Cédric Véga
Orcid: 0000-0002-2740-8845
According to our database1,
Cédric Véga
authored at least 15 papers
between 2011 and 2024.
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Collaborative distances:
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Bibliography
2024
Using Structural Class Pairing to Address the Spatial Mismatch Between GEDI Measurements and NFI Plots.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024
2023
Improving GEDI Footprint Geolocation Using a High-Resolution Digital Elevation Model.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2023
2022
High-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach.
CoRR, 2022
Modelling forest volume with small area estimation of forest inventory using GEDI footprints as auxiliary information.
Int. J. Appl. Earth Obs. Geoinformation, 2022
Int. J. Appl. Earth Obs. Geoinformation, 2022
2021
A new small area estimation algorithm to balance between statistical precision and scale.
Int. J. Appl. Earth Obs. Geoinformation, 2021
2019
Increasing Precision for French Forest Inventory Estimates using the k-NN Technique with Optical and Photogrammetric Data and Model-Assisted Estimators.
Remote. Sens., 2019
2018
Surface reconstruction of incomplete datasets: A novel Poisson surface approach based on CSRBF.
Comput. Graph., 2018
2017
Terrain Model Reconstruction from Terrestrial LiDAR Data Using Radial Basis Functions.
IEEE Computer Graphics and Applications, 2017
2015
Remote. Sens., 2015
2014
Int. J. Appl. Earth Obs. Geoinformation, 2014
2013
Stem Volume and Above-Ground Biomass Estimation of Individual Pine Trees From LiDAR Data: Contribution of Full-Waveform Signals.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2013
2012
A sequential iterative dual-filter for Lidar terrain modeling optimized for complex forested environments.
Comput. Geosci., 2012
2011
Multi-level filtering segmentation to measure individual tree parameters based on Lidar data: Application to a mountainous forest with heterogeneous stands.
Int. J. Appl. Earth Obs. Geoinformation, 2011
Exploiting fullwaveform lidar signals to estimate timber volume and above-ground biomass of individual trees.
Proceedings of the 2011 IEEE International Geoscience and Remote Sensing Symposium, 2011