A Sentinel-1 SAR-based global 1-km resolution soil moisture data product: Algorithm and preliminary assessment
文献类型：期刊论文
| 作者 | Fan, Dong15,16,17; Zhao, Tianjie14; Jiang, Xiaoguang13; Garcia-Garcia, Almudena15,16; Schmidt, Toni13,16; Samaniego, Luis11,12; Attinger, Sabine11,12; Wu, Hua10; Jiang, Yazhen10; Shi, Jiancheng9 |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2025-03-01 |
| 卷号 | 318页码:114579 |
| 关键词 | Soil moisture SAR Microwave Sentinel-1 High resolution |
| ISSN号 | 0034-4257 |
| DOI | 10.1016/j.rse.2024.114579 |
| 产权排序 | 8 |
| 文献子类 | Article |
| 英文摘要 | High spatial resolution of satellite-based soil moisture (SM) data are essential for hydrological, meteorological, ecological, and agricultural studies. Especially, for watershed hydrological simulation and crop water stress analysis, 1-km resolution SM data have attracted considerable attention. In this study, a dual-polarization algorithm (DPA) for SM estimation is proposed to produce a global-scale, 1-km resolution SM dataset (S1-DPA) using the Sentinel-1 synthetic aperture radar (SAR) data. Specifically, a forward model was constructed to simulate the backscatter observed by the Sentinel-1 dual-polarization SAR, and SM retrieval was achieved by minimizing the simulation error for different soil and vegetation states. The produced S1-DPA data products cover the global land surface for the period 2016-2022 and include both ascending and descending data with an observation frequency of 3-6 days for Europe and 6-12 days for the other regions. The validation results show that the S1-DPA reproduces the spatio-temporal variation characteristics of the ground-observed SM, with an unbiased root mean squared difference (ubRMSD) of 0.077 m3/m3. The generated 1-km SM product will facilitate the application of high-resolution SM data in the field of hydrology, meteorology and ecology. |
| URL标识 | 查看原文 |
| WOS关键词 | MICROWAVE DIELECTRIC BEHAVIOR ; EMPIRICAL-MODEL ; WATER CONTENT ; WET SOIL ; SURFACE ; SATELLITE ; RETRIEVAL ; NETWORK ; RADAR ; BACKSCATTERING |
| WOS研究方向 | Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001411113400001 |
| 出版者 | ELSEVIER SCIENCE INC |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/212384]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Peng, Jian |
| 作者单位 | 1.Forschungszentrum Julich, Inst Plasmaphys, Julich, Germany 2.RECH ARBORICULTURE FRUITIERE BORDEAUX STN, CTR RECH AGRON BORDEAUX, INRA, F-33140 Villenave DOrnon, France; 3.Univ Augsburg, Inst Geog, Augsburg, Germany; 4.German Aerosp Ctr DLR, Microwaves & Radar Inst, Wessling, Germany; 5.CNR, Res Inst Geohydrol Protect, Perugia, Italy; 6.UOS, CNR, Bari, Italy; 7.Vienna Univ Technol, TU Wien, Dept Geodesy & Geoinformat, Vienna, Austria; 8.Southwest Univ, Sch Geog Sci, Chongqing Jinfo Mt Karst Ecosyst, Chongqing, Peoples R China; 9.Chinese Acad Sci, Natl Space Sci Ctr, Beijing, Peoples R China; 10.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Fan, Dong,Zhao, Tianjie,Jiang, Xiaoguang,et al. A Sentinel-1 SAR-based global 1-km resolution soil moisture data product: Algorithm and preliminary assessment[J]. REMOTE SENSING OF ENVIRONMENT,2025,318:114579. |
| APA | Fan, Dong.,Zhao, Tianjie.,Jiang, Xiaoguang.,Garcia-Garcia, Almudena.,Schmidt, Toni.,...&Peng, Jian.(2025).A Sentinel-1 SAR-based global 1-km resolution soil moisture data product: Algorithm and preliminary assessment.REMOTE SENSING OF ENVIRONMENT,318,114579. |
| MLA | Fan, Dong,et al."A Sentinel-1 SAR-based global 1-km resolution soil moisture data product: Algorithm and preliminary assessment".REMOTE SENSING OF ENVIRONMENT 318(2025):114579. |
入库方式： OAI收割
来源：地理科学与资源研究所
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