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I created very high dense point cloud of some forest plots using terrestrial laser scanner. Then removed points above 1.3 meter to see the coarse woody debris (Fallen dead trees). Attached is the shaded DEM of the sample plot with coarse woody debris inside red ellipse.

enter image description here

Plot also consists of small trees, part of the stems of trees below 1.3 meter, ground and small rocks. From the image woody debris is discernible with its continuous shape. I am looking for the tool to extract woody debris from this image. Arcmap, Envi or any open source software would be perfect, and I also have basic Python knowledge if coding is helpful.

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    Is your LiDAR classified? Automatic ground/nonground would help here. Automatic algorithms should classify your fallen debris as buildings (above ground with no ground points under), you could try converting your building class (or low/medium veg class) to a TIN with Esri and convert the TIN to triangle resources.arcgis.com/en/help/main/10.1/index.html#//…, delete really long sided triangles (python required), dissolve and ignore small ones. All of these metrics will require experimentation and probably some manual checking to remove aberrations. – Michael Stimson Dec 17 '18 at 0:19
  • Thank you @ Michael Stimson. I have ground and vegetation classified, but I will try building classification to see if it can detect woody debris. TIN method sounds like more manual work which may not be ideal for my case as I have 96 1 hectare plots. – Sher Dec 17 '18 at 0:31
  • Tinning and decimating should reduce the number of areas to inspect by omitting anything that is too small to be considered contiguous but from experience there will be a small number of areas that appear to be contiguous but are not.. contiguity is easily detected by the eye but not so easy to detect by algorithm; machine learning may be of help but I have no experience in this field to persuade/dissuade you from this course of action. Personally I wouldn't rely solely on a software process without verifying the results. – Michael Stimson Dec 17 '18 at 0:45
  • When you get up to the verification stage I have an answer gis.stackexchange.com/questions/152536/… that contains a link to an ArcMap addin for visiting each feature, this tool would help speed up your verification and ensure none are missed; the tool works on a selected set of features, storing the extents in memory then clicking the 'next' button iterates and zooms to the next feature making the process less tedious. – Michael Stimson Dec 17 '18 at 0:48
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    I'm not sure if this has been done before. I would attempt to use a fully convolutional network that does image segmentation such as a U-net: deeplearning.net/tutorial/unet.html. – Aaron Jan 11 at 13:52

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