Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over Two Dense Network Regions at Different Spatial Scales

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Soil Moisture Mapping from Satellites: An Intercomparison of SMAP, SMOS, FY3B, AMSR2, and ESA CCI over Two Dense Network Regions at Different Spatial Scales

A good knowledge of the quality of the satellite soil moisture products is of great importance for their application and improvement. This paper examines the performance of eight satellite-based soil moisture products, including the Soil Moisture Active Passive (SMAP) passive Level 3 (L3), the Soil Moisture and Ocean Salinity (SMOS) Centre Aval de Traitement des Données SMOS (CATDS) L3, the Jap...

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Validation of Smos L2 and L3 Soil Moisture Products over the Duero Basin at Different Spatial Scales

An increasing number of permanent soil moisture measurement networks are nowadays providing the means for validating new remotely sensed soil moisture estimates such as those provided by the ESA’s Soil Moisture and Ocean Salinity (SMOS) mission. Two types of in situ measurement networks can be found: small-scale (100-10000 km2), which provide multiple ground measurements within a single satelli...

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It is clear there is a dire need of both soil moisture measurements and sea surface salinity retrievals as they are key parameters of the Earth system. To access them in a global and reliable fashion it seems that – even if complemented by other measurements, L-band radiometry is currently the best choice. The advantages are linked to an optimal trade off between high sensitivity to soil moistu...

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Soil moisture products acquired from passive satellite missions have been widely applied in environmental processes. A primary challenge for the use of soil moisture products from passive sensors is their reliability. It is crucial to evaluate the reliability of those products before they can be routinely used at a global scale. In this paper, we evaluated the Soil Moisture Active/Passive (SMAP...

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ژورنال

عنوان ژورنال: Remote Sensing

سال: 2017

ISSN: 2072-4292

DOI: 10.3390/rs10010033