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A robust fixed rank kriging method for improving the spatial completeness and accuracy of satellite SST products / Yuxin Zhu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 9 (September 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 9 (September 2015) . - pp 5021 - 5035 Titre : A robust fixed rank kriging method for improving the spatial completeness and accuracy of satellite SST products Type de document : Article/Communication Auteurs : Yuxin Zhu, Auteur ; Emily Lei Kang, Auteur ; Yanchen Bo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 5021 - 5035 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse multirésolution [Termes IGN] changement climatique [Termes IGN] climat terrestre [Termes IGN] erreur systématique [Termes IGN] exhaustivité des données [Termes IGN] image Aqua-MODIS [Termes IGN] interpolation linéaire [Termes IGN] krigeage [Termes IGN] méthode robuste [Termes IGN] température de surface de la mer Résumé : (Auteur) Sea surface temperature (SST) plays a vital role in the Earth's atmosphere and climate systems. Complete and accurate SST observations are in great demand for forecasting tropical cyclones and projecting climate change. Satellite remote sensing has been used to retrieve SST globally, but missing values and biased observations impose difficulties on practical applications of these satellite-derived SST data. Conventional spatial statistics methods such as kriging have been widely used to fill the gaps. However, when such conventional methods are used to analyze a massive satellite data set of size n, the inversion of the n × n covariance matrix may require O(n3) computations, which make the computation very intensive or even infeasible. The fixed rank kriging (FRK) performs dimension reduction through multiresolution wavelet analysis so that it can dramatically reduce the computation cost of various kriging methods. However, the FRK cannot directly be used for incomplete data over spatially irregular regions such as SSTs, and the potential bias in the satellite data is not addressed. In this paper, we construct a data-driven bias-correction model for the correction of the bias in satellite SSTs and develop a robust FRK (R-FRK) method so that the dimension reduction can be used to the satellite data in irregular regions with missing data. We implement the bias-correction model and the R-FRK to the level-3 mapped night Moderate Resolution Imaging Spectroradiometer SSTs. The accuracy of the resulting predictions is assessed using the colocated drifting buoy SST observations, in terms of mean bias (bias), root-mean-squared error, and R squared (R2). The spatial completeness is assessed by the availability of ocean pixels. The assessment results show that the spatially. Numéro de notice : A2015-530 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2416351 Date de publication en ligne : 17/04/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2416351 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77558 [article]

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