EVALUATING ERROR OF LIDAR DERIVED DEM INTERPOLATION FOR VEGETATION AREA

9 citations as recorded by crossref.

1. Crop type mapping using LiDAR, Sentinel-2 and aerial imagery with machine learning algorithms A. Prins & A. Van Niekerk 10.1080/10095020.2020.1782776
2. A Process-Oriented Method for Rapid Acquisition of Canopy Height Model From RGB Point Cloud in Semiarid Region Y. Tian et al. 10.1109/JSTARS.2021.3129472
3. UAV-LiDAR Measurement of Vegetation Canopy Structure Parameters and Their Impact on Land–Air Exchange Simulation Based on Noah-MP Model G. Wu et al. 10.3390/rs14132998
4. Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation K. HASTAOĞLU et al. 10.26833/ijeg.940997
5. Estimation of biogenic volatile organic compound (BVOC) emissions in forest ecosystems using drone-based lidar, photogrammetry, and image recognition technologies X. Duan et al. 10.5194/amt-17-4065-2024
6. A Hybrid Process/Thread Parallel Algorithm for Generating DEM from LiDAR Points Y. Ren et al. 10.3390/ijgi6100300
7. Accuracy of Ground Surface Interpolation from Airborne Laser Scanning (ALS) Data in Dense Forest Cover M. Cățeanu & A. Ciubotaru 10.3390/ijgi9040224
8. The Effect of LiDAR Sampling Density on DTM Accuracy for Areas with Heavy Forest Cover M. Cățeanu & A. Ciubotaru 10.3390/f12030265
9. Evaluating the performance of various interpolation techniques on digital elevation models in highly dense forest vegetation environment S. Adedapo & H. Zurqani 10.1016/j.ecoinf.2024.102646