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Related: Just the other day I used USGS 3DEP LiDAR data + Claude Code to get a sense for the number of trees on my property. Diffing terrain map and canopy map gives tree elevation. It was a fun project to explore, primarily because I set CC loose and said "here is the bounding box of my property, pad it by 50 feet and then go absolutely nuts against government datasets gathering as much open data as you can" - it figured out the rest. Dug into soil maps, historical satellite imagery, and lidar data.

Here are the visuals re: trees - https://i.imgur.com/R0W4q4O.png

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The USGS Lidar data is a treasure trove, I use it a lot at work.

What did you do to actually count trees? Even from aerial Lidar it can be a bit finicky for closed canopies.

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It's very rudimentary: smooth the canopy and find the local maxima above a base height. It's really just identifying the tallest points.

Here is the first pass, https://i.imgur.com/f7Gpxmm.png, it under counted and also even counted my house as a tree, lol.

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> counted my house as a tree

Even the more sophisticated algorithms pretty much always do this ;-)

You are probably not interested in taking this further, but you could give the Li tree filter a try: https://pdal.org/en/stable/stages/filters.litree.html

But getting perfect segmentation is basically impossible.

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