4 citations · 10 across the 5 of their papers we have counts for
5 papers
Overview of GeoLifeCLEF 2023: Species Composition Prediction with High Spatial Resolution at Continental Scale Using Remote Sensing
Christophe Botella, Benjamin Deneu, Diego Marcos +6
Understanding the spatio-temporal distribution of species is a cornerstone of ecology and conservation. By pairing species observations with geographic and environmental predictors…
Modelling Species Distributions with Deep Learning to Predict Plant Extinction Risk and Assess Climate Change Impacts
Joaquim Estopinan, Pierre Bonnet, Maximilien Servajean +2
The post-2020 global biodiversity framework needs ambitious, research-based targets. Estimating the accelerated extinction risk due to climate change is critical. The International…
AI-based Mapping of the Conservation Status of Orchid Assemblages at Global Scale
Joaquim Estopinan, Maximilien Servajean, Pierre Bonnet +2
Although increasing threats on biodiversity are now widely recognised, there are no accurate global maps showing whether and where species assemblages are at risk. We hereby assess…
The GeoLifeCLEF 2023 Dataset to evaluate plant species distribution models at high spatial resolution across Europe
Christophe Botella, Benjamin Deneu, Diego Marcos +6
The difficulty to measure or predict species community composition at fine spatio-temporal resolution and over large spatial scales severely hampers our ability to understand speci…
Learning Sentinel-2 Spectral Dynamics for Long-Run Predictions Using Residual Neural Networks
Joaquim Estopinan, Guillaume Tochon, Lucas Drumetz
Making the most of multispectral image time-series is a promising but still relatively under-explored research direction because of the complexity of jointly analyzing spatial, spe…