A global soil moisture product at 1 km resolution based on Sentinel-1 (2023-2024)
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| Natura: | Dataset Open Access |
| Lingua: | en |
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PANGAEA
2025
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| _version_ | 1867172347950137344 |
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| author | Fan, Dong Zhao, Tianjie Jiang, Xiaoguang García-García, Almudena Schmidt, Toni Samaniego, Luis Attinger, Sabine Wu, Hua Jiang, Yazhen Shi, Jiancheng Fan, Lei Tang, Bohui Wagner, Wolfgang Dorigo, Wouter Gruber, Alexander Mattia, Francesco Balenzano, Anna Brocca, Luca Jagdhuber, Thomas Wigneron, Jean-Pierre Montzka, Carsten Peng, Jian |
| author_facet | Fan, Dong Zhao, Tianjie Jiang, Xiaoguang García-García, Almudena Schmidt, Toni Samaniego, Luis Attinger, Sabine Wu, Hua Jiang, Yazhen Shi, Jiancheng Fan, Lei Tang, Bohui Wagner, Wolfgang Dorigo, Wouter Gruber, Alexander Mattia, Francesco Balenzano, Anna Brocca, Luca Jagdhuber, Thomas Wigneron, Jean-Pierre Montzka, Carsten Peng, Jian |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Although soil moisture represents only a small fraction of the Earth's total water content, it plays a pivotal role in the land surface water and energy cycle by regulating key processes such as evaporation, infiltration, and vegetation growth. Remote sensing has become an essential tool for acquiring global-scale soil moisture data. In this study, a dual-polarization algorithm (DPA) is proposed, utilizing VV and VH polarization observations from the Sentinel-1 C-band synthetic aperture radar to produce a global soil moisture dataset at a spatial resolution of 1 km. Due to the observation configuration of Sentinel-1, the dataset exhibits higher temporal resolution in Europe and high-latitude regions than in other continents and lower-latitude areas. The dataset is provided in raster format, with daily ascending and descending observations. To ensure data quality, regions unsuitable for soil moisture retrieval—such as open water, permanent wetlands, frozen ground, snow- and ice-covered surfaces, and urban or built-up areas-have been excluded. User feedback and collaborative efforts to enhance the dataset are welcome. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_982398 |
| institution | PANGAEA |
| language | en |
| publishDate | 2025 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | A global soil moisture product at 1 km resolution based on Sentinel-1 (2023-2024) Fan, Dong Zhao, Tianjie Jiang, Xiaoguang García-García, Almudena Schmidt, Toni Samaniego, Luis Attinger, Sabine Wu, Hua Jiang, Yazhen Shi, Jiancheng Fan, Lei Tang, Bohui Wagner, Wolfgang Dorigo, Wouter Gruber, Alexander Mattia, Francesco Balenzano, Anna Brocca, Luca Jagdhuber, Thomas Wigneron, Jean-Pierre Montzka, Carsten Peng, Jian 1km spatial resolution; Binary Object; Binary Object (File Size); Binary Object (MD5 Hash); Binary Object (Media Type); CLIMATE-Pan-TPE; global; Model-Data fusion for understanding Environmental Variability; MoDEV; Monitoring and Modelling Climate Change in Water, Energy and Carbon Cycles in the Pan-Third Pole Environment; SAR; Sentinel-1; Soil Moisture; water content Although soil moisture represents only a small fraction of the Earth's total water content, it plays a pivotal role in the land surface water and energy cycle by regulating key processes such as evaporation, infiltration, and vegetation growth. Remote sensing has become an essential tool for acquiring global-scale soil moisture data. In this study, a dual-polarization algorithm (DPA) is proposed, utilizing VV and VH polarization observations from the Sentinel-1 C-band synthetic aperture radar to produce a global soil moisture dataset at a spatial resolution of 1 km. Due to the observation configuration of Sentinel-1, the dataset exhibits higher temporal resolution in Europe and high-latitude regions than in other continents and lower-latitude areas. The dataset is provided in raster format, with daily ascending and descending observations. To ensure data quality, regions unsuitable for soil moisture retrieval—such as open water, permanent wetlands, frozen ground, snow- and ice-covered surfaces, and urban or built-up areas-have been excluded. User feedback and collaborative efforts to enhance the dataset are welcome. |
| title | A global soil moisture product at 1 km resolution based on Sentinel-1 (2023-2024) |
| topic | 1km spatial resolution; Binary Object; Binary Object (File Size); Binary Object (MD5 Hash); Binary Object (Media Type); CLIMATE-Pan-TPE; global; Model-Data fusion for understanding Environmental Variability; MoDEV; Monitoring and Modelling Climate Change in Water, Energy and Carbon Cycles in the Pan-Third Pole Environment; SAR; Sentinel-1; Soil Moisture; water content |
| url | https://doi.org/10.1594/PANGAEA.982398 |