ASSESSING THE FEASIBILITY OF UAV-BASED LIDAR FOR HIGH RESOLUTION FOREST CHANGE DETECTION

23 citations as recorded by crossref.

1. Weighted data fusion for UAV-borne 3D mapping with camera and line laser scanner B. Jutzi et al. 10.1080/19479832.2014.889228
2. An Advanced Framework for Multi-Scale Forest Structural Parameter Estimations Based on UAS-LiDAR and Sentinel-2 Satellite Imagery in Forest Plantations of Northern China X. Wu et al. 10.3390/rs14133023
3. Evaluating Sensor Fusion and Flight Parameters for Enhanced Plant Height Measurement in Dry Peas A. Bazrafkan et al. 10.3390/s25082436
4. Image classification-based ground filtering of point clouds extracted from UAV-based aerial photos V. Yilmaz et al. 10.1080/10106049.2016.1250825
5. Super-resolution and super-sensitivity of quantum LiDAR with a multi-photonic state and binary outcome photon counting measurement P. Sharma et al. 10.1364/JOSAB.507405
6. A hierarchical approach for refining point cloud quality of a low cost UAV LiDAR system in the urban environment B. Yang & J. Li 10.1016/j.isprsjprs.2021.11.022
7. Airborne LiDAR and Photogrammetric Point Cloud Fusion for Extraction of Urban Tree Metrics According to Street Network Segmentation W. Yang et al. 10.1109/ACCESS.2021.3094307
8. An Assessment of the Repeatability of Automatic Forest Inventory Metrics Derived From UAV-Borne Laser Scanning Data L. Wallace et al. 10.1109/TGRS.2014.2308208
9. Unmanned aerial systems for precision forest inventory purposes: A review and case study T. Goodbody et al. 10.5558/tfc2017-012
10. Rapid Forest Change Detection Using Unmanned Aerial Vehicles and Artificial Intelligence J. Xiang et al. 10.3390/f15091676
11. Novel UAV Flight Designs for Accuracy Optimization of Structure from Motion Data Products M. Mueller et al. 10.3390/rs15174308
12. Comparison of the performances of ground filtering algorithms and DTM generation from a UAV-based point cloud C. Serifoglu Yilmaz & O. Gungor 10.1080/10106049.2016.1265599
13. Drone lidar-derived surface complexity metrics as indicators of intertidal oyster reef condition M. Espriella et al. 10.1016/j.ecolind.2023.110190
14. An improved SIFT algorithm in the application of close-range Stereo image matching X. Zhang et al. 10.1088/1755-1315/46/1/012009
15. Unmanned aerial systems for photogrammetry and remote sensing: A review I. Colomina & P. Molina 10.1016/j.isprsjprs.2014.02.013
16. UAV‐derived habitat predictors contribute strongly to understanding avian species–habitat relationships on the Eastern Qinghai‐Tibetan Plateau A. Fritz et al. 10.1002/rse2.73
17. Observing Geomorphological Change on an Evolving Coastal Sand Dune Using SLAM-Based UAV LiDAR J. Sofonia et al. 10.1007/s41976-019-00021-x
18. Concept of an Innovative Autonomous Unmanned System for Bathymetric Monitoring of Shallow Waterbodies (INNOBAT System) M. Specht et al. 10.3390/en14175370
19. Detection of REEs with lightweight UAV-based hyperspectral imaging R. Booysen et al. 10.1038/s41598-020-74422-0
20. The Application of UASs in Forest Management and Monitoring: Challenges and Opportunities for Use in the Miombo Woodland H. Shamaoma et al. 10.3390/f13111812
21. Integration of Optical Remote Sensing and Laser Point Cloud for Forest Stock Estimation in Karst Mountainous Areas J. Zheng et al. 10.3390/f15122106
22. Evaluating Tree Detection and Segmentation Routines on Very High Resolution UAV LiDAR Data L. Wallace et al. 10.1109/TGRS.2014.2315649
23. Manned aircraft versus small unmanned aerial system—forestry remote sensing comparison utilizing lidar and structure-from-motion for forest carbon modeling and disturbance detection M. McClelland et al. 10.1117/1.JRS.14.022202