80 citations as recorded by crossref.

1. A simple oriented search and clustering method for extracting individual forest trees from ALS point clouds W. Ding et al.
2. Upscaling UAV and Lidar-derived forest gap area and edge length extractions using radar and optical sentinel images M. Naseri et al.
3. Exploring transfer learning for individual tree species classification by cross-platform point cloud L. Wang et al.
4. Accuracy comparison of terrestrial and airborne laser scanning and manual measurements for stem curve-based growth measurements of individual trees V. Soininen et al.
5. Assessing the potential of synthetic and ex situ airborne laser scanning and ground plot data to train forest biomass models J. Schäfer et al.
6. CNN-based transfer learning for forest aboveground biomass prediction from ALS point cloud tomography J. Schäfer et al.
7. Earth-Observation-Based Monitoring of Forests in Germany—Recent Progress and Research Frontiers: A Review S. Holzwarth et al.
8. Self-adaptive individual tree modeling based on skeleton graph optimization and fractal self-similarity Z. Hui et al.
9. Comparative Accuracy Assessment of Unmanned and Terrestrial Laser Scanning Systems for Tree Attribute Estimation in an Urban Mediterranean Forest A. Šiljeg et al.
10. Using Terrestrial Laser Scanning Data to Unsupervised Segment Broadleaved Tree and Estimate Leaf Area Y. Dong et al.
11. Three-Dimensional Reconstruction of Forest Scenes with Tree–Shrub–Grass Structure Using Airborne LiDAR Point Cloud D. Xu et al.
12. Towards Intricate Stand Structure: A Novel Individual Tree Segmentation Method for ALS Point Cloud Based on Extreme Offset Deep Learning Y. Zhang et al.
13. Carbon stock assessment and estimation using machine learning: A case study on acacia forest plantation in Rupat Island peat ecosystem, Indonesia W. Utomo et al.
14. A Comparative Analysis of Low-Cost Devices for High-Precision Diameter at Breast Height Estimation J. Výbošťok et al.
15. Comparing airborne laser scanning and UAV photogrammetry for estimating aboveground biomass of individual urban trees in Helsinki O. Shafaat et al.
16. A Method for Extracting the Tree Feature Parameters of Populus tomentosa in the Leafy Stage X. Shen et al.
17. Non-Destructive Estimation of Deciduous Forest Metrics: Comparisons between UAV-LiDAR, UAV-DAP, and Terrestrial LiDAR Leaf-Off Point Clouds Using Two QSMs Y. Gan et al.
18. A Method to Order Point Clouds for Visualization on the Ray Tracing Pipeline P. Timokhin & M. Mikhaylyuk
19. Individual Tree Segmentation Using Deep Learning and Climbing Algorithm: A Method for Achieving High-precision Single-tree Segmentation in High-density Forests under Complex Environments H. Ma et al.
20. DPFANet: Deep Point Feature Aggregation Network for Classification of Irregular Objects in LIDAR Point Clouds S. Zhang & D. Xu
21. Leveraging Open-Source Tools to Analyse Ground-Based Forest LiDAR Data in South Australian Forests S. O’Keeffe et al.
22. Point Cloud Data Mining With HD Map Priors for Making Synthetic Forest Datasets K. Karlauskas et al.
23. A Review of Point Cloud Registration Algorithms for Laser Scanners: Applications in Large-Scale Aircraft Measurement H. Si et al.
24. Tree Stem Detection and Crown Delineation in a Structurally Diverse Deciduous Forest Combining Leaf-On and Leaf-Off UAV-SfM Data S. Dietenberger et al.
25. HMeMD-Net: A Hybrid Network for Inverting Tree Diameter at Breast Height in Dense Mixed Forests With Airborne Laser Scanning Z. Zhang et al.
26. Benchmarking tree species classification from proximally sensed laser scanning data: Introducing the FOR‐species20K dataset S. Puliti et al.
27. TPM: Efficient Tree Point Matching for ULS-TBLS Point Clouds in Weakly Structured Forests H. Chen et al.
28. Construction of a Precision Thinning Framework for Cunninghamia Lanceolata Plantations Driven by Point Cloud Fusion and Multi-Criteria Weighting Z. Cai et al.
29. Using a terrestrial laser scanner (TLS) to optimize tree sampling for biomass model fitting: A case study in short-rotation woody crops (SRWCs) I. Dănilă et al.
30. The Method to Order Point Clouds for Visualization on the Ray Tracing Pipeline P. Timokhin & M. Mikhailyuk
31. OpenForest: a data catalog for machine learning in forest monitoring A. Ouaknine et al.
32. SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data M. Wielgosz et al.
33. Canopy structure influences arthropod communities within and beyond tree identity effects: Insights from combining LiDAR data, insecticidal fogging and machine learning regression modelling B. Wildermuth et al.
34. Spatial Differentiation of Mangrove Aboveground Biomass and Identification of Its Main Environmental Drivers in Qinglan Harbor Mangrove Nature Reserve K. Wang et al.
35. Individual-Tree Segmentation from UAV–LiDAR Data Using a Region-Growing Segmentation and Supervoxel-Weighted Fuzzy Clustering Approach Y. Fu et al.
36. Validation of the vertical plant area index profile product derived from GEDI over global forest sites Y. Wang et al.
37. Individual tree segmentation from UAS Lidar data based on hierarchical filtering and clustering C. Zhang et al.
38. InceptionFormer: A deep learning framework for UAV LiDAR point cloud completion to improve tree parameters estimation in dense forests B. Luo et al.
39. Benchmarking airborne laser scanning tree segmentation algorithms in broadleaf forests shows high accuracy only for canopy trees Y. Cao et al.
40. Evaluating forest aboveground biomass estimation model using simulated ALS point cloud from an individual-based forest model and 3D radiative transfer model across continents Z. Yu et al.
41. A new method for individual treetop detection with low-resolution aerial laser scanned data G. Diószegi et al.
42. Species-specific responses of tree productivity to diversity effects in young planted forests: Insights from terrestrial laser scanning M. Wang et al.
43. A novel UAV lidar-derived shrub structural index for estimating above-ground biomass J. Wu et al.
44. A crop tree model of Quercus serrata based on TLS data – a critical appraisal Y. Wardius et al.
45. Toward Detailed and Accurate Forest Inventory with Multi-Source Lidar Data Z. Ma et al.
46. Individual Tree Segmentation Based on Region-Growing and Density-Guided Canopy 3-D Morphology Detection Using UAV LiDAR Data S. Li et al.
47. LiPheStream - A 18-month high spatiotemporal resolution point cloud time series of Boreal trees from Finland S. Wittke et al.
48. Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR S. Oehmcke et al.
49. Adaptive Shortest Path Tracking for Robust Leaf–Wood Separation in Individual Trees from TLS Point Clouds Y. Shen et al.
50. Benchmarking individual tree segmentation using multispectral airborne laser scanning data: The FGI-EMIT dataset L. Ruoppa et al.
51. Regional‐Scale Landscape Response to an Extreme Precipitation Event From Repeat Lidar and Object‐Based Image Analysis S. DeLong et al.
52. Development and Evaluation of a Thinning Tree Selection System Using Optimization Techniques Based on Multi-Platform LiDAR Y. Lee et al.
53. A large dataset of labelled single tree point clouds, QSMs and tree graphs N. Griese et al.
54. Cognition-inspired multimodal attention fusion of close-range laser scanning data for globally representative tree species classification X. Luo et al.
55. Tree parameter extraction method based on new remote sensing technology and terrestrial laser scanning technology A. Wang et al.
56. Exploring unmanned aerial systems operations in wildfire management: data types, processing algorithms and navigation P. Keerthinathan et al.
57. Tree Branch Characterisation from Point Clouds: a Comprehensive Review R. Hartley et al.
58. MMTSCNet: Multimodal Tree Species Classification Network for Classification of Multi-Source, Single-Tree LiDAR Point Clouds J. Vahrenhold et al.
59. Graph-Based Leaf–Wood Separation Method for Individual Trees Using Terrestrial Lidar Point Clouds Z. Tian & S. Li
60. TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds J. Henrich et al.
61. The Role of RPAS in Vegetation Height Estimation: Challenges and Future Perspectives in the Forestry Context F. Moreira et al.
62. A Review of Software Solutions to Process Ground-based Point Clouds in Forest Applications A. Murtiyoso et al.
63. A Reliable DBH Estimation Method Using Terrestrial LiDAR Points through Polar Coordinate Transformation and Progressive Outlier Removal Z. Hui et al.
64. A synthetic data generation framework for deep learning-based LiDAR forest structure analysis J. Liu et al.
65. Efficient Registration of Airborne LiDAR and Terrestrial LiDAR Point Clouds in Forest Scenes Based on Single-Tree Position Consistency X. Cheng et al.
66. GlobalGeoTree: a multi-granular vision-language dataset for global tree species classification Y. Mu et al.
67. ALS Point Cloud Semantic Segmentation Based on Graph Convolution and Transformer With Elevation Attention S. Huang et al.
68. Evaluating UAV and Handheld LiDAR Point Clouds for Radiative Transfer Modeling Using a Voxel-Based Point Density Proxy T. Fujiwara et al.
69. Deep learning with simulated laser scanning data for 3D point cloud classification A. Esmorís et al.
70. Robust Multisource Forest Point Cloud Registration With Distribution Similarity Analysis X. Liu et al.
71. Interdisciplinary Applications of LiDAR in Forest Studies: Advances in Sensors, Methods, and Cross-Domain Metrics N. Fareed et al.
72. STSCNet：空基激光雷达树干点云补全网络模型 惠. Hui Zhenyang et al.
73. Assessing forest structural complexity: insights from alternative laser scanning approaches R. Cimdins et al.
74. Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data X. Zhao et al.
75. Testing treecbh in Central European forests: an R package for crown base height detection using high-resolution aerial laser-scanned data G. Diószegi et al.
76. Light detection and ranging of natural systems L. Irwin et al.
77. WHU-STree: A multi-modal benchmark dataset for street tree inventory R. Ding et al.
78. Cross-platform forest understanding: A multi-platform synergistic training framework for generalized forest point cloud segmentation J. Jiang et al.
79. Pointwise deep learning for leaf-wood segmentation of tropical tree point clouds from terrestrial laser scanning W. Van den Broeck et al.
80. Tree Species Classification Using Optimized Features Derived from Light Detection and Ranging Point Clouds Based on Fractal Geometry and Quantitative Structure Model Z. Hui et al.