Using data from the Puget Sound LiDAR Consortium, I did a very straightforward analysis to determine tree height. By subtracting the 6-foot resolution bare earth data from the 6-foot resolution top surface data you get the difference, which is of course the height of whatever is out there.
Now, what I really want is to determine the spatial pattern and extent of forested areas so there is one slight problem with the data: if I determine “forested” land to be anything over say, 30 feet high, then the places that have had recent forest harvest will not be delineated as “forested.” For some analyses this would be okay but we’d like to know total forest versus non forest where clear-cuts we still consider to be forested since they will be replanted (unless they are going to be converted).
The accuracy of the data, however, makes it so appealing to use that we’ll have to determine a way around this slight inadequacy. I’ll probably bring in a couple of other layers such as parcel landuse codes that denote forest land to add back in any areas that were not initially designated as forest but that are in a commercial forest parcel. This still doesn’t help capture any recent cutting done at a very small scale, however, such as when a 5 acre parcel owner cuts 5 of their 10 trees.
I’ve only run the analysis on one tile so far, while the entire study area is around 200 tiles. The one tile didn’t take very long to run in ArcGIS so hopefully all 200 will be relatively easy. I’m still in the very early stages of this analysis so who knows what snags will be encountered. In the screenshots below you’ll see the results and an image of the area to compare it with. The results show values as high as 300 feet. Those would be interesting to select out. Most of the bright-white areas, though, are only about 100 feet.
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