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The SMOS, and SMAP retrievals are not only influenced by soil moisture, vegetation but also highly sensitive to surface roughness. The current retrieval algorithms use roughness models and parameterization developed at field scale to estimate soil moisture at satellite footprint. These models ignored large scale roughness features due to differences in elevation, concavity etc., observed within the...
There are a variety of soil moisture station designs and networks deployed throughout the world, each with varying applications and uses. For the purpose of satellite validation of soil moisture products, a dense network of soil moisture networks are required with soil moisture sensors at the near surface (∼5 cm or less) to correspond to the satellite footprints and signals. The USDA-Agricultural...
Vegetation water content (VWC) plays an important role in parameterizing the vegetation influence on microwave soil moisture retrieval. During the past decade, relationships have been developed between VWC and vegetation indices from satellite optical sensors, in order to create large-scale VWC maps based on these relationships. Among existing vegetation indices, the normalized difference vegetation...
Retrieval of soil moisture content from microwave sensors also returns an estimate of vegetation water content. Remotely sensed indices from optical sensors can be used to estimate canopy water content. For corn and soybean in central Iowa, there are allometric relationships between canopy water content and vegetation water content. The Normalized Difference Infrared Index from MODIS was used to estimate...
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