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 (2025): A global soil moisture product at 1 km resolution based on Sentinel-1 (2016-2022) [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.968754
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Published: 2025-01-09 • DOI registered: 2025-01-09
Abstract:
Soil moisture, although a small fraction of total water content, plays a critical role in the Earth's surface water-heat cycle by influencing processes such as evaporation, infiltration, and vegetation growth and development. Remote sensing has emerged as a critical method for obtaining global-scale soil moisture data. A dual-polarization algorithm (DPA) is proposed and the dual-polarization (VV+VH) observations from the Sentinel-1 C-band synthetic aperture radar are used to generate a global soil moisture dataset with a spatial resolution of 1 km. Due to the observation mode of Sentinel-1, the temporal resolution of this dataset is higher in European and high latitude regions compared to other continents and lower latitude regions. The dataset is provided in raster format, with one set of ascending and one set of descending data for each day, and to ensure data quality, certain areas not suitable for soil moisture retrieval have been excluded, such as water bodies, permanent wetlands, frozen areas, ice and snow covered surfaces, and urban and built-up areas. Feedback and collaboration to improve the dataset is encouraged.
Supplement to:
Fan, Dong; Zhao, Tianjie; Jiang, Xiaoguang; García-García, Almudena; Schmidt, Toni; Samaniego, Luis; Attinger, Sabine; Wu, Hua; Jiang, Yazhen; Shi, Jiancheng; Fan, Lei; Tang, Bo-Hui; Wagner, Wolfgang; Dorigo, Wouter; Gruber, Alexander; Mattia, Francesco; Balenzano, Anna; Brocca, Luca; Jagdhuber, Thomas; Wigneron, Jean-Pierre; Montzka, Carsten; 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, https://doi.org/10.1016/j.rse.2024.114579
Project(s):
Funding:
European Space Agency (ESA), grant/award no. 4000141141/23/I-EF: Hyper-resolution Earth Observations And Land-surface Modeling For A Better Understanding Of The Water Cycle - 4DHydro
Yunnan Provincial Department of Science and Technology, grant/award no. 202401CF07016: Yunnan Fundamental Research Projects
Comment:
* File descriptions:
(1) File format: TIFF
(2) Naming rule: SM_Ascending/Descending_YYYYMMDD.tif (eg: SM_D_20160906.tif)
(3) Spatial resolution: 1km (about 0.0089831528 degree)
(4) Columns and rows: 40074 and 20036
(5) Coordinate system: D_WGS_1984 (EPSG:4326)
(6) Scope: Top 89.9887335867, Left -179.990941903, Right 179.990941903, Bottom -89.9887335867
(7) Pixel_Type: signed integer (16Bit)
(8) Scale: 1000
(9) Valid range: 0.02 to 0.6 m³/m³
(10) Backgroud value:
32767: Permanent Wetlands, Urban and Built-up Lands, Permanent Snow and Ice, Water Bodies
32766: Surface temperature < 275.15K
32765: Snow cover > 10%
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Binary Object | Binary | Fan, Dong | MATLAB ® - modeling and processing | ||
| 2 | Binary Object (File Size) | Binary (Size) | Bytes | Fan, Dong | MATLAB ® - modeling and processing | |
| 3 | Binary Object (Media Type) | Binary (Type) | Fan, Dong | MATLAB ® - modeling and processing | ||
| 4 | Binary Object (MD5 Hash) | Binary (Hash) | Fan, Dong | MATLAB ® - modeling and processing |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
14 data points