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I am learning how to use lidar to study forest structures, but I cannot find any methodology on how to map understory trees. It is for a school project where I am mapping forest developmental phases in a specific area of interest which is a beech forest. The lidar data I have is airborne full waveform taken during leaf-off conditions. I am working on QGIS 2.18.25 and LAStools. Does anyone have any suggestions on how understory trees could be identified?

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The following literature highlights several approaches that should help get you started:

Hamraz, H.; Contreras, M.A.; Zhang, J. Vertical stratification of forest canopy for segmentation of understory trees within small-footprint airborne LiDAR point clouds. ISPRS J. Photogramm. Remote Sens. 2017, 130, 385–392.

Wing, B.M.; Ritchie, M.W.; Boston, K.; Cohen, W.B.; Gitelman, A.; Olsen, M.J. Prediction of understory vegetation cover with airborne lidar in an interior ponderosa pine forest. Remote Sens. Environ. 2012, 124, 730–741.

Latifi, H.; Heurich, M.; Hartig, F.; Müller, J.; Krzystek, P.; Jehl, H.; Dech, S. Estimating over- and understorey canopy density of temperate mixed stands by airborne LiDAR data. Forestry 2015, 89, 69–81.

Amiri, N.; Yao, W.; Heurich, M.; Krzystek, P.; Skidmore, A.K. Estimation of regeneration coverage in a temperate forest by 3D segmentation using airborne laser scanning data. Int. J. Appl. Earth Observ. Geoinf.

Fleming, S.; Cottin, A.; Woodhouse, I. The first spectral map of a forest understory from multispectral lidar. Lidar News 2015, 5, 26–30.

Hill, R.; Broughton, R. Mapping the understorey of deciduous woodland from leaf-on and leaf-off airborne LiDAR data: A case study in lowland Britain. ISPRS J. Photogramm. Remote Sens. 2009, 64, 223–233.

Korpela, I.; Hovi, A.; Morsdorf, F. Understory trees in airborne LiDAR data—Selective mapping due to transmission losses and echo-triggering mechanisms. Remote Sens. Environ. 2012, 119, 92–104.

Heinzel, J., & Ginzler, C. (2019). A Single-Tree Processing Framework Using Terrestrial Laser Scanning Data for Detecting Forest Regeneration. Remote Sensing, 11(1), 60. [1]: https://arxiv.org/pdf/1701.00169

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