This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1080/10106049.2018.1520926. This is version 3 of this Preprint.
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Surface Soil Moisture (SSM) is a key parameter of the global energy and water cycle and knowing its spatio-temporal variability is of key importance in an array of research topics and in several practical applications alike. Recent developments in Earth Observation (EO) have indicated that SSM can be retrieved from different regions of electromagnetic spectrum and numerous approaches have been proposed to facilitate this. Herein, are reviewed the SSM retrieval techniques exploiting optical and thermal EO data, including synergistic techniques with other types of EO datasets. The challenges and limitations of EO in this respect are also discussed, aiming in the end at providing a roadmap on which future research by the scientific community should be directed to provide more accurately estimates of SSM from space. A number of challenges still required to be addressed to allow deriving accurately SSM estimates using those specific types of EO data. It is also apparent that to satisfy the requirements for SSM information for many practical applications, efforts should be towards the investigation of the synergistic use of EO systems in deriving soil moisture for water resources applications.
Earth Sciences, Environmental Sciences, Other Earth Sciences, Physical Sciences and Mathematics
Published in Geocarto International
Published: 2020-03-23 16:52
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