Articles | Volume 14, issue 10
https://doi.org/10.5194/essd-14-4473-2022
© Author(s) 2022. 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-14-4473-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
06 Oct 2022
Data description article |
| 06 Oct 2022
| 06 Oct 2022
SGD-SM 2.0: an improved seamless global daily soil moisture long-term dataset from 2002 to 2022
Qiang Zhang
Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, China
School of Geodesy and Geomatics, Wuhan University, China
Taoyong Jin
CORRESPONDING AUTHOR
School of Geodesy and Geomatics, Wuhan University, China
Meiping Song
Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information Science and Technology College, Dalian Maritime University, China
Fujun Sun
CASIC Research Institute of Intelligent Decision Engineering, Beijing, China
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Cited
20 citations as recorded by crossref.
- Development of Continuous AMSR-E/2 Soil Moisture Time Series by Hybrid Deep Learning Model (ConvLSTM2D and Conv2D) and Transfer Learning for Reanalyses V. Sivaprasad et al.
- A decade-long seamless-continuity daily L-band soil moisture product derived from SMOS observations since 2010 Y. Bai et al.
- Validation of Himawari-8/9 10-minute wildfire products: Comparisons with MODIS and VIIRS from 2015 to 2023 Z. Liu et al.
- Synergizing machine learning and interpolation methods: A Stacking framework for global-scale satellite soil moisture gap filling J. Rong et al.
- Spatiotemporal Reconstruction of FY-3B Soil Moisture Using a Hybrid Attention and Partial Convolution Neural Network R. Xu et al.
- Rolling forecast of snowmelt floods in data-scarce mountainous regions using weather forecast products to drive distributed energy balance hydrological model G. Zhou et al.
- An Integrated Learning Framework for Seamless High-Resolution Soil Moisture Estimation Y. Jing et al.
- A global daily seamless 9 km vegetation optical depth (VOD) product from 2010 to 2021 D. Hu et al.
- A seamless global daily 5 km soil moisture product from 1982 to 2021 using AVHRR satellite data and an attention-based deep learning model Y. Zhang et al.
- From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution Y. Xiao et al.
- Seamless global daily soil moisture mapping using deep learning based spatiotemporal fusion M. Jiang et al.
- 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.
- Green water availability and water-limited crop yields under a changing climate in Ethiopia M. Wakjira et al.
- A TCN-Transformer Parallel model for reconstruction of a global, daily, spatially seamless FY-3B soil moisture dataset Q. Wang et al.
- Global-scale gap filling of satellite soil moisture products: Methods and validation C. Zhang et al.
- Assessment of Maximum Snow-Water Equivalent in the Uba River Basin (Altai) Using the Temperature-Based Melt-Index Method N. Bykov et al.
- Soil moisture estimation based on FY-3E backscattering data for enhanced daily coverage to SMAP observations in the dawn-dusk orbit P. Song et al.
- A global long-term (2002–2022) C-band vegetation optical depth record retrieved after merging AMSR-E, AMSR2 and WindSat D. Chen et al.
- A seamless global daily soil moisture dataset (2010–2015) harmonized from SMOS observations and SMAP-era assimilation modeling X. Wang et al.
- Physically-aware deep learning for reconstructing gap-free sea surface temperature in the South China Sea C. Su et al.
20 citations as recorded by crossref.
- Development of Continuous AMSR-E/2 Soil Moisture Time Series by Hybrid Deep Learning Model (ConvLSTM2D and Conv2D) and Transfer Learning for Reanalyses V. Sivaprasad et al.
- A decade-long seamless-continuity daily L-band soil moisture product derived from SMOS observations since 2010 Y. Bai et al.
- Validation of Himawari-8/9 10-minute wildfire products: Comparisons with MODIS and VIIRS from 2015 to 2023 Z. Liu et al.
- Synergizing machine learning and interpolation methods: A Stacking framework for global-scale satellite soil moisture gap filling J. Rong et al.
- Spatiotemporal Reconstruction of FY-3B Soil Moisture Using a Hybrid Attention and Partial Convolution Neural Network R. Xu et al.
- Rolling forecast of snowmelt floods in data-scarce mountainous regions using weather forecast products to drive distributed energy balance hydrological model G. Zhou et al.
- An Integrated Learning Framework for Seamless High-Resolution Soil Moisture Estimation Y. Jing et al.
- A global daily seamless 9 km vegetation optical depth (VOD) product from 2010 to 2021 D. Hu et al.
- A seamless global daily 5 km soil moisture product from 1982 to 2021 using AVHRR satellite data and an attention-based deep learning model Y. Zhang et al.
- From degrade to upgrade: Learning a self-supervised degradation guided adaptive network for blind remote sensing image super-resolution Y. Xiao et al.
- Seamless global daily soil moisture mapping using deep learning based spatiotemporal fusion M. Jiang et al.
- 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.
- Green water availability and water-limited crop yields under a changing climate in Ethiopia M. Wakjira et al.
- A TCN-Transformer Parallel model for reconstruction of a global, daily, spatially seamless FY-3B soil moisture dataset Q. Wang et al.
- Global-scale gap filling of satellite soil moisture products: Methods and validation C. Zhang et al.
- Assessment of Maximum Snow-Water Equivalent in the Uba River Basin (Altai) Using the Temperature-Based Melt-Index Method N. Bykov et al.
- Soil moisture estimation based on FY-3E backscattering data for enhanced daily coverage to SMAP observations in the dawn-dusk orbit P. Song et al.
- A global long-term (2002–2022) C-band vegetation optical depth record retrieved after merging AMSR-E, AMSR2 and WindSat D. Chen et al.
- A seamless global daily soil moisture dataset (2010–2015) harmonized from SMOS observations and SMAP-era assimilation modeling X. Wang et al.
- Physically-aware deep learning for reconstructing gap-free sea surface temperature in the South China Sea C. Su et al.
Saved (final revised paper)
Latest update: 30 Apr 2026
Short summary
Compared to previous seamless global daily soil moisture (SGD-SM 1.0) products, SGD-SM 2.0 enlarges the temporal scope from 2002 to 2022. By fusing auxiliary precipitation information with the long short-term memory convolutional neural network (LSTM-CNN) model, SGD-SM 2.0 can consider sudden extreme weather conditions for 1 d in global daily soil moisture products and is significant for full-coverage global daily hydrologic monitoring, rather than averaging monthly–quarterly–yearly results.
Compared to previous seamless global daily soil moisture (SGD-SM 1.0) products, SGD-SM 2.0...
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