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Steve, Yes indeed. That is why I mentioned that the "cut larger polygon" was the most efficient. But sometimes you have to deal with the hand you are dealt (Shapefile or Geodatabase).
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06-18-2015
10:13 AM
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I use the cut larger polygon method suggested by Darren when I can. It is definitely the most efficient and leads to fewer gap and overlap errors. Another couple of techniques that I use: 1) use the Trace tool to trace coincident boundaries, then end the trace to digitize the non-coincident boundaries 2) turn vertex snapping on (Editor - Snapping - Snapping Window, click on Edit Sketch and Edit Sketch Vertices). Then, as you are digitizing, hold the V key down which will highlight the vertices making it easier to click on the exact location so that the lines coincide
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06-18-2015
09:06 AM
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Gordon, I agree that finding the nearest 5 trees would be very compute intensive. Another idea might be to use a "moving window" type of analysis. You could center the moving window on each tree, and get a count of how many trees are inside that window which would give you a measure of density/spacing. Alternatively you could use one of the neighborhood analysis tools in Spatial Analyst (which is quite efficient) to calculate density/spacing measures across the entire study area. Those density/spacing measures could then be imputed to individual trees. That begs the question that Sephe asked, how will you use density/spacing to calculate diameters. Crown Area is very strongly correlated with diameter. But density/spacing and crown area may or may not be related due to canopy gaps, especially in younger forests. You may be better served finding a method to calculate crown area from your LiDAR data
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05-21-2015
08:12 AM
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This is an exceptional conference and is a must attend for all Forestry and Natural Resources professionals.
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01-23-2015
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1 | 06-18-2015 10:13 AM |
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