RANDOM FORESTS-BASED FEATURE SELECTION FOR LAND-USE CLASSIFICATION USING LIDAR DATA AND ORTHOIMAGERY

12 citations as recorded by crossref.

1. Analysing Urban Development Patterns in a Conflict Zone: A Case Study of Kabul V. Chaturvedi et al. 10.3390/rs12213662
2. Investigation of landslide-based road surface deformation in mountainous areas with single period UAV data M. Zeybek & S. Biçici 10.1080/10106049.2022.2142969
3. Classifying airborne bathymetry data using the Random Forest algorithm T. Kogut & M. Weistock 10.1080/2150704X.2019.1629710
4. Point Cloud Classification Algorithm Based on the Fusion of the Local Binary Pattern Features and Structural Features of Voxels Y. Li et al. 10.3390/rs13163156
5. Generation of Radiometric, Phenological Normalized Image Based on Random Forest Regression for Change Detection D. Seo et al. 10.3390/rs9111163
6. Prediction of fall risk among community-dwelling older adults using a wearable system T. Lockhart et al. 10.1038/s41598-021-00458-5
7. 3DMASC: Accessible, explainable 3D point clouds classification. Application to bi-spectral topo-bathymetric lidar data M. Letard et al. 10.1016/j.isprsjprs.2023.11.022
8. Review of Automatic Processing of Topography and Surface Feature Identification LiDAR Data Using Machine Learning Techniques Z. Gharineiat et al. 10.3390/rs14194685
9. Post-War Land Cover Changes and Fragmentation in Halgurd Sakran National Park (HSNP), Kurdistan Region of Iraq R. Hamad et al. 10.3390/land7010038
10. Application of Multi-Source Data for Mapping Plantation Based on Random Forest Algorithm in North China F. Wu et al. 10.3390/rs14194946
11. Applicability of multifractal features as global characteristics of WorldView-2 panchromatic satellite images W. Drzewiecki et al. 10.5721/EuJRS20164943
12. Assessing the Changes in the Moisture/Dryness of Water Cavity Surfaces in Imlili Sebkha in Southwestern Morocco by Using Machine Learning Classification in Google Earth Engine S. Hakdaoui et al. 10.3390/rs12010131