Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Margot Verhulst"'
Publikováno v:
Remote Sensing, Vol 16, Iss 14, p 2653 (2024)
Detailed information on forest tree species is crucial to inform management and policy and support environmental and ecological research. Sentinel-2 imagery is useful for obtaining spatially explicit and frequent information on forest tree species du
Externí odkaz:
https://doaj.org/article/864ab7893d2a484f965ca33280808362
Publikováno v:
IGARSS
Data-driven environmental governance is gaining importance for tackling the current biodiversity and climate crises. Remote sensing can provide an efficient alternative to expensive and time-intensive in-situ monitoring. Deep learning is the current
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffe7088782cb05f8e6871ef4f5c2d4f6
https://doi.org/10.1109/igarss47720.2021.9554514
https://doi.org/10.1109/igarss47720.2021.9554514
Autor:
Stien Heremans, Margot Verhulst, Julie Callebaut, Francis Turkelboom, Ils Reusen, Tanja Van Achteren, Matthew Blashko, Ben Somers
Publikováno v:
Research Institute for Nature and Forest
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::4a69bbb00831e833e4252ee939360104
https://pureportal.inbo.be/portal/en/publications/towards-unlocking-the-potential-of-freely-available-copernicus-data-for-environmental-monitoring-through-spatiospectrotemporal-deep-learning(baab2c85-eacb-42b5-ad03-7d9479d92dd9).html
https://pureportal.inbo.be/portal/en/publications/towards-unlocking-the-potential-of-freely-available-copernicus-data-for-environmental-monitoring-through-spatiospectrotemporal-deep-learning(baab2c85-eacb-42b5-ad03-7d9479d92dd9).html
