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

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3 Author(s)
Kiyofuji, H. ; Graduate Sch. of Fisheries Sci, Hokkaido Univ., Japan ; Hokimoto, T. ; Saitoh, S.-I.

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 autocorrelation in time, we propose a new spatiotemporal model for chl-a distribution and its predictor. Numerical prediction experiments applying the SeaWiFS data showed that the predictor could forecast chl-a distributions in summer and early fall well, although further changes in the model structure will be necessary to predict aspects of the spring and late fall blooms.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:3 ,  Issue: 2 )