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Data fusion in data scarce areas using a back-propagation artificial neural network model： a case study of the South China Sea

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Frontiers of Earth Science 2018年第2期12卷 280-298页

作者： Zheng WANG Zhihua MAO Junshi XIA Peijun DU Liangliang SHI Haiqing HUANG Tianyu WANG Fang GONG Qiankun ZHU School of Geographic and Oceanographic Sciences Nanjing University Nanjing 210023 China Collaborative Innovation Center for the South China Sea Studies Nanjing University Nanjing 210023 China States Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of Oceanography State Oceanic Administration Hangzhou 310012 China Research Center for Advanced Science and Technology The University of Tokyo Tokyo 153-8904 Japan Ocean College Zhejiang University Hangzhou 310058 China

The cloud cover for the South China Sea andits coastal area is relatively large throughout the year,which limits the potential application of optical remotesensing. A H J-charge-coupled device （HJ-CCD） has theadvantages of wide field, high temporal resolution, andshort repeat cycle. However, this instrument suffers fromits use of only four relatively low-quality bands whichcan＇t adequately resolve the features of long *** Landsat Enhanced Thematic Mapper-plus （ETM＋）provides high-quality data, however, the Scan LineCorrector （SLC） stopped working and caused striping ofremote sensed images, which dramatically reduced thecoverage of the ETM＋ data. In order to combine theadvantages of the HJ-CCD and Landsat ETM＋ data, weadopted a back-propagation artificial neural network （bp-ann） to fuse these two data types for this study. Theresults showed that the fused output data not only have theadvantage of data intactness for the HJ-CCD, but also havethe advantages of the multi-spectral and high radiometricresolution of the ETM＋ data. Moreover, the fused datawere analyzed qualitatively, quantitatively and from apractical application point of view. Experimental studiesindicated that the fused data have a full spatial distribution,multi-spectral bands, high radiometric resolution, a smalldifference between the observed and fused output data, anda high correlation between the observed and fused *** excellent performance in its practical application is afurther demonstration that the fused data are of highquality.

关键词： data fusion South China Sea bp-ann model

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