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United States Department of Agriculture

Agricultural Research Service

Research Project: Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes

Location: Hydrology and Remote Sensing Laboratory

Title: SMAP L2/L3 soil moisture algorithms and CAL/VAL

item Jackson, Thomas
item Bindlish, R
item Njoku, E
item Colliander, A

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 11/20/2012
Publication Date: 2/25/2013
Citation: Jackson, T.J., Bindlish, R., Njoku, E., Colliander, A. 2013. SMAP L2/L3 soil moisture algorithms and CAL/VAL[abstract]. Soil Mositure Ocean Salinity Land Appplications Workshop. 2012 CDROM.

Interpretive Summary:

Technical Abstract: The SMAP (Soil Moisture Active Passive, launch in 2014) satellite mission will include global measurements of soil moisture at 40 km, 10 km and 3 km resolutions with a 3-day revisit time. The goal accuracy for these products is 0.04 m3/m3. Over the past three years the SMAP project has developed a calibration/validation (Cal/Val) plan that will utilize a wide range of methodologies. These include in situ observations (both dense and sparse networks), products from other satellites, model products, and field experiments. The data provided by the Soil Moisture Ocean Salinity (SMOS) mission will be a cornerstone of SMAP Cal/Val. In addition to its role in cross-calibrating the SMAP radiometer, it will be used for global validation of the soil moisture products (often referred to as Stage 2 validation). The experiences and lessons learned of the SMOS mission are extremely valuable to the SMAP Cal/Val program. SMOS data has already played a significant role in the development and selection of the baseline radiometer-only soil moisture algorithm, An overview of the SMAP mission status, soil moisture products and algorithms, experiences with SMOS data, and Cal/Val plan will be presented. USDA is an equal opportunity employer.

Last Modified: 08/15/2017
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