Articles | Volume 13, issue 1
https://doi.org/10.5194/essd-13-1-2021
© Author(s) 2021. 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-13-1-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
An improved global remote-sensing-based surface soil moisture (RSSSM) dataset covering 2003–2018
Yongzhe Chen
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085,
China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049,
China
Xiaoming Feng
CORRESPONDING AUTHOR
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085,
China
Bojie Fu
State Key Laboratory of Urban and Regional Ecology, Research Center
for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085,
China
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049,
China
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- Increasing relative abundance of C4 plants mitigates a dryness-stress effect on gross primary productivity along an aridity gradient in grassland ecosystems J. Wang & X. Wen 10.1007/s11104-022-05529-8
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- Spatiotemporal characteristics of agricultural droughts based on soil moisture data in Inner Mongolia from 1981 to 2019 S. Cai et al. 10.1016/j.jhydrol.2021.127104
- Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning X. Zhu et al. 10.1016/j.scitotenv.2022.159390
- Impact of crop types and irrigation on soil moisture downscaling in water-stressed cropland regions Y. Wang et al. 10.1016/j.eiar.2023.107073
- A fine-resolution soil moisture dataset for China in 2002–2018 X. Meng et al. 10.5194/essd-13-3239-2021
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- An alternative AMSR2 vegetation optical depth for monitoring vegetation at large scales M. Wang et al. 10.1016/j.rse.2021.112556
- Eddy covariance measurement-based differences in annual evapotranspiration between forests and grasslands in China R. Fan et al. 10.3389/fpls.2022.1030929
- Evaluation of global seamless soil moisture products over China: A perspective of soil moisture sensitivity to precipitation X. Hong et al. 10.1016/j.jhydrol.2024.131789
- Photosynthetic capacity dominates the interannual variation of annual gross primary productivity in the Northern Hemisphere W. Zhang et al. 10.1016/j.scitotenv.2022.157856
- Excess radiation exacerbates drought stress impacts on canopy conductance along aridity gradients J. Wang & X. Wen 10.5194/bg-19-4197-2022
- Divergent responses of nitrogen availability to aridity in drylands J. Wang & X. Wen 10.1007/s11104-022-05673-1
- ASCAT IB: A radar-based vegetation optical depth retrieved from the ASCAT scatterometer satellite X. Liu et al. 10.1016/j.rse.2021.112587
- Trends and attribution analysis of modelled evapotranspiration on the Tibetan Plateau H. Zhang et al. 10.1002/hyp.14527
- A 21-year dataset (2000–2020) of gap-free global daily surface soil moisture at 1-km grid resolution C. Zheng et al. 10.1038/s41597-023-01991-w
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- Critical adjustment of land mitigation pathways for assessing countries’ climate progress G. Grassi et al. 10.1038/s41558-021-01033-6
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Latest update: 23 Nov 2024
Short summary
Soil moisture can greatly influence the ecosystem but is hard to monitor at the global scale. By calibrating and combining 11 different products derived from satellite observation, we developed a new global surface soil moisture dataset spanning from 2003 to 2018 with high accuracy. Using this new dataset, not only can the global long-term trends be derived, but also the seasonal variation and spatial distribution of surface soil moisture at different latitudes can be better studied.
Soil moisture can greatly influence the ecosystem but is hard to monitor at the global scale. By...
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