A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites
文献类型：期刊论文
| 作者 | Li, Weifu1,2; Zhao, Xinghui1,2; Peng, Jiangtao1,2; Luo, Zhicheng1,2; Shen, Lijun2 ; Han, Hua2; Zhang, Peng3; Yang, Lei3
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| 刊名 | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
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| 出版日期 | 2020-02-01 |
| 卷号 | 17期号:2页码:197-201 |
| 关键词 | Coastline detection geolocation error measurement iterative closest point (ICP) microwave radiation imager (MWRI) |
| ISSN号 | 1545-598X |
| DOI | 10.1109/LGRS.2019.2920660 |
| 通讯作者 | Yang, Lei(yangl@cma.gov.cn) |
| 英文摘要 | Known as input in the numerical weather prediction (NWP) models, microwave radiation imager (MWRI) data have been widely distributed to the user community. Nevertheless, the current operational geolocation accuracy is still on the pixel scale due to the presence of geolocation uncertainty. In this letter, we propose a new method to estimate the geolocation errors in MWRI data. Compared to the traditional coastline inflection method (CIM), the proposed method has two innovations. First, we establish a surface fitting interpolation model by involving more observations to detect the coastline. Second, we employ the iterative closest point (ICP) algorithm to determine the correspondences between the detected coastline and the actual coastline. Simulated experimental results demonstrate that the proposed method can provide a more accurate geolocation error estimation than the CIM. By applying our method, we have processed an MWRI data set from January 1 to February 28 in 2016. The experimental results have shown that the operational FY-3C MWRI geolocation errors are 0.4813 and 0.4909 pixels in the along-track and cross-track directions, respectively, which can be significantly reduced to 0.1299 and 0.1497 pixels after the attitude correction. It means that the geolocation accuracy has an average improvement up to 70%. |
| 资助项目 | National Key Research and Development Problem[2018YFB0504900] ; National Key Research and Development Problem[2018YFB0504905] ; National Natural Science Foundation of China[11771130] ; National Natural Science Foundation of China[61871177] ; National Natural Science Foundation of China[61673381] ; National Natural Science Foundation of China[61701497] ; National Natural Science Foundation of China[91338109] ; National Natural Science Foundation of China[61172113] ; Scientific Instrument Developing Project of Chinese Academy of Sciences[YZ201671] |
| WOS研究方向 | Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000510900300003 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Key Research and Development Problem ; National Natural Science Foundation of China ; Scientific Instrument Developing Project of Chinese Academy of Sciences |
| 源URL | [http://ir.ia.ac.cn/handle/173211/28560]  |
| 专题 | 类脑智能研究中心_微观重建与智能分析 |
| 通讯作者 | Yang, Lei |
| 作者单位 | 1.Hubei Univ, Fac Math & Stat, Wuhan 430062, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 3.China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing 100081, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Weifu,Zhao, Xinghui,Peng, Jiangtao,et al. A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites[J]. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,2020,17(2):197-201. |
| APA | Li, Weifu.,Zhao, Xinghui.,Peng, Jiangtao.,Luo, Zhicheng.,Shen, Lijun.,...&Yang, Lei.(2020).A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites.IEEE GEOSCIENCE AND REMOTE SENSING LETTERS,17(2),197-201. |
| MLA | Li, Weifu,et al."A New Geolocation Error Estimation Method in MWRI Data Aboard FY3 Series Satellites".IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 17.2(2020):197-201. |
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