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Remote Sensing of Environment 112 (2008) 4242-4260
Inferring missing data in satellite chlorophyll maps using turbulent cascading
Claire Pottier ( ) 1, 2, Antonio Turiel 3, Veronique Garçon 1
(2008-12-04)

Oceanic turbulent flows develop complicated patterns, with eddies, filaments and shear currents. Although usually referred as chaotic, their inner organization is strongly hierarchical: turbulent flows develop cascades, which transfer properties such as energy or scalar density from larger to smaller scales. In this work, we present a novel algorithm based on the cascade and able to fill data gaps in satellite images (particularly, chlorophyll concentration maps). The first step is to show that cascade processes for chlorophyll-a concentration images take a simple, explicit form when an appropriate wavelet (here Battle-Lemarié of order 3) representation is used. A reconstruction algorithm exploiting the cascade structure is then given with a detailed description. We discuss the validity and quality of this algorithm when applied to SeaWiFS and MODIS-Aqua ocean color images. An application to merging data from multiple satellite missions is presented together with a demonstration of the benefit of this algorithm over two other merging methods.
1:  Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS)
CNRS : UMR5566 – Institut de recherche pour le développement [IRD] – CNES – Observatoire Midi-Pyrénées – INSU – Université Paul Sabatier [UPS] - Toulouse III
2:  Centre National d'Etudes Spatiales (CNES)
Ministère de l'Enseignement Supérieur et de la Recherche Scientifique
3:  Instituto de Ciencias del Mar (ICM)
Consejo Superior de Investigaciones Cientificas
Sciences of the Universe/Ocean, Atmosphere
Missing data – Oceanic phytoplankton – Satellite ocean color images – Turbulence cascading – Wavelet representation