Predicting the spatiotemporal chlorophyll-a distribution in the Sea of Japan based on SeaWiFS ocean color satellite data

We developed a new statistical spatiotemporal model for chlorophyll-a (chl-a) distribution over the Sea of Japan, derived from the satellite-based Sea-viewing Wide Field-of-view Sensor (SeaWiFS). Because preliminary analysis showed that the SeaWiFS data exhibit anisotropy in space and autocorrelatio...

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Veröffentlicht in:	IEEE geoscience and remote sensing letters 2006-04, Vol.3 (2), p.212-216
Hauptverfasser:	Kiyofuji, H., Hokimoto, T., Saitoh, S.-I.
Format:	Artikel
Sprache:	eng
Schlagworte:	Anisotropic magnetoresistance Aquaculture Autocorrelation Biological system modeling Chlorophyll data assimilation Equations forecasting Mathematical models Numerical prediction Ocean color Oceans Predictive models Satellites Sea of Japan Sea-viewing Wide Field-of-view Sensor Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Sensor phenomena and characterization Spatiotemporal phenomena spatiotemporal statistical model Springs Summer
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