A voxel-based technique to estimate the volume of trees from terrestrial laser scanner data

32 citations as recorded by crossref.

1. Advances in Laser Scanning to Assess Carbon in Forests: From Ground-Based to Space-Based Sensors N. Coops et al. https://doi.org/10.1007/s40725-024-00242-4
2. PointDMM: A Deep-Learning-Based Semantic Segmentation Method for Point Clouds in Complex Forest Environments J. Li et al. https://doi.org/10.3390/f14122276
3. Efficient Encoding and Decoding of Voxelized Models for Machine Learning-Based Applications D. Strnad et al. https://doi.org/10.1109/ACCESS.2025.3526202
4. Estimating biomass volumes on aquaculture dropper lines using multibeam water column data T. Vandorpe et al. https://doi.org/10.3389/frsen.2025.1572674
5. Geometric Modeling and Surface-Quality Inspection of Prefabricated Concrete Components Using Sliced Point Clouds Z. Xu et al. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002345
6. 3D reconstruction and volume measurement of irregular objects based on RGB-D camera Y. Zhu et al. https://doi.org/10.1088/1361-6501/ad7621
7. Quantifying the Link Between 3D Vegetation Structure and Plant Diversity in Urban Parks Using Fused Multi-Platform LiDAR Data Y. Liu et al. https://doi.org/10.3390/rs18101458
8. Point-cloud segmentation and volume estimation of dense medium piles based on an improved PointNet++ M. Sun et al. https://doi.org/10.1080/19392699.2026.2672626
9. A fast volume measurement method for obtaining point cloud data from bulk stockpiles W. Ding et al. https://doi.org/10.1088/1361-6501/acdc43
10. Comparative Accuracy Assessment of Unmanned and Terrestrial Laser Scanning Systems for Tree Attribute Estimation in an Urban Mediterranean Forest A. Šiljeg et al. https://doi.org/10.3390/rs17213557
11. Processing Point Clouds Using Simulated Physical Processes as Replacements of Conventional Mathematically Based Procedures: A Theoretical Virtual Measurement for Stem Volume Z. Wang et al. https://doi.org/10.3390/rs13224627
12. Volume Estimation of Stem Segments Based on a Tetrahedron Model Using Terrestrial Laser Scanning Data L. You et al. https://doi.org/10.3390/rs15205060
13. Nighttime Mobile Laser Scanning and 3D Luminance Measurement: Verifying the Outcome of Roadside Tree Pruning with Mobile Measurement of the Road Environment M. Maksimainen et al. https://doi.org/10.3390/ijgi9070455
14. Do different indices of forest structural heterogeneity yield consistent results? K. Reich et al. https://doi.org/10.3832/ifor4096-015
15. Evaluation of mobile laser scanning acquisition scenarios for automated wood volume estimation in a temperate hardwood forest using quantitative structural models B. Vandendaele et al. https://doi.org/10.1139/cjfr-2023-0202
16. A comparative analysis of two point cloud volume calculation methods B. Li et al. https://doi.org/10.1080/01431161.2018.1541111
17. Comparison of models describing forest inventory attributes using standard and voxel-based lidar predictors across a range of pulse densities G. Pearse et al. https://doi.org/10.1016/j.jag.2018.10.008
18. Simulation of Sentinel-2 Bottom of Atmosphere Reflectance Using Shadow Parameters on a Deciduous Forest in Thailand T. Fujiwara & W. Takeuchi https://doi.org/10.3390/ijgi9100582
19. Estimating volume of oversized copper ore chunks in an underground mine using a laser scanner and an RGB camera for hammering efficiency assessment P. Dąbek et al. https://doi.org/10.1080/17480930.2023.2289302
20. Automated Estimation of Standing Dead Tree Volume Using Voxelized Terrestrial Lidar Data E. Putman & S. Popescu https://doi.org/10.1109/TGRS.2018.2839088
21. Comparison of wood volume estimates of young trees from terrestrial laser scan data M. Kunz et al. https://doi.org/10.3832/ifor2151-010
22. Comparison and Combination of Mobile and Terrestrial Laser Scanning for Natural Forest Inventories A. Bienert et al. https://doi.org/10.3390/f9070395
23. A high‐resolution approach for the spatiotemporal analysis of forest canopy space using terrestrial laser scanning data C. Hess et al. https://doi.org/10.1002/ece3.4193
24. Terrestrial laser scanning vs. manual methods for assessing complex forest stand structure: a comparative analysis on plenter forests Y. Wardius & S. Hein https://doi.org/10.1007/s10342-023-01641-1
25. An innovative and automated method for characterizing wood defects on trunk surfaces using high-density 3D terrestrial LiDAR data V. Nguyen et al. https://doi.org/10.1007/s13595-020-01022-3
26. Simulation of reflected sunlight using a voxel model in a forest T. FUJIWARA & M. TAKAGI https://doi.org/10.4287/jsprs.58.184
27. Tree stem volume estimation from terrestrial LiDAR point cloud by unwrapping Z. An & R. Froese https://doi.org/10.1139/cjfr-2022-0153
28. A novel circle-fitting algorithm combined with a height-diameter pair selection method improves the tree trunk volume estimation from terrestrial laser scanning X. Yang et al. https://doi.org/10.1016/j.compag.2026.111822
29. The importance of riparian plant orientation in river flow: implications for flow structures and drag R. Boothroyd et al. https://doi.org/10.1080/24705357.2019.1573648
30. The impact of 3D urban landscapes on multidimensional human experience: An interpretable machine learning approach Y. Liu et al. https://doi.org/10.1016/j.buildenv.2026.114320
31. An insight into the patterns and controls of the structure of South American Chaco woodlands A. Ferraina et al. https://doi.org/10.1002/ldr.4186
32. Micro-CT imaging of a frozen bubble cluster: Sample holder development and image processing techniques S. Janishar Anzoom et al. https://doi.org/10.1016/j.seppur.2023.126111