Cargando…
Neural Networks Technique for Filling Gaps in Satellite Measurements: Application to Ocean Color Observations
A neural network (NN) technique to fill gaps in satellite data is introduced, linking satellite-derived fields of interest with other satellites and in situ physical observations. Satellite-derived “ocean color” (OC) data are used in this study because OC variability is primarily driven by biologica...
Autores principales: | Krasnopolsky, Vladimir, Nadiga, Sudhir, Mehra, Avichal, Bayler, Eric, Behringer, David |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4706868/ https://www.ncbi.nlm.nih.gov/pubmed/26819586 http://dx.doi.org/10.1155/2016/6156513 |
Ejemplares similares
-
Gap-filling of ocean color over the tropical Indian Ocean using Monte-Carlo method
por: Modi, Aditi, et al.
Publicado: (2022) -
Filling the Observability Gap
por: Oram, Andy
Publicado: (2021) -
Atmospheric Correction of Satellite Ocean-Color Imagery During the PACE Era
por: Frouin, Robert J., et al.
Publicado: (2019) -
Global Estimation of Suspended Particulate Matter From Satellite Ocean Color Imagery
por: Wei, Jianwei, et al.
Publicado: (2021) -
Proxying economic activity with daytime satellite imagery: Filling data gaps across time and space
por: Lehnert, Patrick, et al.
Publicado: (2023)