Hierarchical Bayesian Model Based on Robust Fixed Rank Filter for Fusing MODIS SST and AMSR-E SST
文献类型：期刊论文
| 作者 | Zhu, Yuxin3,4,5; Kang, Emily Lei6; Bo, Yanchen2; Zhang, Jinzong3,4; Wang, Yuexiang3,4; Tang, Qingxin1 |
| 刊名 | PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
 |
| 出版日期 | 2019-02-01 |
| 卷号 | 85期号:2页码:119-131 |
| 关键词 | Hierarchical Bayesian Model based on R-FRF MODIS SST AMSR-E SST scale transformation local variance |
| ISSN号 | 0099-1112 |
| DOI | 10.14358/PERS.85.2.119 |
| 通讯作者 | Zhu, Yuxin(zhuyuxin_402@163.com) |
| 英文摘要 | Spatiotemporal complete sea surface temperature (SST) dataset with higher accuracy and resolution is desirable for many studies in atmospheric science and climate change. The purpose of this study is to establish the spatiotemporal data fusion model, the Hierarchical Bayesian Model (HBM) based on Robust Fixed Rank Filter (R-FRF), that merge Moderate Resolution Imaging Spectroradiometer (MODIS) SST with 4-km resolution and Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) SST with 25-km resolution through their spatiotemporal complementarity to obtain fusion SST with complete coverage, high spatial resolution, and fine spatial pattern. First, a bias correction model was applied to correct satellite SST. Second, a spatiotemporal model called R-FRF was established to model potential spatiotemporal process of SST. Third, the R-FRF model was embedded in the hierarchical Bayesian framework, and the corrected MODIS and AMSR-E SST are merged. Finally, the accuracy, spatial pattern and spatial completeness of the fusion SST were assessed. The results of this study are the following: (a) It is necessary to carry out bias correction before data fusion. (b) The R-FRF model could simulate SST spatiotemporal trend well. (c) Fusion SST has similar accuracy and spatial pattern to MODIS SST. Though the accuracy is lower than that of the AMSR-E SST, the fusion SST has more local detail information. The results indicated that fusion SST with higher accuracy, finer spatial pattern, and complete coverage can be obtained through HBM based on R-FRF. |
| WOS关键词 | SEA-SURFACE TEMPERATURE ; OCEAN COLOR DATA ; TEMPORAL VARIABILITY ; MULTITEMPORAL MODIS ; PASSIVE MICROWAVE ; IN-SITU ; PRODUCTS ; NDVI ; VALIDATION ; DATASETS |
| 资助项目 | Natural Science Foundation of China[41401405] ; Statistics Bureau of China[2016LY32] ; Natural Science Foundation of Shandong Province[ZR2013DL002] ; Natural Science Foundation of Shandong Province[ZR2017MD017] ; China Postdoctoral Science Foundation[2014M561039] ; Huaian key laboratory for geographic information technology and application[HAP201405] |
| WOS研究方向 | Physical Geography ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000456709400005 |
| 出版者 | AMER SOC PHOTOGRAMMETRY |
| 资助机构 | Natural Science Foundation of China ; Statistics Bureau of China ; Natural Science Foundation of Shandong Province ; China Postdoctoral Science Foundation ; Huaian key laboratory for geographic information technology and application |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/50579]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhu, Yuxin |
| 作者单位 | 1.Liaocheng Univ, Sch Environm & Planning, Liaocheng 252059, Shandong, Peoples R China 2.Beijing Normal Univ, Fac Geog Sci, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China 3.Huaiyin Normal Univ, Sch Urban & Environm Sci, Inst Land & Urban Rural Planning, Huaian 223300, Jiangsu, Peoples R China 4.Huaiyin Normal Univ, Jiangsu Collaborat Innovat Ctr Reg Modern Agr & E, Huaian 223300, Jiangsu, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 6.Univ Cincinnati, Cincinnati, OH 45221 USA |
| 推荐引用方式 GB/T 7714 | Zhu, Yuxin,Kang, Emily Lei,Bo, Yanchen,et al. Hierarchical Bayesian Model Based on Robust Fixed Rank Filter for Fusing MODIS SST and AMSR-E SST[J]. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING,2019,85(2):119-131. |
| APA | Zhu, Yuxin,Kang, Emily Lei,Bo, Yanchen,Zhang, Jinzong,Wang, Yuexiang,&Tang, Qingxin.(2019).Hierarchical Bayesian Model Based on Robust Fixed Rank Filter for Fusing MODIS SST and AMSR-E SST.PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING,85(2),119-131. |
| MLA | Zhu, Yuxin,et al."Hierarchical Bayesian Model Based on Robust Fixed Rank Filter for Fusing MODIS SST and AMSR-E SST".PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING 85.2(2019):119-131. |
入库方式： OAI收割
来源：地理科学与资源研究所
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