Articles | Volume 15, issue 5
https://doi.org/10.5194/essd-15-2055-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-2055-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
23 May 2023
Data description article |
| 23 May 2023
| 23 May 2023
Generation of global 1 km daily soil moisture product from 2000 to 2020 using ensemble learning
Yufang Zhang
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
Department of Geography, The University of Hong Kong, Hong Kong
999077, China
Department of Geography, The University of Hong Kong, Hong Kong
999077, China
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
Qian Wang
State Key Laboratory of Remote Sensing Science, Beijing Normal
University, Beijing 100875, China
Bing Li
Key Research Institute of Yellow River Civilization and Sustainable
Development and Collaborative Innovation Center on Yellow River
Civilization of Henan Province, Henan University, Kaifeng 475001, China
Jianglei Xu
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
Guodong Zhang
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
Xiaobang Liu
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
Changhao Xiong
School of Remote Sensing and Information Engineering, Wuhan
University, Wuhan 430079, China
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- Validation of high-resolution surface soil moisture time series retrieved by means of SAR interferometry F. De Zan et al. https://doi.org/10.1016/j.rse.2026.115266
- SMCR: A first satellite-derived all-weather daily/1-km Soil Moisture Climatological Record (1980–2023) S. Zhai et al. https://doi.org/10.1038/s41597-025-06432-4
51 citations as recorded by crossref.
- High-resolution soil moisture mapping in northern boreal forests using SMAP data and downscaling techniques E. Jääskeläinen et al. https://doi.org/10.5194/hess-29-6237-2025
- Soil Moisture Monitoring Method and Data Products: Current Research Status and Future Development Trends R. Liu et al. https://doi.org/10.3390/rs17243945
- Estimating Land Surface All-Wave Daily Net Radiation From VIIRS Top-of-Atmosphere Data X. Yin et al. https://doi.org/10.1109/LGRS.2024.3412731
- Crop Dynamic Root-Depth-Matched High-Resolution Multilayer Soil Moisture Dataset Generated by In Situ-Remote Sensing Data Fusion X. Zhang et al. https://doi.org/10.1109/TGRS.2026.3700579
- Improving SMAP soil moisture spatial resolution in different climatic conditions using remote sensing data F. Imanpour et al. https://doi.org/10.1007/s10661-023-12107-7
- Soil Moisture Satellite Data Under Scrutiny: Assessing Accuracy Through Environmental Proxies and Extended Triple Collocation Analysis A. Pataki et al. https://doi.org/10.1007/s41748-025-00605-2
- AI in soil moisture remote sensing C. Montzka et al. https://doi.org/10.1016/j.jag.2025.105011
- A review of crop yield estimation on pixel and field scales from remotely sensed data F. Zhang et al. https://doi.org/10.1016/j.srs.2025.100342
- Generation of global 1 km all-weather instantaneous and daily mean land surface temperatures from MODIS data B. Li et al. https://doi.org/10.5194/essd-16-3795-2024
- A Review on Soil Moisture Dynamics Monitoring in Semi-Arid Ecosystems: Methods, Techniques, and Tools Applied at Different Scales E. Duarte & A. Hernandez https://doi.org/10.3390/app14177677
- An Integrated Learning Framework for Seamless High-Resolution Soil Moisture Estimation Y. Jing et al. https://doi.org/10.1109/TGRS.2024.3461717
- Enhancing spatial resolution of satellite soil moisture data through stacking ensemble learning techniques M. Tahmouresi et al. https://doi.org/10.1038/s41598-024-77050-0
- Global daily 1 km gapless XCO₂ (2003−2023) derived from multi-satellite observations and a spatiotemporal deep learning framework J. Wang https://doi.org/10.1016/j.eiar.2025.108146
- The Impact of Spatial Dynamic Error on the Assimilation of Soil Moisture Retrieval Products X. Bai et al. https://doi.org/10.3390/rs17020239
- An independent evaluation of global 1 km soil moisture products using in-situ and airborne observations Y. Ma et al. https://doi.org/10.1016/j.rse.2026.115534
- Identification of the dominant factors and altitudinal variation in water use efficiency in the Qinling–Daba Mountains T. Zhao et al. https://doi.org/10.1016/j.ecolind.2024.111626
- Patterns and drivers of critical soil moisture threshold across global tree species C. Song et al. https://doi.org/10.1016/j.agrformet.2026.111181
- Are the Current Expectations for SAR Remote Sensing of Soil Moisture Using Machine Learning Overoptimistic? L. Zhu et al. https://doi.org/10.1109/TGRS.2025.3533927
- Using remote sensing and machine learning to generate 100-cm soil moisture at 30-m resolution for the black soil region of China: Implication for agricultural water management L. Chen et al. https://doi.org/10.1016/j.agwat.2025.109353
- Systematic evaluation of atmospheric forcing, surface datasets, and mesh effects on kilometer-scale land surface and river modeling L. Li et al. https://doi.org/10.1016/j.jhydrol.2026.135500
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- A global long-term daily multilayer soil moisture dataset derived from machine learning Z. Wei et al. https://doi.org/10.1038/s41597-025-06436-0
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- A smart approach to soil quality evaluation by integrating hesitant fuzzy-AHP and artificial intelligence for multi-criteria decision S. Pacci et al. https://doi.org/10.1007/s13762-025-06787-6
- How Big Data Can Help to Monitor the Environment and to Mitigate Risks due to Climate Change: A review J. Montillet et al. https://doi.org/10.1109/MGRS.2024.3379108
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- Spatial Representativeness of Soil Moisture Stations and Its Influential Factors at a Global Scale C. Peng et al. https://doi.org/10.1109/TGRS.2024.3523484
- Relative surface evapotranspiration index (RSETI): A novel approach for drought characterization in Australia Y. Liou & M. Thai https://doi.org/10.1016/j.rse.2025.114948
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- Fusing ERA5-Land and SMAP L4 for an improved global soil moisture product (1950–2025) W. Wang et al. https://doi.org/10.5194/essd-18-1061-2026
- Determination of irrigation water use from multiple soil moisture observations at a fine spatial resolution: Preferred model optimization and fusion strategy Q. Yan et al. https://doi.org/10.1016/j.agwat.2026.110232
- Significant variations in terrestrial water flux in mainland China during 2024 using GRACE-FO: impacts of extreme climate events Y. Zhong et al. https://doi.org/10.1016/j.jag.2025.104875
- Regional differences in carbon-water dynamics of various plantation forests in Southwest China Q. Li et al. https://doi.org/10.1016/j.jhydrol.2025.133809
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- High spatio-temporal resolution soil moisture nowcasting at multiple depths with data-driven approaches Y. Zhang et al. https://doi.org/10.1016/j.agwat.2025.109457
- Downscaling of soil moisture in satellite-borne GNSS-R based on multi-model fusion Y. Liang et al. https://doi.org/10.1088/1361-6501/adef6e
- A novel fusion framework for generating 30 m daily seamless soil moisture with reliable performance Y. Liu et al. https://doi.org/10.1016/j.jhydrol.2026.135791
- Surface Water Availability-Temperature Index (SWATI) for Global Drought Monitoring M. Thai & Y. Liou https://doi.org/10.1109/TGRS.2025.3541287
- A Transformer-based method to simulate multi-scale soil moisture Y. Liu et al. https://doi.org/10.1016/j.jhydrol.2025.132900
- Generating high accuracy multi-layer soil moisture at daily scale in the black soil region of China L. Chen et al. https://doi.org/10.1038/s41597-025-05986-7
- Ensemble of optimised machine learning algorithms for predicting surface soil moisture content at a global scale Q. Han et al. https://doi.org/10.5194/gmd-16-5825-2023
- Quantification and Correction of SMAP Soil Moisture Retrieval Biases Induced by Subpixel Moisture and Texture Heterogeneity Over China P. Song et al. https://doi.org/10.1109/TGRS.2026.3679771
- Dynamic parameterization of global land surface albedo components: Bare soil, non-photosynthetic vegetation, and photosynthetic vegetation A. Jia et al. https://doi.org/10.1016/j.rse.2025.114943
- Improved soil moisture mapping using an integrated cyclic modeling and bias correction approach Y. Shi et al. https://doi.org/10.1016/j.rsase.2025.101741
- Validation of high-resolution surface soil moisture time series retrieved by means of SAR interferometry F. De Zan et al. https://doi.org/10.1016/j.rse.2026.115266
- SMCR: A first satellite-derived all-weather daily/1-km Soil Moisture Climatological Record (1980–2023) S. Zhai et al. https://doi.org/10.1038/s41597-025-06432-4
Saved (final revised paper)
Latest update: 25 Jun 2026
Short summary
Soil moisture observations are important for a range of earth system applications. This study generated a long-term (2000–2020) global seamless soil moisture product with both high spatial and temporal resolutions (1 km, daily) using an XGBoost model and multisource datasets. Evaluation of this product against dense in situ soil moisture datasets and microwave soil moisture products showed that this product has reliable accuracy and more complete spatial coverage.
Soil moisture observations are important for a range of earth system applications. This study...
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