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

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1. A Review of Unoccupied Aerial Vehicle Use in Wetland Applications: Emerging Opportunities in Approach, Technology, and Data I. Dronova et al. 10.3390/drones5020045
2. Use of UAV oblique imaging for the detection of individual trees in residential environments Y. Lin et al. 10.1016/j.ufug.2015.03.003
3. Co-registration of multi-sensor UAV imagery. Case study: Boreal forest areas P. Martínez-Carricondo et al. 10.1080/02827581.2022.2084563
4. Concept of an Innovative Autonomous Unmanned System for Bathymetric Monitoring of Shallow Waterbodies (INNOBAT System) M. Specht et al. 10.3390/en14175370
5. 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. 10.1016/j.rse.2019.03.025
6. A multi-scale approach of fluvial biogeomorphic dynamics using photogrammetry B. Hortobágyi et al. 10.1016/j.jenvman.2016.08.069
7. Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices B. Strimbu et al. 10.3390/rs11161877
8. Inventory of Small Forest Areas Using an Unmanned Aerial System S. Puliti et al. 10.3390/rs70809632
9. Image-Based 3D Reconstruction for Posthurricane Residential Building Damage Assessment Z. Zhou et al. 10.1061/(ASCE)CP.1943-5487.0000480
10. Very High Density Point Clouds from UAV Laser Scanning for Automatic Tree Stem Detection and Direct Diameter Measurement K. Kuželka et al. 10.3390/rs12081236
11. Short Communication. Using high resolution UAV imagery to estimate tree variables in Pinus pinea plantation in Portugal J. Hernandez et al. 10.5424/fs/2016252-08895
12. Citrus rootstock evaluation utilizing UAV-based remote sensing and artificial intelligence Y. Ampatzidis et al. 10.1016/j.compag.2019.104900
13. Integrated fire severity–land cover mapping using very-high-spatial-resolution aerial imagery and point clouds J. Arkin et al. 10.1071/WF19008
14. 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. 10.3389/fpls.2019.01472
15. An Unsupervised Canopy-to-Root Pathing (UCRP) Tree Segmentation Algorithm for Automatic Forest Mapping J. Carpenter et al. 10.3390/rs14174274
16. A comparison of terrestrial and UAS sensors for measuring fuel hazard in a dry sclerophyll forest S. Hillman et al. 10.1016/j.jag.2020.102261
17. 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. 10.3390/drones5020043
18. Three‐dimensional digitization of the arid land plant Haloxylon ammodendron using a consumer‐grade camera H. Huang et al. 10.1002/ece3.4126
19. Use of unmanned aerial vehicles for the diagnosis of parasitic plant infestation at the crown level in Pinus hartwegii L. León-Bañuelos et al. 10.3832/ifor4002-016
20. Detection of Tree Species in Mixed Broad-Leaved Stands of Caspian Forests Using UAV Images (Case study: Darabkola Forest) m. Pourahmad et al. 10.29252/ifej.6.11.61
21. Simplifying UAV-Based Photogrammetry in Forestry: How to Generate Accurate Digital Terrain Model and Assess Flight Mission Settings F. Pessacg et al. 10.3390/f13020173
22. Using Unmanned Aerial Vehicles in Postfire Vegetation Survey Campaigns through Large and Heterogeneous Areas: Opportunities and Challenges J. Fernández-Guisuraga et al. 10.3390/s18020586
23. Analysis of Changes in Oil Palm Canopy Architecture From Basal Stem Rot Using Terrestrial Laser Scanner N. Azuan et al. 10.1094/PDIS-10-18-1721-RE
24. Assessment of Using UAV Photogrammetry Based DEM and Ground-Measurement Based DEM in Computer-Assisted Forest Road Design İ. TAŞ et al. 10.33904/ejfe.1312514
25. 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. 10.1007/s00367-020-00665-5
26. Estimating tree heights with images from an unmanned aerial vehicle A. Birdal et al. 10.1080/19475705.2017.1300608
27. Assessment of camera focal length influence on canopy reconstruction quality M. Denter et al. 10.1016/j.ophoto.2022.100025
28. Acquisition of Forest Attributes for Decision Support at the Forest Enterprise Level Using Remote-Sensing Techniques—A Review P. Surový & K. Kuželka 10.3390/f10030273
29. Application of UAV photogrammetry for the assessment of forest structure and species network in the tropical forests of Southern Nigeria S. Akinbiola et al. 10.1080/10106049.2023.2190621
30. A Deformable Shape Model for Automatic and Real-Time Dendrometry L. Wells & W. Chung 10.3390/f14122299
31. Uncertainty in Parameterizing Floodplain Forest Friction for Natural Flood Management, Using Remote Sensing A. Antonarakis & D. Milan 10.3390/rs12111799
32. Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds F. Brieger et al. 10.3390/rs11121447
33. Assessing lean and positional error of individual mature Douglas-fir (Pseudotsuga menziesii) trees using active and passive sensors C. Garms et al. 10.1139/cjfr-2020-0041
34. Evaluation of UAV- and GNSS-Based DEMs for Earthwork Volume M. Akgul et al. 10.1007/s13369-017-2811-9
35. Photogrammetry and Remote Sensing for the identification and characterization of trees in urban areas. M. Mueed Choudhury et al. 10.1088/1742-6596/1249/1/012008
36. A comparison between TLS and UAS LiDAR to represent eucalypt crown fuel characteristics S. Hillman et al. 10.1016/j.isprsjprs.2021.09.008
37. Unmanned aerial systems for photogrammetry and remote sensing: A review I. Colomina & P. Molina 10.1016/j.isprsjprs.2014.02.013
38. Urban Tree Species Identification and Carbon Stock Mapping for Urban Green Planning and Management M. Choudhury et al. 10.3390/f11111226
39. Combination of UAV Photogrammetry and Field Inventories Enables Description of Height–Diameter Relationship within Semi-Arid Silvopastoral Systems A. Fakhri et al. 10.3390/rs15215261
40. Analysing the potential of UAV point cloud as input in quantitative structure modelling for assessment of woody biomass of single trees N. Ye et al. 10.1016/j.jag.2019.05.010
41. Comparison of ALS- and UAV(SfM)-derived high-density point clouds for individual tree detection in Eucalyptus plantations J. Guerra-Hernández et al. 10.1080/01431161.2018.1486519
42. 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. 10.1080/01431161.2017.1362132
43. Convolutional Neural Networks accurately predict cover fractions of plant species and communities in Unmanned Aerial Vehicle imagery T. Kattenborn et al. 10.1002/rse2.146
44. Highly Accurate Tree Models Derived from Terrestrial Laser Scan Data: A Method Description J. Hackenberg et al. 10.3390/f5051069
45. Mathematically optimized trajectory for terrestrial close-range photogrammetric 3D reconstruction of forest stands K. Kuželka & P. Surový 10.1016/j.isprsjprs.2021.06.013
46. Aboveground biomass estimation in linear forest objects: 2D- vs. 3D-data S. LINGNER et al. 10.17221/106/2018-JFS
47. Assessment of Shoreline Transformation Rates and Landslide Monitoring on the Bank of Kuibyshev Reservoir (Russia) Using Multi-Source Data O. Yermolaev et al. 10.3390/rs13214214
48. Customizing unmanned aircraft systems to reduce forest inventory costs: can oblique images substantially improve the 3D reconstruction of the canopy? G. Díaz et al. 10.1080/01431161.2019.1706200
49. Identifying species from the air: UAVs and the very high resolution challenge for plant conservation S. Baena et al. 10.1371/journal.pone.0188714
50. When a definition makes the difference: operative issues about tree height measures from RPAS-derived CHMs S. De Petris et al. 10.3832/ifor3411-013
51. CaR3DMIC: A novel method for evaluating UAV-derived 3D forest models by tree features A. Fakhri et al. 10.1016/j.isprsjprs.2024.01.012
52. Trunk Model Establishment and Parameter Estimation for a Single Tree Using Multistation Terrestrial Laser Scanning C. Hu et al. 10.1109/ACCESS.2020.2998806
53. Augmentation of Traditional Forest Inventory and Airborne Laser Scanning with Unmanned Aerial Systems and Photogrammetry for Forest Monitoring K. Fankhauser et al. 10.3390/rs10101562
54. Forestry Remote Sensing from Unmanned Aerial Vehicles: A Review Focusing on the Data, Processing and Potentialities N. Guimarães et al. 10.3390/rs12061046
55. Comparing terrestrial laser scanning and unmanned aerial vehicle structure from motion to assess top of canopy structure in tropical forests S. Roşca et al. 10.1098/rsfs.2017.0038
56. Predicting Growing Stock Volume of Eucalyptus Plantations Using 3-D Point Clouds Derived from UAV Imagery and ALS Data J. Guerra-Hernández et al. 10.3390/f10100905
57. Individual Tree Crown Methods for 3D Data from Remote Sensing E. Lindberg & J. Holmgren 10.1007/s40725-017-0051-6
58. 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. 10.1080/01431161.2018.1471551
59. SLOAM: Semantic Lidar Odometry and Mapping for Forest Inventory S. Chen et al. 10.1109/LRA.2019.2963823
60. Use of Multi-Temporal UAV-Derived Imagery for Estimating Individual Tree Growth in Pinus pinea Stands J. Guerra-Hernández et al. 10.3390/f8080300
61. Mapping the 3D structure of almond trees using UAV acquired photogrammetric point clouds and object-based image analysis J. Torres-Sánchez et al. 10.1016/j.biosystemseng.2018.10.018
62. 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. 10.17221/92/2015-JFS
63. Unmanned aerial vehicle and artificial intelligence revolutionizing efficient and precision sustainable forest management T. Liu et al. 10.1016/j.jclepro.2021.127546
64. Comparison between point cloud and mesh models using images from an unmanned aerial vehicle H. Park & D. Lee 10.1016/j.measurement.2019.02.023
65. The Use of a Hand-Held Camera for Individual Tree 3D Mapping in Forest Sample Plots X. Liang et al. 10.3390/rs6076587
66. GNSS/INS-Assisted Structure from Motion Strategies for UAV-Based Imagery over Mechanized Agricultural Fields S. Hasheminasab et al. 10.3390/rs12030351
67. UAV Photogrammetry of Forests as a Vulnerable Process. A Sensitivity Analysis for a Structure from Motion RGB-Image Pipeline J. Frey et al. 10.3390/rs10060912
68. Drone-based photogrammetry for the construction of high-resolution models of individual trees C. Scher et al. 10.1007/s00468-019-01866-x
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 10.1007/s10661-019-7628-4
70. Detection of Coniferous Seedlings in UAV Imagery C. Feduck et al. 10.3390/f9070432
71. Applicability of different non-invasive methods for tree mass estimation: A review S. Dittmann et al. 10.1016/j.foreco.2017.05.013
72. Graph-based methods for analyzing orchard tree structure using noisy point cloud data F. Westling et al. 10.1016/j.compag.2021.106270
73. Geometric and Radiometric Consistency of Parrot Sequoia Multispectral Imagery for Precision Agriculture Applications M. Franzini et al. 10.3390/app9245314
74. Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest M. Mohan et al. 10.3390/f8090340
75. High Throughput Phenotyping of Blueberry Bush Morphological Traits Using Unmanned Aerial Systems A. Patrick & C. Li 10.3390/rs9121250
76. Classification of Basal Stem Rot Disease in Oil Palm Plantations Using Terrestrial Laser Scanning Data and Machine Learning N. Husin et al. 10.3390/agronomy10111624
77. Influence of Drone Altitude, Image Overlap, and Optical Sensor Resolution on Multi-View Reconstruction of Forest Images E. Seifert et al. 10.3390/rs11101252
78. Determining tree height and crown diameter from high-resolution UAV imagery D. Panagiotidis et al. 10.1080/01431161.2016.1264028
79. Comparison of UAS photogrammetric products for tree detection and characterization of coniferous stands S. Bonnet et al. 10.1080/01431161.2017.1338839
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. 10.3390/rs70404213
81. RPAS-based photogrammetry to support tree stability assessment: Longing for precision arboriculture S. De Petris et al. 10.1016/j.ufug.2020.126862
82. 3D modelling of individual trees using a handheld camera: Accuracy of height, diameter and volume estimates J. Miller et al. 10.1016/j.ufug.2015.09.001
83. Accuracy of Photogrammetric UAV-Based Point Clouds under Conditions of Partially-Open Forest Canopy J. Tomaštík et al. 10.3390/f8050151
84. A Review of In-Situ and Remote Sensing Technologies to Monitor Water and Sanitation Interventions L. Andres et al. 10.3390/w10060756
85. Dry Biomass Estimation of Hedge Banks: Allometric Equation vs. Structure from Motion via Unmanned Aerial Vehicle S. LINGNER et al. 10.17221/152/2017-JFS
86. Stem Measurements and Taper Modeling Using Photogrammetric Point Clouds R. Fang & B. Strimbu 10.3390/rs9070716
87. Forest Data Collection Using Terrestrial Image-Based Point Clouds From a Handheld Camera Compared to Terrestrial and Personal Laser Scanning X. Liang et al. 10.1109/TGRS.2015.2417316
88. Forestry applications of UAVs in Europe: a review C. Torresan et al. 10.1080/01431161.2016.1252477
89. Issues in Unmanned Aerial Systems (UAS) Data Collection of Complex Forest Environments B. Fraser & R. Congalton 10.3390/rs10060908