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Mapping Biodiversity at Very-High Resolution in Europe

César Leblanc,Lukáš Picek,Benjamin Deneu,P. Bonnet,Maximilien Servajean,Rémi Palard,A. Joly

Published 2025 in 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

ABSTRACT

This paper describes a cascading multimodal pipeline for high-resolution biodiversity mapping across Europe, integrating species distribution modeling, biodiversity indicators, and habitat classification. The proposed pipeline first predicts species compositions using a deep-SDM, a multimodal model trained on remote sensing, climate time series, and species occurrence data at $50 \times 50 ~\mathrm{m}$ resolution. These predictions are then used to generate biodiversity indicator maps and classify habitats with Pl@ntBERT, a transformerbased LLM designed for species-to-habitat mapping. With this approach, continental-scale species distribution maps, biodiversity indicator maps, and habitat maps are produced, providing fine-grained ecological insights. Unlike traditional methods, this framework enables joint modeling of interspecies dependencies, bias-aware training with heterogeneous presence-absence data, and large-scale inference from multi-source remote sensing inputs.

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