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Found 4 papers, 1 papers with code
Modelling Species Distributions with Deep Learning to Predict Plant Extinction Risk and Assess Climate Change Impacts
Cross-validation yields average accuracies of 0. 61 for status classification and 0. 78 for binary classification.
AI-based Mapping of the Conservation Status of Orchid Assemblages at Global Scale
In Sumatra, we found good correspondence of protected areas with our indicators, but supplementing current IUCN assessments with status predictions results in alarming levels of species threat across the island.
The GeoLifeCLEF 2023 Dataset to evaluate plant species distribution models at high spatial resolution across Europe
We designed a European scale dataset covering around ten thousand plant species to calibrate and evaluate SDM predictions of species composition in space and time at high spatial resolution (~ten meters), and their spatial transferability.
Learning Sentinel-2 Spectral Dynamics for Long-Run Predictions Using Residual Neural Networks
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, spectral and temporal information.
