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metadata
license: mit
language:
  - en
pretty_name: EcoWikiRS
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: id
      dtype: string
    - name: EUNIS
      dtype:
        class_label:
          names:
            '0': '14'
            '1': '15'
            '2': '16'
            '3': '21'
            '4': '23'
            '5': '24'
            '6': '25'
            '7': '26'
            '8': '31'
            '9': '32'
            '10': '40'
            '11': '41'
            '12': '43'
            '13': '44'
            '14': '45'
            '15': '47'
            '16': '48'
            '17': '49'
            '18': '50'
            '19': '52'
            '20': '53'
            '21': '54'
            '22': '55'
            '23': '56'
            '24': '57'
    - name: species_list
      list: string
    - name: image
      dtype: image
    - name: species_text
      dtype: string
  splits:
    - name: train
      num_bytes: 6206448837
      num_examples: 58230
    - name: validation
      num_bytes: 618946914
      num_examples: 6172
    - name: test
      num_bytes: 2829427476
      num_examples: 27398
  download_size: 7798126881
  dataset_size: 9654823227

EcoWikiRS: Learning Ecological Representations of Satellite Images from Weak Supervision with Species Observations and Wikipedia

Authors
Valerie Zermatten · Javiera Castillo-Navarro · Pallavi Jain · Devis Tuia · Diego Marcos

arXiv GitHub DOI

Overview

The WikiRS dataset, composed of triplets of images, species list and Wikipedia sentences :

  • 91k high-resolution aerial images (50cm, RGB bands) from the swissIMAGE product
  • crowd-sourced species observations from 2745 different species, collected from GBIF, geolocated within the footprint of the aerial image.
  • 103K different sentences describing the habitat of the observed species, extracted from the corresponding Wikipedia article.

Data formats in this repository

1. Original raw data

  • In ecowikirs.zip
  • Original data structure used in the codebase and archived on Zenodo
  • Intended for full reproducibility

2. Hugging Face processed version

  • In the data/ directory
  • Automatically loaded via load_dataset("EPFL-ECEO/EcoWikiRS")

HF Features

  • id (string): Unique site/sample identifier
  • EUNIS (ClassLabel): Habitat class label. Original codes remapped to contiguous indices to handle gaps.
  • species_list (list[string]): All species recorded at the site.
  • image (Image): PIL image from TIFF file (swissimage/{id}.tif in the raw data).
  • species_text (json string): Aggregated JSON data per species (from wiki/{species_name}.json in the raw data), keyed by binomial_name, including keywords, habitat_section, and random_sentences.

Notes

EUNIS labels have been remapped in the Hugging Face processed version to contiguous integers. The mapping is the following: {0: 14, 1: 15, 2: 16, 3: 21, 4: 23, 5: 24, 6: 25, 7: 26, 8: 31, 9: 32, 10: 40, 11: 41, 12: 43, 13: 44, 14: 45, 15: 47, 16: 48, 17: 49, 18: 50, 19: 52, 20: 53, 21: 54, 22: 55, 23: 56, 24: 57}

How to cite this work: 

@InProceedings{Zermatten_2025_WikiRS,
    author    = { Zermatten, Valerie and Castillo-Navarro, Javiera and Jain, Pallavi and Tuia, Devis and Marcos, Diego},
    title     = {EcoWikiRS: Learning Ecological Representations of Satellite Images from Weak Supervision with Species Observations and Wikipedia},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
    month     = {June},
    year      = {2025},
    pages     = {00-00}
}

Additional data information

  • More information on the EUNIS ecosystem type map is available on the European Environment Agency website : Ecosystem type map (all classes).

  • The raw aerial images with 10cm resolution from the swissIMAGE product can be openly downloaded from the swisstopo website

Contacts & Information