Cédric Vega
YOU?
Author Swipe
View article: First Report: Rapid assessment of forest area and volume impacted by the 2025 fires in Aude, France
First Report: Rapid assessment of forest area and volume impacted by the 2025 fires in Aude, France Open
3D canopy height models and optical remote sensing imagery combined with national forest inventory data enable rapid assessment of fire contours and associated forest attributes. In Aude, southwestern France, wildfires between June 26 and …
View article: Wood density variation in European forest species: drivers and implications for multiscale biomass and carbon assessment in France
Wood density variation in European forest species: drivers and implications for multiscale biomass and carbon assessment in France Open
Wood density is a key parameter for estimating forest biomass and carbon stocks. However, the magnitude and the drivers of wood density variation in temperate forests, and the implications of this variation for biomass and carbon assessmen…
View article: Sentinel-2 time series reveal species-specific responses in temperate conifer dieback
Sentinel-2 time series reveal species-specific responses in temperate conifer dieback Open
Silver fir (Abies alba Mill.), Norway spruce (Picea abies (L.) H. Karst) and Scots pine (Pinus sylvestris L.) tare major European conifers undergoing severe dieback. Large-scale, high-frequency monitoring with multispectral satellites usin…
View article: An outlook on the Rapid Decline of Carbon Sequestration in French Forests and associated reporting needs
An outlook on the Rapid Decline of Carbon Sequestration in French Forests and associated reporting needs Open
In this study, we present and discuss changes in carbon storage in the French forests from 1990 to 2022, derived from CITEPA statistics on forest carbon accounting, fed by National Forest Inventory (NFI) data collected through an extensive…
View article: Bayesian Averaging of Lidar-based AI Models for High-Resolution Canopy Height Mapping: Application in Post-Stratification of a Large-Scale Forest Inventory
Bayesian Averaging of Lidar-based AI Models for High-Resolution Canopy Height Mapping: Application in Post-Stratification of a Large-Scale Forest Inventory Open
The development of high-resolution mapping models for forest attributes, driven by machine and deep learning techniques, has resulted in the widespread availability of multiple information sources. While this abundance can potentially lead…
View article: Remote-sensing-based forest canopy height mapping: some models are useful, but might they provide us with even more insights when combined?
Remote-sensing-based forest canopy height mapping: some models are useful, but might they provide us with even more insights when combined? Open
The development of high-resolution mapping models for forest attributes based on remote sensing data combined with machine or deep learning techniques has become a prominent topic in the field of forest observation and monitoring. This has…
View article: Showcasing the effectiveness of GEDI footprints as first-phase sample for forest inventories based on double sampling for post-stratification
Showcasing the effectiveness of GEDI footprints as first-phase sample for forest inventories based on double sampling for post-stratification Open
International audience
View article: How reliable are remote sensing maps calibrated over large areas? A matter of scale?
How reliable are remote sensing maps calibrated over large areas? A matter of scale? Open
Remote sensing data are increasingly available and frequently used to produce forest attributes maps. The sampling strategy of the calibration plots may directly affect predictions and map qualities. The aim of this manuscript is to evalua…
View article: Remote sensing-based high-resolution mapping of the forest canopy height: some models are useful, but might they be even more if combined?
Remote sensing-based high-resolution mapping of the forest canopy height: some models are useful, but might they be even more if combined? Open
The development of high-resolution mapping models for forest attributes based on remote sensing data combined with machine or deep learning techniques, has become a prominent topic in the field of forest observation and monitoring. This ha…
View article: Combining satellite images with national forest inventory measurements for monitoring post-disturbance forest height growth
Combining satellite images with national forest inventory measurements for monitoring post-disturbance forest height growth Open
The understanding of forest growth is crucial for the preservation of forests in the future. Factors such as tree species, age, forest management and environmental conditions influence this growth.Tree height and age data can be combined t…
View article: Bayesian model averaging of AI models for the high resolution mapping of the forest canopy height
Bayesian model averaging of AI models for the high resolution mapping of the forest canopy height Open
The development of high resolution mapping models of forest attributes based on employing machine or deep learning techniques has increasingly accelerated in the last couple of years. The consequence of this is the widespread availabi…
View article: Using Structural Class Pairing to Address the Spatial Mismatch Between GEDI Measurements and NFI Plots
Using Structural Class Pairing to Address the Spatial Mismatch Between GEDI Measurements and NFI Plots Open
International audience
View article: A large-scale artificial forest tree population for sampling and estimation methods simulations
A large-scale artificial forest tree population for sampling and estimation methods simulations Open
The dataset utilized in the Simulation Study section of the article is generated for a 10 km x 10 km area. This artificial dataset is constructed by populating polygons with trees sourced from the NFI database, representing the stands of t…
View article: A large-scale artificial forest tree population for sampling and estimation methods simulations
A large-scale artificial forest tree population for sampling and estimation methods simulations Open
The dataset utilized in the Simulation Study section of the article is generated for a 10 km x 10 km area. This artificial dataset is constructed by populating polygons with trees sourced from the NFI database, representing the stands of t…
View article: FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and Global Ecosystem Dynamics Investigation (GEDI) data with a deep learning approach
FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and Global Ecosystem Dynamics Investigation (GEDI) data with a deep learning approach Open
The contribution of forests to carbon storage and biodiversity conservation highlights the need for accurate forest height and biomass mapping and monitoring. In France, forests are managed mainly by private owners and divided into small s…
View article: FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach
FORMS: Forest Multiple Source height, wood volume, and biomass maps in France at 10 to 30 m resolution based on Sentinel-1, Sentinel-2, and GEDI data with a deep learning approach Open
The contribution of forests to carbon storage and biodiversity conservation highlights the need for accurate forest height and biomass mapping and monitoring. In France, forests are managed mainly by private owners and divided into small s…
View article: Improving GEDI Footprint Geolocation using a High Resolution Digital Terrain Model
Improving GEDI Footprint Geolocation using a High Resolution Digital Terrain Model Open
GEDI (Global Ecosystem Dynamics Investigation) is a lidar system on-board the International Space Station designed to study forest ecosystems. However, GEDI footprint low accuracy geolocation is a major impediment to the optimal benefit of…
View article: Improving GEDI Footprint Geolocation using a High Resolution Digital Terrain Model
Improving GEDI Footprint Geolocation using a High Resolution Digital Terrain Model Open
GEDI (Global Ecosystem Dynamics Investigation) is a lidar system on-board the International Space Station designed to study forest ecosystems. However, GEDI footprint low accuracy geolocation is a major impediment to the optimal benefit of…
View article: Improving GEDI Footprint Geolocation Using a High-Resolution Digital Elevation Model
Improving GEDI Footprint Geolocation Using a High-Resolution Digital Elevation Model Open
Global Ecosystem Dynamics Investigation (GEDI) is a lidar system on-board the International Space Station designed to study forest ecosystems. However, GEDI footprint low accuracy geolocation is a major impediment to the optimal benefit of…
View article: High-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach
High-resolution canopy height map in the Landes forest (France) based on GEDI, Sentinel-1, and Sentinel-2 data with a deep learning approach Open
In intensively managed forests in Europe, where forests are divided into stands of small size and may show heterogeneity within stands, a high spatial resolution (10 - 20 meters) is arguably needed to capture the differences in canopy heig…