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GeoPl@ntNet: A Platform for Exploring Essential Biodiversity Variables

arXiv 2511.13790 ↗First posted 16 Nov 2025q-bio.QM cs.AIcited by 0

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Abstract (arXiv)

This paper describes GeoPl@ntNet, an interactive web application designed to make Essential Biodiversity Variables accessible and understandable to everyone through dynamic maps and fact sheets. Its core purpose is to allow users to explore high-resolution AI-generated maps of species distributions, habitat types, and biodiversity indicators across Europe. These maps, developed through a cascading pipeline involving convolutional neural networks and large language models, provide an intuitive yet information-rich interface to better understand biodiversity, with resolutions as precise as 50x50 meters. The website also enables exploration of specific regions, allowing users to select areas of interest on the map (e.g., urban green spaces, protected areas, or riverbanks) to view local species and their coverage. Additionally, GeoPl@ntNet generates comprehensive reports for selected regions, including insights into the number of protected species, invasive species, and endemic species.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 29 references that are in the map. First posted on arXiv 16 Nov 2025.

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7 of 29 references.

References · 7

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2020Conformal Prediction: a Unified Review of Theory and New Challengescited by 118
  3. 2023Spatial Implicit Neural Representations for Global-Scale Species Mappingcited by 59
  4. 2024GeoPlant: Spatial Plant Species Prediction Datasetcited by 16
  5. 2024Fully automatic extraction of morphological traits from the Web: utopia or reality?cited by 2
  6. 2025Overview of GeoLifeCLEF 2023: Species Composition Prediction with High Spatial Resolution at Continental Scale Using Remote Sensingcited by 2
  7. 2025Mapping biodiversity at very-high resolution in Europecited by 1

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