishing for some feed back on these and similar topics.

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  • I am sorry I have nothing to contribute to the interesting question forwarded by CUT FILL. But I had other questions to add to that one. Does anyone know of a pilot LIDAR test for topographic mapping? Specifically: a pilot test consisting of first obtaining a LIDAR-derived DTM (gridded digital file) at medium scale for an area that exhibits as many examples of terrain as possible: flat, broken, dry, wetland, etc. In this area there should exist exist a top quality topo map. For instance a 1:20000 Swiss topo map. Next this map should be impeccably converted into a gridded model and compared the LIDAR DTM. 

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