Articles | Volume 27, issue 2
https://doi.org/10.5194/hess-27-577-2023
© 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/hess-27-577-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Jan 2023
Research article |
| 30 Jan 2023
| 30 Jan 2023
A robust gap-filling approach for European Space Agency Climate Change Initiative (ESA CCI) soil moisture integrating satellite observations, model-driven knowledge, and spatiotemporal machine learning
Kai Liu
Aerospace Information Research Institute, Chinese Academy of Sciences,
Beijing 100094, China
Institute at Brown for Environment and Society, Brown University,
Providence, RI 02912, USA
Shudong Wang
CORRESPONDING AUTHOR
Aerospace Information Research Institute, Chinese Academy of Sciences,
Beijing 100094, China
Collaborative Innovation Center on Forecast and Evaluation of
Meteorological Disasters (CIC-FEMD), Nanjing University of Information
Science & Technology, Nanjing 210044, China
Hongyan Zhang
Aerospace Information Research Institute, Chinese Academy of Sciences,
Beijing 100094, China
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Cited
17 citations as recorded by crossref.
- Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China A. Nadeem et al. 10.3390/rs15030812
- Detecting the human fingerprint in the summer 2022 western–central European soil drought D. Schumacher et al. 10.5194/esd-15-131-2024
- Evaluating thermal conductivity of soil-rock mixtures in Qinghai-Tibet plateau based on theory models and machine learning methods Q. Wang et al. 10.1016/j.ijthermalsci.2024.109210
- Optimizing Rice Field Mapping in the Northern Region of China: An Asynchronous Flooding Signal and Object-Based Method L. Li et al. 10.1109/JSTARS.2024.3357141
- A Deep Learning Framework for Long-Term Soil Moisture-Based Drought Assessment Across the Major Basins in China Y. Duan et al. 10.3390/rs17061000
- İnsansız Hava Aracı Kullanarak Toprak Neminin Mısır Tarlası Örneğinde Haritalanması F. Sönmez Erdoğan & M. Erdoğan 10.51534/tiha.1493413
- Assessing reclamation potential of abandoned drylands using knowledge-guided machine learning (KGML) and remote sensing K. Liu et al. 10.1016/j.watres.2025.124623
- Response of Grassland Vegetation Growth to Drought in Inner Mongolia of China from 2002 to 2020 A. Zhao et al. 10.3390/atmos14111613
- Spatial Downscaling of ESA CCI Soil Moisture Data Based on Deep Learning with an Attention Mechanism D. Zhang et al. 10.3390/rs16081394
- Evaluating the NASA MERRA-2 climate reanalysis and ESA CCI satellite remote sensing soil moisture over the contiguous United States M. Valipour et al. 10.1080/01431161.2023.2237665
- Addressing spatial gaps in ESA CCI soil moisture product: A hierarchical reconstruction approach using deep learning model T. Ding et al. 10.1016/j.jag.2024.104003
- ESA CCI Soil Moisture GAPFILLED: an independent global gap-free satellite climate data record with uncertainty estimates W. Preimesberger et al. 10.5194/essd-17-4305-2025
- Temporal Gap‐Filling of 12‐Hourly SMAP Soil Moisture Over the CONUS Using Water Balance Budgeting R. Zhang et al. 10.1029/2023WR034457
- Evaluating satellite-based precipitation products for spatiotemporal drought analysis H. Khan et al. 10.1016/j.jaridenv.2024.105225
- Adaptive Gap-Filling of Multispectral Images at Coarse and Fine Spatial Resolution S. Afsharipour et al. 10.1109/JSTARS.2025.3551360
- Relationship between carbon pool changes and environmental changes in arid and semi-arid steppe—A two decades study in Inner Mongolia, China H. Li et al. 10.1016/j.scitotenv.2023.164930
- Gap‐Filled Multivariate Observations of Global Land–Climate Interactions V. Bessenbacher et al. 10.1029/2023JD039099
17 citations as recorded by crossref.
- Spatial Downscaling and Gap-Filling of SMAP Soil Moisture to High Resolution Using MODIS Surface Variables and Machine Learning Approaches over ShanDian River Basin, China A. Nadeem et al. 10.3390/rs15030812
- Detecting the human fingerprint in the summer 2022 western–central European soil drought D. Schumacher et al. 10.5194/esd-15-131-2024
- Evaluating thermal conductivity of soil-rock mixtures in Qinghai-Tibet plateau based on theory models and machine learning methods Q. Wang et al. 10.1016/j.ijthermalsci.2024.109210
- Optimizing Rice Field Mapping in the Northern Region of China: An Asynchronous Flooding Signal and Object-Based Method L. Li et al. 10.1109/JSTARS.2024.3357141
- A Deep Learning Framework for Long-Term Soil Moisture-Based Drought Assessment Across the Major Basins in China Y. Duan et al. 10.3390/rs17061000
- İnsansız Hava Aracı Kullanarak Toprak Neminin Mısır Tarlası Örneğinde Haritalanması F. Sönmez Erdoğan & M. Erdoğan 10.51534/tiha.1493413
- Assessing reclamation potential of abandoned drylands using knowledge-guided machine learning (KGML) and remote sensing K. Liu et al. 10.1016/j.watres.2025.124623
- Response of Grassland Vegetation Growth to Drought in Inner Mongolia of China from 2002 to 2020 A. Zhao et al. 10.3390/atmos14111613
- Spatial Downscaling of ESA CCI Soil Moisture Data Based on Deep Learning with an Attention Mechanism D. Zhang et al. 10.3390/rs16081394
- Evaluating the NASA MERRA-2 climate reanalysis and ESA CCI satellite remote sensing soil moisture over the contiguous United States M. Valipour et al. 10.1080/01431161.2023.2237665
- Addressing spatial gaps in ESA CCI soil moisture product: A hierarchical reconstruction approach using deep learning model T. Ding et al. 10.1016/j.jag.2024.104003
- ESA CCI Soil Moisture GAPFILLED: an independent global gap-free satellite climate data record with uncertainty estimates W. Preimesberger et al. 10.5194/essd-17-4305-2025
- Temporal Gap‐Filling of 12‐Hourly SMAP Soil Moisture Over the CONUS Using Water Balance Budgeting R. Zhang et al. 10.1029/2023WR034457
- Evaluating satellite-based precipitation products for spatiotemporal drought analysis H. Khan et al. 10.1016/j.jaridenv.2024.105225
- Adaptive Gap-Filling of Multispectral Images at Coarse and Fine Spatial Resolution S. Afsharipour et al. 10.1109/JSTARS.2025.3551360
- Relationship between carbon pool changes and environmental changes in arid and semi-arid steppe—A two decades study in Inner Mongolia, China H. Li et al. 10.1016/j.scitotenv.2023.164930
- Gap‐Filled Multivariate Observations of Global Land–Climate Interactions V. Bessenbacher et al. 10.1029/2023JD039099
Latest update: 08 Oct 2025
Short summary
Remote sensing has opened opportunities for mapping spatiotemporally continuous soil moisture, but it is hampered by data gaps. We propose a robust gap-filling approach to reconstruct daily satellite soil moisture. The merit of our approach is to integrate satellite observations, model-driven knowledge, and spatiotemporal machine learning. We also apply the developed approach to long-term datasets. Our study provides a potential avenue for hydrological applications.
Remote sensing has opened opportunities for mapping spatiotemporally continuous soil moisture,...
