UAV-BASED PHOTOGRAMMETRIC POINT CLOUDS – TREE STEM MAPPING IN OPEN STANDS IN COMPARISON TO TERRESTRIAL LASER SCANNER POINT CLOUDS

90 citations as recorded by crossref.

1. Use of UAV oblique imaging for the detection of individual trees in residential environments Y. Lin et al.
2. Co-registration of multi-sensor UAV imagery. Case study: Boreal forest areas P. Martínez-Carricondo et al.
3. Concept of an Innovative Autonomous Unmanned System for Bathymetric Monitoring of Shallow Waterbodies (INNOBAT System) M. Specht et al.
4. UAV data as alternative to field sampling to map woody invasive species based on combined Sentinel-1 and Sentinel-2 data T. Kattenborn et al.
5. Winter Wheat Crop Height Estimation Using Small Unmanned Aerial System (sUAS) M. Villareal et al.
6. A multi-scale approach of fluvial biogeomorphic dynamics using photogrammetry B. Hortobágyi et al.
7. Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices B. Strimbu et al.
8. Inventory of Small Forest Areas Using an Unmanned Aerial System S. Puliti et al.
9. Multi-level k-nearest neighbors algorithm for direct point cloud-based engineering analysis A. Corpuz et al.
10. UnDER: Unsupervised Dense Point Cloud Extraction Routine for UAV Imagery Using Deep Learning J. Bergado & F. Nex
11. Image-Based 3D Reconstruction for Posthurricane Residential Building Damage Assessment Z. Zhou et al.
12. Very High Density Point Clouds from UAV Laser Scanning for Automatic Tree Stem Detection and Direct Diameter Measurement K. Kuželka et al.
13. Short Communication. Using high resolution UAV imagery to estimate tree variables in Pinus pinea plantation in Portugal J. Hernandez et al.
14. Citrus rootstock evaluation utilizing UAV-based remote sensing and artificial intelligence Y. Ampatzidis et al.
15. Dynamic monitoring of maize field vegetation cover using sentinel-1 and sentinel-2 data and transfer learning algorithms H. Sun et al.
16. Integrated fire severity–land cover mapping using very-high-spatial-resolution aerial imagery and point clouds J. Arkin et al.
17. High-Throughput System for the Early Quantification of Major Architectural Traits in Olive Breeding Trials Using UAV Images and OBIA Techniques A. de Castro et al.
18. An Unsupervised Canopy-to-Root Pathing (UCRP) Tree Segmentation Algorithm for Automatic Forest Mapping J. Carpenter et al.
19. A comparison of terrestrial and UAS sensors for measuring fuel hazard in a dry sclerophyll forest S. Hillman et al.
20. Assessment of the Influence of Survey Design and Processing Choices on the Accuracy of Tree Diameter at Breast Height (DBH) Measurements Using UAV-Based Photogrammetry B. Moreira et al.
21. Three‐dimensional digitization of the arid land plant Haloxylon ammodendron using a consumer‐grade camera H. Huang et al.
22. Use of unmanned aerial vehicles for the diagnosis of parasitic plant infestation at the crown level in Pinus hartwegii L. León-Bañuelos et al.
23. Detection of Tree Species in Mixed Broad-Leaved Stands of Caspian Forests Using UAV Images (Case study: Darabkola Forest) m. Pourahmad et al.
24. Simplifying UAV-Based Photogrammetry in Forestry: How to Generate Accurate Digital Terrain Model and Assess Flight Mission Settings F. Pessacg et al.
25. Using Unmanned Aerial Vehicles in Postfire Vegetation Survey Campaigns through Large and Heterogeneous Areas: Opportunities and Challenges J. Fernández-Guisuraga et al.
26. Analysis of Changes in Oil Palm Canopy Architecture From Basal Stem Rot Using Terrestrial Laser Scanner N. Azuan et al.
27. Assessment of Using UAV Photogrammetry Based DEM and Ground-Measurement Based DEM in Computer-Assisted Forest Road Design İ. TAŞ et al.
28. 3D modelling of beach topography changes caused by the tombolo phenomenon using terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry on the example of the city of Sopot C. Specht et al.
29. Estimating tree heights with images from an unmanned aerial vehicle A. Birdal et al.
30. Acquisition of Forest Attributes for Decision Support at the Forest Enterprise Level Using Remote-Sensing Techniques—A Review P. Surový & K. Kuželka
31. Application of UAV photogrammetry for the assessment of forest structure and species network in the tropical forests of Southern Nigeria S. Akinbiola et al.
32. A Deformable Shape Model for Automatic and Real-Time Dendrometry L. Wells & W. Chung
33. Uncertainty in Parameterizing Floodplain Forest Friction for Natural Flood Management, Using Remote Sensing A. Antonarakis & D. Milan
34. Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds F. Brieger et al.
35. Assessing lean and positional error of individual mature Douglas-fir (Pseudotsuga menziesii) trees using active and passive sensors C. Garms et al.
36. Evaluation of UAV- and GNSS-Based DEMs for Earthwork Volume M. Akgul et al.
37. Photogrammetry and Remote Sensing for the identification and characterization of trees in urban areas. M. Mueed Choudhury et al.
38. A comparison between TLS and UAS LiDAR to represent eucalypt crown fuel characteristics S. Hillman et al.
39. Unmanned aerial systems for photogrammetry and remote sensing: A review I. Colomina & P. Molina
40. Urban Tree Species Identification and Carbon Stock Mapping for Urban Green Planning and Management M. Choudhury et al.
41. Combination of UAV Photogrammetry and Field Inventories Enables Description of Height–Diameter Relationship within Semi-Arid Silvopastoral Systems A. Fakhri et al.
42. Advancing in Pinus pinea L. cone yield assessment in Chile using UAV innovations R. Del Río et al.
43. Evolution of Forest Tree DBH Measurement Technologies: From Contact-Based Traditional Approaches to Remote Sensing Non-Contact Methods G. Zhang et al.
44. Comparison of ALS- and UAV(SfM)-derived high-density point clouds for individual tree detection in Eucalyptus plantations J. Guerra-Hernández et al.
45. Disturbance feedbacks on the height of woody vegetation in a savannah: a multi-plot assessment using an unmanned aerial vehicle (UAV) M. Mayr et al.
46. Convolutional Neural Networks accurately predict cover fractions of plant species and communities in Unmanned Aerial Vehicle imagery T. Kattenborn et al.
47. Highly Accurate Tree Models Derived from Terrestrial Laser Scan Data: A Method Description J. Hackenberg et al.
48. Mathematically optimized trajectory for terrestrial close-range photogrammetric 3D reconstruction of forest stands K. Kuželka & P. Surový
49. Aboveground biomass estimation in linear forest objects: 2D- vs. 3D-data S. LINGNER et al.
50. Assessment of Shoreline Transformation Rates and Landslide Monitoring on the Bank of Kuibyshev Reservoir (Russia) Using Multi-Source Data O. Yermolaev et al.
51. Customizing unmanned aircraft systems to reduce forest inventory costs: can oblique images substantially improve the 3D reconstruction of the canopy? G. Díaz et al.
52. Identifying species from the air: UAVs and the very high resolution challenge for plant conservation S. Baena et al.
53. When a definition makes the difference: operative issues about tree height measures from RPAS-derived CHMs S. De Petris et al.
54. CaR3DMIC: A novel method for evaluating UAV-derived 3D forest models by tree features A. Fakhri et al.
55. Trunk Model Establishment and Parameter Estimation for a Single Tree Using Multistation Terrestrial Laser Scanning C. Hu et al.
56. Augmentation of Traditional Forest Inventory and Airborne Laser Scanning with Unmanned Aerial Systems and Photogrammetry for Forest Monitoring K. Fankhauser et al.
57. Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities N. Guimarães et al.
58. Comparing terrestrial laser scanning and unmanned aerial vehicle structure from motion to assess top of canopy structure in tropical forests S. Roşca et al.
59. Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data J. Guerra-Hernández et al.
60. Individual Tree Crown Methods for 3D Data from Remote Sensing E. Lindberg & J. Holmgren
61. Testing the quality of forest variable estimation using dense image matching: a comparison with airborne laser scanning in a Mediterranean pine forest J. Navarro et al.
62. SLOAM: Semantic Lidar Odometry and Mapping for Forest Inventory S. Chen et al.
63. Use of Multi-Temporal UAV-Derived Imagery for Estimating Individual Tree Growth in Pinus pinea Stands J. Guerra-Hernández et al.
64. Accuracy of Structure from Motion models in comparison with terrestrial laser scanner for the analysis of DBH and height influence on error behaviour D. Panagiotidis et al.
65. The Use of a Hand-Held Camera for Individual Tree 3D Mapping in Forest Sample Plots X. Liang et al.
66. GNSS/INS-Assisted Structure from Motion Strategies for UAV-Based Imagery over Mechanized Agricultural Fields S. Hasheminasab et al.
67. UAV Photogrammetry of Forests as a Vulnerable Process. A Sensitivity Analysis for a Structure from Motion RGB-Image Pipeline J. Frey et al.
68. Drone-based photogrammetry for the construction of high-resolution models of individual trees C. Scher et al.
69. The determination of some stand parameters using SfM-based spatial 3D point cloud in forestry studies: an analysis of data production in pure coniferous young forest stands S. Gülci
70. Detection of Coniferous Seedlings in UAV Imagery C. Feduck et al.
71. Applicability of different non-invasive methods for tree mass estimation: A review S. Dittmann et al.
72. Graph-based methods for analyzing orchard tree structure using noisy point cloud data F. Westling et al.
73. Geometric and Radiometric Consistency of Parrot Sequoia Multispectral Imagery for Precision Agriculture Applications M. Franzini et al.
74. Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest M. Mohan et al.
75. High Throughput Phenotyping of Blueberry Bush Morphological Traits Using Unmanned Aerial Systems A. Patrick & C. Li
76. Classification of Basal Stem Rot Disease in Oil Palm Plantations Using Terrestrial Laser Scanning Data and Machine Learning N. Husin et al.
77. Influence of Drone Altitude, Image Overlap, and Optical Sensor Resolution on Multi-View Reconstruction of Forest Images E. Seifert et al.
78. Determining tree height and crown diameter from high-resolution UAV imagery D. Panagiotidis et al.
79. Comparison of UAS photogrammetric products for tree detection and characterization of coniferous stands S. Bonnet et al.
80. High-Resolution Airborne UAV Imagery to Assess Olive Tree Crown Parameters Using 3D Photo Reconstruction: Application in Breeding Trials R. Díaz-Varela et al.
81. 3D modelling of individual trees using a handheld camera: Accuracy of height, diameter and volume estimates J. Miller et al.
82. A review of data-driven key technologies for intelligent citrus systems W. Li et al.
83. Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy J. Tomaštík et al.
84. A Review of In-Situ and Remote Sensing Technologies to Monitor Water and Sanitation Interventions L. Andres et al.
85. How to Better Use Canopy Height in Soybean Biomass Estimation Y. Zhu et al.
86. Dry Biomass Estimation of Hedge Banks: Allometric Equation vs. Structure from Motion via Unmanned Aerial Vehicle S. LINGNER et al.
87. Stem Measurements and Taper Modeling Using Photogrammetric Point Clouds R. Fang & B. Strimbu
88. Forest Data Collection Using Terrestrial Image-Based Point Clouds From a Handheld Camera Compared to Terrestrial and Personal Laser Scanning X. Liang et al.
89. Forestry applications of UAVs in Europe: a review C. Torresan et al.
90. Issues in Unmanned Aerial Systems (UAS) Data Collection of Complex Forest Environments B. Fraser & R. Congalton