The soil moisture data bank: The ground-based, model-based, and satellite-based soil moisture data

Soil moisture is a critical component of the climate system due to the link it provides between atmospheric and terrestrial energy, water, and carbon cycles. A better understanding of floods, droughts, and heatwaves, as well as weather forecasting, is highly dependent on the knowledge of soil moistu...

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Veröffentlicht in:Remote sensing applications 2021-11, Vol.24, p.100649, Article 100649
Hauptverfasser: Tavakol, Ameneh, McDonough, Kelsey R., Rahmani, Vahid, Hutchinson, Stacy L., Hutchinson, J.M. Shawn
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Sprache:eng
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Zusammenfassung:Soil moisture is a critical component of the climate system due to the link it provides between atmospheric and terrestrial energy, water, and carbon cycles. A better understanding of floods, droughts, and heatwaves, as well as weather forecasting, is highly dependent on the knowledge of soil moisture variations and its impacts. Ground-based soil moisture datasets are crucial for climatological analysis, as are model- and satellite-based data. However, ground-based data are sparse in spatial and temporal coverage, and often include missing data. Since ground-based observations are limited in both time and space, model- and satellite-based measurements often serve as alternatives. Here in this paper, the interest is to provide an overview of the state-of-the-art open-access soil moisture datasets at various spatial and temporal scales. Despite the recent progress in producing model-based and satellite-based data, there are many potentials to improve the quality of the data. These sets of data can be used for forecasting weather and climate variability, monitoring the influence of climate change on an ecosystem, drought monitoring and prediction, water resources management, agricultural production, and more. •An overview of the state-of-the-art open-access soil moisture datasets is provided.•Ground-based soil moisture measurements are often considered to be the ground truth.•Selection of data depends on different parameters.•No single data can be suggested for universal application.
ISSN:2352-9385
2352-9385
DOI:10.1016/j.rsase.2021.100649