CLASSIFICATION OF AIRBORNE LASER SCANNING DATA IN WADDEN SEA AREAS USING CONDITIONAL RANDOM FIELDS

10 citations as recorded by crossref.

1. Linking Points With Labels in 3D: A Review of Point Cloud Semantic Segmentation Y. Xie et al. https://doi.org/10.1109/MGRS.2019.2937630
2. Using Multispectral Airborne LiDAR Data for Land/Water Discrimination: A Case Study at Lake Ontario, Canada S. Morsy et al. https://doi.org/10.3390/app8030349
3. Conditional Random Field Features and Structure Assessment for Digital Terrain Modeling T. Arevalo-Ramirez & F. Auat Cheein https://doi.org/10.1109/ACCESS.2021.3061371
4. Retrieval-and-alignment based large-scale indoor point cloud semantic segmentation Z. Xu et al. https://doi.org/10.1007/s11432-022-3928-x
5. Contextual Classification of Full Waveform Lidar Data in the Wadden Sea A. Schmidt et al. https://doi.org/10.1109/LGRS.2014.2302317
6. Large-scale classification of water areas using airborne topographic lidar data J. Smeeckaert et al. https://doi.org/10.1016/j.rse.2013.07.004
7. Automatic boundary extraction of inland water bodies using LiDAR data S. Canaz et al. https://doi.org/10.1016/j.ocecoaman.2015.07.024
8. The Use of Green Laser in LiDAR Bathymetry: State of the Art and Recent Advancements A. Szafarczyk & C. Toś https://doi.org/10.3390/s23010292
9. Processing and performance of topobathymetric lidar data for geomorphometric and morphological classification in a high-energy tidal environment M. Andersen et al. https://doi.org/10.5194/hess-21-43-2017
10. A spatial–spectral classification framework for multispectral LiDAR S. Shi et al. https://doi.org/10.1080/10095020.2023.2208611