PyEOGPR: A Python package for vegetation trait mapping with Gaussian Process Regression on Earth observation cloud platforms.

Kovács DD, De Clerck E, Verrelst J

DOI: 10.1016/j.ecoinf.2025.103497
Published: 2025 Dec
Container: Ecological informatics
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1016/j.ecoinf.2025.103497,
  title = {PyEOGPR: A Python package for vegetation trait mapping with Gaussian Process Regression on Earth observation cloud platforms.},
  author = {Kovács DD and De Clerck E and Verrelst J},
  year = {2025},
  journal = {Ecological informatics},
  doi = {10.1016/j.ecoinf.2025.103497},
  url = {https://doi.org/10.1016/j.ecoinf.2025.103497}
}

RIS

TY  - JOUR
TI  - PyEOGPR: A Python package for vegetation trait mapping with Gaussian Process Regression on Earth observation cloud platforms.
AU  - Kovács DD
AU  - De Clerck E
AU  - Verrelst J
PY  - 2025
JO  - Ecological informatics
DO  - 10.1016/j.ecoinf.2025.103497
UR  - https://doi.org/10.1016/j.ecoinf.2025.103497
ER  -

APA

DD, K., E, D. C., & J, V. (2025). PyEOGPR: A Python package for vegetation trait mapping with Gaussian Process Regression on Earth observation cloud platforms.. Ecological informatics. https://doi.org/10.1016/j.ecoinf.2025.103497

Source records

pubmed · retrieved 2026-09-27T09:29:02.563Z