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Integrating camera imagery, crowdsourcing, and deep learning to improve high-frequency automated monitoring of snow at continental-to-global scales

Snow is important for local to global climate and surface hydrology, but spatial and temporal heterogeneity in the extent of snow cover make accurate, fine-scale mapping and monitoring of snow an enormous challenge. We took 184,453 daily near-surface images acquired by 133 automated cameras and proc...

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Detalles Bibliográficos
Autores principales: Kosmala, Margaret, Hufkens, Koen, Richardson, Andrew D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6307743/
https://www.ncbi.nlm.nih.gov/pubmed/30589858
http://dx.doi.org/10.1371/journal.pone.0209649