UNMANNED AERIAL VEHICLES PRODUCE HIGH-RESOLUTION, SEASONALLY-RELEVANT IMAGERY FOR CLASSIFYING WETLAND VEGETATION

20 citations as recorded by crossref.

1. GIS-based detection of terraced landscape heritage: comparative tests using regional DEMs and UAV data A. Spanò et al. https://doi.org/10.1007/s12518-018-0205-7
2. The contribution of Earth observation technologies to the reporting obligations of the Habitats Directive and Natura 2000 network in a protected wetland A. Regos & J. Domínguez https://doi.org/10.7717/peerj.4540
3. Application of unmanned aerial vehicles in earth resources monitoring: focus on evaluating potentials for forest monitoring in Ethiopia H. Berie & I. Burud https://doi.org/10.1080/22797254.2018.1432993
4. Modelling heights of sparse aquatic reed (Phragmites australis) using Structure from Motion point clouds derived from Rotary- and Fixed-Wing Unmanned Aerial Vehicle (UAV) data N. Meneses et al. https://doi.org/10.1016/j.limno.2018.07.001
5. Combination of Aerial, Satellite, and UAV Photogrammetry for Mapping the Diachronic Coastline Evolution: The Case of Lefkada Island K. Nikolakopoulos et al. https://doi.org/10.3390/ijgi8110489
6. Classification of Eurasian Watermilfoil (Myriophyllum spicatum) Using Drone-Enabled Multispectral Imagery Analysis C. Brooks et al. https://doi.org/10.3390/rs14102336
7. A novel strategy for estimating biomass of submerged aquatic vegetation in lake integrating UAV and Sentinel data L. Lu et al. https://doi.org/10.1016/j.scitotenv.2023.169404
8. Drones for Conservation in Protected Areas: Present and Future J. Jiménez López & M. Mulero-Pázmány https://doi.org/10.3390/drones3010010
9. Remote Sensing of Wetlands in the Prairie Pothole Region of North America J. Montgomery et al. https://doi.org/10.3390/rs13193878
10. Quantification of Extent, Density, and Status of Aquatic Reed Beds Using Point Clouds Derived from UAV–RGB Imagery N. Corti Meneses et al. https://doi.org/10.3390/rs10121869
11. Fusion of UAV-Acquired Visible Images and Multispectral Data by Applying Machine-Learning Methods in Crop Classification Z. Zheng et al. https://doi.org/10.3390/agronomy14112670
12. Mapping Coastal Wetland Biomass from High Resolution Unmanned Aerial Vehicle (UAV) Imagery C. Doughty & K. Cavanaugh https://doi.org/10.3390/rs11050540
13. AqUavplant Dataset: A High-Resolution Aquatic Plant Classification and Segmentation Image Dataset Using UAV M. Istiak et al. https://doi.org/10.1038/s41597-024-04155-6
14. Unoccupied Aircraft Systems (UAS) for Marine Ecosystem Restoration J. Ridge & D. Johnston https://doi.org/10.3389/fmars.2020.00438
15. Multiscale collection and analysis of submerged aquatic vegetation spectral profiles for Eurasian watermilfoil detection C. Brooks et al. https://doi.org/10.1117/1.JRS.13.037501
16. Quantifying Vegetation and Landscape Metrics with Hyperspatial Unmanned Aircraft System Imagery in a Coastal Oligohaline Marsh W. Broussard et al. https://doi.org/10.1007/s12237-020-00828-8
17. Sensemaking in the Wild: A Review of Practitioner Collected Geospatial Data and its Synthesis within Protected Areas for Poaching Mitigation W. Zeller Zigaitis & A. robinson https://doi.org/10.1080/19475683.2023.2192761
18. Rapid assessment of wetland ecosystem services (RAWES) in wetland offsetting for urban developments: an example from Valenzuela City, Philippines A. Lecciones et al. https://doi.org/10.1088/2515-7620/ae4857
19. Using Uncrewed Aerial Vehicles for Identifying the Extent of Invasive Phragmites australis in Treatment Areas Enrolled in an Adaptive Management Program C. Brooks et al. https://doi.org/10.3390/rs13101895
20. Examination of Drone Usage in Estimating Hardwood Plantations Structural Metrics T. Corbin & M. Bataineh https://doi.org/10.1007/s13157-024-01807-6