🚧This documentation is under construction. We will produce updates aprox. once a week. 🚧
🌿 Welcome to the GeoPlant Dataset Hub! 🌍
GeoPlant is a large-scale, multimodal dataset for spatial plant species prediction across Europe, combining expert-verified species observations with rich environmental context. It enables research, benchmarking, and applications in biodiversity, earth observation, and deep learning.
Figure 1. GeoPlant integrates over 5 million Presence-Only and 90,000 Presence-Absence records for 10,000+ European plant species, each linked with high-resolution satellite imagery, long-term climate and Landsat time series, and diverse environmental predictors. All data and benchmarks are openly available for SDM research.
🚀 Quick Start
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Dataset Overview: Learn about provided presence-absence and presence-only species data.
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Environmental Predictors: Explore different variables, e.g., satellite imagery, time series, climate, soil, land cover, and human footprint.
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Baselines & Benchmarking: See benchmark tasks, metrics, and baseline models.
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Resources & Download: Get links to Kaggle, Seafile, code, and the NeurIPS 2024 paper.
🔎 Key Resources
| Resource | Description | Link |
|---|---|---|
| 📄 Dataset Paper | NeurIPS 2024 paper detailing the dataset and benchmark | NeurIPS Paper (PDF) |
| 🧠 GitHub Repository | Codebase with data loaders, baseline models, and utilities | GeoPlant Repo |
| 🚀 Starter Notebooks | Baseline models, pipelines, and scripts | GeoPlant Code on Kaggle |
| 📦 Full Dataset | Full data including PO and environmental rasters | GeoPlant Seafile |