Forest canopies and tree crown structures are of high ecological importance. Measuring canopies and crowns by direct inventory methods is time‐consuming and of limited accuracy. High‐resolution inventory tools, in particular terrestrial laser scanning (TLS), is able to overcome these limitations and obtain three‐dimensional (3D) structural information about the canopy with a very high level of detail. The main objective of this study was to introduce a novel method to analyze spatiotemporal dynamics in canopy occupancy at the individual tree and local neighborhood level using high‐resolution 3D TLS data. For the analyses, a voxel grid approach was applied. The tree crowns were modeled through the combination of two approaches: the encasement of all crown points with a 3D α‐shape, which was then converted into a voxel grid, and the direct voxelization of the crown points. We show that canopy occupancy at individual tree level can be quantified as the crown volume occupied only by the respective tree or shared with neighboring trees. At the local neighborhood level, our method enables the precise determination of the extent of canopy space filling, the identification of tree–tree interactions, and the analysis of complementary space use. Using multitemporal TLS data recordings, this method allows the precise detection and quantification of changes in canopy occupancy through time. The method is applicable to a wide range of investigations in forest ecology research, including the study of tree diversity effects on forest productivity or growing space analyses for optimal tree growth. Due to the high accuracy of this novel method, it facilitates the precise analyses even of highly plastic individual tree crowns and, thus, the realistic representation of forest canopies. Moreover, our voxel grid framework is flexible enough to allow for the inclusion of further biotic and abiotic variables relevant to complex analyses of forest canopy dynamics.

Accurate estimates of the wood volume or biomass of individual trees have gained considerable importance in recent years. The accuracy of wood volume estimation by terrestrial laser scanning (TLS) point cloud data may differ between individual trees due to species-specific differences in tree architecture. We selected three common and ecologically important central European deciduous tree species, which differ considerably in tree architectural complexity in early ontogenetic stages: Acer pseudoplatanus (simple), Sorbus aucuparia (intermediate) and Betula pendula (complex). We scanned six single young trees for each species (18 trees in total) under optimal scan conditions (single tree stand, leafless state, four scanning positions, high resolution). TLS-based volume estimates were derived for the total tree as well as for the two compartments; trunk and branches, using a voxel-based bounding box method. These estimates were compared with highly accurate xyolmetric (water displacement) volume measurements. Coefficients of determination between xylometric measurements and bounding box estimates were very high for total trees (R²_adj = 0.99), trunks (R²_adj = 0.99), and high for branches (R²_adj = 0.78). The accuracy of estimations for total tree and trunk volume was highly similar among the three tree species. In contrast, significant differences were found for branch volume estimates: the accuracy was very high for Sorbus aucuparia, intermediate for Betula pendula, and low for Acer pseudoplatanus. A stepwise multiple regression showed that the accuracy of branch volume estimates was negatively related to the number of the first-order branches within diameter sizes of D ≤ 5 mm and crown surface area (R²_adj = 0.61). We conclude that the accuracy in total tree and trunk volume estimates was not affected by the studied types of tree architectural complexity. The impact of the structural variability of branches and occlusion by branches was, thus, not as high as expected. In contrast, the accuracy of branch volume estimates was strongly influenced by tree architectural complexity, though not in a simple way. Because underestimations originated from different sources, the accuracy of branch volume estimates cannot be directly derived from the degree of architectural complexity. These results imply that the voxel-based bounding box method provides highly accurate total tree and trunk volume estimates, whereas further research is needed to improve branch volume estimation for young trees of different architectural types.

We present the data recorded by eight institutions within the PYROPHOB project, running from 2020 to 2024 at two forest research sites in the south-west of Brandenburg, Germany. The aim of the project was to monitor abiotic and biotic parameters of forest regrowth under different management regimes on former wildfire sites in northeastern Germany. The observations comprised intermittent and continuous measurements or surveys on meteorological parameters (rainfall, temperature, vapour pressure deficit), soil (soil type and texture, soil chemistry and leaching, water content, soil temperature), deadwood, stand structure, vegetation regrowth, abundance of selected fauna (moths, beetles, mammals), UAV-based remote sensing (stand structure, spatial overview), and photo monitoring (succession). Thus, the multitude of collected data allows not only for detailed analyses of these observables separately, but also considering their interaction for a more multidisciplinary view on forest recovery after a wildfire. The data are available under the following DOIs: https://doi.org/10.23728/b2share.08a6a8b56f774a08a984871e7ef1b5a8 (Part 1, Schmehl et al., 2025a), under embargo until 31 March 2026 (Part 2, Schmehl et al., 2025b), https://doi.org/10.23728/b2share.de1661761da5481f938caf460e4f0ca9 (Part 3.1, Schmehl et al., 2025c), and https://doi.org/10.23728/b2share.51bdf4b6dc854873b6ff44fdddbf4c3b (Part 3.2, Schmehl et al., 2025d).

We present the data recorded by eight institutions within the PYROPHOB project, running from 2020 to 2024 at two forest research sites in the south-west of Brandenburg, Germany. The aim of the project was to monitor abiotic and biotic parameters of forest regrowth under different management regimes on former wildfire sites in northeastern Germany. The observations comprised intermittent and continuous measurements or surveys on meteorological parameters (rainfall, temperature, vapour pressure deficit), soil (soil type and texture, soil chemistry and leaching, water content, soil temperature), deadwood, stand structure, vegetation regrowth, abundance of selected fauna (moths, beetles, mammals), UAV-based remote sensing, and photo monitoring. Thus, the multitude of collected data allows not only for detailed analyses of these observables separately, but also considering their interaction for a more multidisciplinary view on forest recovery after a wildfire. The data are available under the following DOIs: 10.23728/b2share.5821b57eae3b45619c2263205b1c9815 (Part 1, (Schmehl et al., 2025a)), under embargo until 2026-03-31 (Part 2, (Schmehl et al., 2025b)), 10.23728/b2share.d49631857d1345c48be9e36b62214e6d (Part 3.1, (Schmehl et al., 2025c)), and 10.23728/b2share.51bdf4b6dc854873b6ff44fdddbf4c3b (Part 3.2, (Schmehl et al., 2025d)).