Evaluation of Deep Species Distribution Models Using Environment and Co-occurrences
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Deep learning methods have started to be employed to model species' ecological niches, facilitated by the development of machine-learning-ready datasets such as GeoLifeCLEF.
“Recently, DL methods have also started to be employed to model species’ ecological niches82,145, facilitated by the development of machine-learning-ready datasets such as GeoLifeCLEF.”
From Perspectives in machine learning for wildlife conservation (2022) · cites this paper as [82]
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Cites
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Perspectives in machine learning for wildlife conservation
Tuia, D., Kellenberger, B., Beery, S., Costelloe, B. R., Zuffi, S., Risse, B., Mathis, A., Mathis, M. W., van Langevelde, F., Burghardt, T., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-27980-y · Cited by 740 · see citing works
Species Distribution Modeling for Machine Learning Practitioners: A Review
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- Authors
- Deneu, B., Servajean, M., Botella, C., & Joly, A.
- Affiliations
- Institut national de recherche en sciences et technologies du numérique (FR)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Deneu, Benjamin
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2019
- Volume
- 11696
- Pages
- 213-225
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2971315579
- Cited by
- 8
- References
- 20
- Citations by year
- 2024: 2 · 2023: 1 · 2022: 3 · 2021: 1 · 2019: 1
- FWCI
- 3.76
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- HAL (submittedVersion, cc-by)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Botany and Plant Ecology Studies
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
- Keywords
- co-occurrence data, environmental variables, model evaluation, end-to-end neural network, species distribution prediction
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