期刊
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
卷 24, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.rsase.2021.100649
关键词
Remote sensing; Model-based soil moisture retrieval; In situ observation; SMAP; NLDAS; GLDAS; AMSR; SMOS; North American Soil moisture database; International soil moisture network; ESA CCI; ASCAT; ASAR; Resolution; Soil moisture application
Soil moisture plays a critical role in the climate system, linking atmospheric and terrestrial energy, water, and carbon cycles. Understanding soil moisture variations is crucial for predicting floods, droughts, and heatwaves, as well as improving weather forecasting. Ground-based data are limited by spatial and temporal coverage, leading to the importance of model- and satellite-based measurements as alternatives.
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-theart 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.
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