Articles | Volume 14, issue 7
https://doi.org/10.5194/essd-14-2989-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-2989-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Individual tree point clouds and tree measurements from multi-platform laser scanning in German forests
3DGeo Research Group, Institute of Geography, Heidelberg University, Heidelberg, Germany
Jannika Schäfer
Institute of Geography and Geoecology, Karlsruhe Institute of Technology, Karlsruhe, Germany
Lukas Winiwarter
3DGeo Research Group, Institute of Geography, Heidelberg University, Heidelberg, Germany
Nina Krašovec
3DGeo Research Group, Institute of Geography, Heidelberg University, Heidelberg, Germany
Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
Fabian E. Fassnacht
Institute of Geography and Geoecology, Karlsruhe Institute of Technology, Karlsruhe, Germany
Remote Sensing and Geoinformatics, Freie Universität Berlin, Berlin, Germany
Bernhard Höfle
3DGeo Research Group, Institute of Geography, Heidelberg University, Heidelberg, Germany
Interdisciplinary Center for Scientific Computing (IWR), Heidelberg University, Heidelberg, Germany
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36 citations as recorded by crossref.
- Individual tree segmentation from UAS Lidar data based on hierarchical filtering and clustering C. Zhang et al. 10.1080/17538947.2024.2356124
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- 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. 10.1016/j.jenvman.2024.123287
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- Assessing the potential of synthetic and ex situ airborne laser scanning and ground plot data to train forest biomass models J. Schäfer et al. 10.1093/forestry/cpad061
- CNN-based transfer learning for forest aboveground biomass prediction from ALS point cloud tomography J. Schäfer et al. 10.1080/22797254.2024.2396932
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- LiPheStream - A 18-month high spatiotemporal resolution point cloud time series of Boreal trees from Finland S. Wittke et al. 10.1038/s41597-024-04143-w
- Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR S. Oehmcke et al. 10.1016/j.rse.2023.113968
- Regional‐Scale Landscape Response to an Extreme Precipitation Event From Repeat Lidar and Object‐Based Image Analysis S. DeLong et al. 10.1029/2022EA002420
- Three-Dimensional Reconstruction of Forest Scenes with Tree–Shrub–Grass Structure Using Airborne LiDAR Point Cloud D. Xu et al. 10.3390/f15091627
- Tree parameter extraction method based on new remote sensing technology and terrestrial laser scanning technology A. Wang et al. 10.1016/j.bdr.2024.100460
- Exploring unmanned aerial systems operations in wildfire management: data types, processing algorithms and navigation P. Keerthinathan et al. 10.1080/01431161.2023.2249604
- Tree Branch Characterisation from Point Clouds: a Comprehensive Review R. Hartley et al. 10.1007/s40725-024-00225-5
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- Towards Intricate Stand Structure: A Novel Individual Tree Segmentation Method for ALS Point Cloud Based on Extreme Offset Deep Learning Y. Zhang et al. 10.3390/app13116853
- TreeLearn: A deep learning method for segmenting individual trees from ground-based LiDAR forest point clouds J. Henrich et al. 10.1016/j.ecoinf.2024.102888
- A Method for Extracting the Tree Feature Parameters of Populus tomentosa in the Leafy Stage X. Shen et al. 10.3390/f14091757
- 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. 10.3390/rs16040697
- A Method to Order Point Clouds for Visualization on the Ray Tracing Pipeline P. Timokhin & M. Mikhaylyuk 10.1134/S0361768824700075
- A Review of Software Solutions to Process Ground-based Point Clouds in Forest Applications A. Murtiyoso et al. 10.1007/s40725-024-00228-2
- A Reliable DBH Estimation Method Using Terrestrial LiDAR Points through Polar Coordinate Transformation and Progressive Outlier Removal Z. Hui et al. 10.3390/f15061031
- DPFANet: Deep Point Feature Aggregation Network for Classification of Irregular Objects in LIDAR Point Clouds S. Zhang & D. Xu 10.3390/electronics13224355
- A Review of Point Cloud Registration Algorithms for Laser Scanners: Applications in Large-Scale Aircraft Measurement H. Si et al. 10.3390/app122010247
- ALS Point Cloud Semantic Segmentation Based on Graph Convolution and Transformer With Elevation Attention S. Huang et al. 10.1109/JSTARS.2023.3347224
- Deep learning with simulated laser scanning data for 3D point cloud classification A. Esmorís et al. 10.1016/j.isprsjprs.2024.06.018
- 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. 10.3390/rs15184366
- Fine-Scale Quantification of Absorbed Photosynthetically Active Radiation (APAR) in Plantation Forests with 3D Radiative Transfer Modeling and LiDAR Data X. Zhao et al. 10.34133/plantphenomics.0166
- 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. 10.1093/forestry/cpae044
- The Method to Order Point Clouds for Visualization on the Ray Tracing Pipeline P. Timokhin & M. Mikhailyuk 10.31857/S0132347424030054
- SegmentAnyTree: A sensor and platform agnostic deep learning model for tree segmentation using laser scanning data M. Wielgosz et al. 10.1016/j.rse.2024.114367
- 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. 10.1016/j.ecolind.2024.111901
- Spatial Differentiation of Mangrove Aboveground Biomass and Identification of Its Main Environmental Drivers in Qinglan Harbor Mangrove Nature Reserve K. Wang et al. 10.3390/su16198408
- Individual-Tree Segmentation from UAV–LiDAR Data Using a Region-Growing Segmentation and Supervoxel-Weighted Fuzzy Clustering Approach Y. Fu et al. 10.3390/rs16040608
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Latest update: 13 Dec 2024
Short summary
3D point clouds, acquired by laser scanning, allow us to retrieve information about forest structure and individual tree properties. We conducted airborne, UAV-borne and terrestrial laser scanning in German mixed forests, resulting in overlapping point clouds with different characteristics. From these, we generated a comprehensive database of individual tree point clouds and corresponding tree metrics. Our dataset may serve as a benchmark dataset for algorithms in forestry research.
3D point clouds, acquired by laser scanning, allow us to retrieve information about forest...
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