1 citations · 1 across the 4 of their papers we have counts for
4 papers
Super-Resolved Canopy Height Mapping from Sentinel-2 Time Series Using Airborne LiDAR HD Reference Data across Metropolitan France
Ekaterina Kalinicheva, Florian Helen, Stéphane Mermoz +2
Fine-scale forest monitoring is essential for understanding canopy structure and its dynamics, which are key indicators of carbon stocks, biodiversity, and forest health. Deep lear…
Multi-Layer Modeling of Dense Vegetation from Aerial LiDAR Scans
Ekaterina Kalinicheva, Loic Landrieu, Clément Mallet +1
The analysis of the multi-layer structure of wild forests is an important challenge of automated large-scale forestry. While modern aerial LiDARs offer geometric information across…
Predicting Vegetation Stratum Occupancy from Airborne LiDAR Data with Deep Learning
Ekaterina Kalinicheva, Loic Landrieu, Clément Mallet +1
We propose a new deep learning-based method for estimating the occupancy of vegetation strata from airborne 3D LiDAR point clouds. Our model predicts rasterized occupancy maps for…
Vegetation Stratum Occupancy Prediction from Airborne LiDAR 3D Point Clouds
Ekaterina Kalinicheva, Loic Landrieu, Clément Mallet +1
We propose a new deep learning-based method for estimating the occupancy of vegetation strata from 3D point clouds captured from an aerial platform. Our model predicts rasterized o…