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The analysis of the multi-layer structure of wild forests is an importantchallenge of automated large-scale forestry. While modern aerial LiDARs offergeometric information across all vegetation layers, most datasets and methodsfocus only on the segmentation and reconstruction of the top of canopy. Werelease WildForest3D, which consists of 29 study plots and over 2000 individualtrees across 47 000m2 with dense 3D annotation, along with occupancy and heightmaps for 3 vegetation layers: ground vegetation, understory, and overstory. Wepropose a 3D deep network architecture predicting for the first time both 3Dpoint-wise labels and high-resolution layer occupancy rasters simultaneously.This allows us to produce a precise estimation of the thickness of eachvegetation layer as well as the corresponding watertight meshes, thereforemeeting most forestry purposes. Both the dataset and the model are released inopen access: https://github.com/ekalinicheva/multi_layer_vegetation.

Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans