VERTICAL VEGETATION STRUCTURE ANALYSIS AND HYDRAULIC ROUGHNESS DETERMINATION USING DENSE ALS POINT CLOUD DATA - A VOXEL BASED APPROACH

9 citations as recorded by crossref.

1. The Use of LiDAR-Derived DEM in Flood Applications: A Review N. Muhadi et al. https://doi.org/10.3390/rs12142308
2. Deriving Floodplain Topography and Vegetation Characteristics for Hydraulic Engineering Applications by Means of Terrestrial Laser Scanning J. Jalonen et al. https://doi.org/10.1061/(ASCE)HY.1943-7900.0000928
3. Understanding flood regime changes in Europe: a state-of-the-art assessment J. Hall et al. https://doi.org/10.5194/hess-18-2735-2014
4. Multiscale analysis of surface roughness for the improvement of natural hazard modelling N. Brožová et al. https://doi.org/10.5194/nhess-21-3539-2021
5. Maize LAI Retrieval Using PointNet++ and Transfer Learning with Integrated 3D Radiative Transfer Modeling and LiDAR Point Clouds Q. Li et al. https://doi.org/10.3390/rs18101660
6. Identification of Riparian Vegetation Types with Machine Learning Based on LiDAR Point-Cloud Made Along the Lower Tisza’s Floodplain I. Fehérváry & T. Kiss https://doi.org/10.2478/jengeo-2020-0006
7. Airborne LiDAR-assisted deep learning methodology for riparian land cover classification using aerial photographs and its application for flood modelling K. Yoshida et al. https://doi.org/10.2166/hydro.2022.134
8. Estimation of distributed flow resistance in vegetated rivers using airborne topo‐bathymetric LiDAR and its application to risk management tasks for Asahi River flooding K. Yoshida et al. https://doi.org/10.1111/jfr3.12584
9. Assessing entrepreneurial and regional‐economic flood impacts on a globalized production facility C. Pfurtscheller & M. Vetter https://doi.org/10.1111/jfr3.12102