Validation of Satellite-Based Soil Moisture Products Using in Situ Data
Hydrology and Remote Sensing Laboratory
2013 Annual Report
1a.Objectives (from AD-416):
To provide a testbed to compare soil moisture sensor technologies and provide a basis for merging diverse in situ soil moisture networks for validation of satellite remote sensing products. To develop, extend, and maintain validation networks for soil moisture monitoring, including seven ARS research watersheds. Develop and deploy temporary networks for the verification of permanent networks at ARS watersheds.
1b.Approach (from AD-416):
A testbed was developed in Marena, Oklahoma, which will compare soil moisture sensor technology for several years and develop a basis for sensor intercomparison. This testbed was begun with startup funds from NASA and it is planned to continue until the launch of the SMAP mission in 2015. This testbed has multiple technologies, including new technologies such as the COSMOS and GPS reflectometry soil moisture programs. Regular soil moisture and vegetation sampling will be conducted to support the ground truth of the sensors and intensive observation periods will be coordinated. The results will be extended to include verification and validation of watershed networks at several ARS locations throughout the U.S. To accomplish this, temporary networks will be developed and deployed to these watersheds for several months to provide more representative and higher density sampling than was previously available. This will result in a verified, quality controlled set of validation networks for satellite remote sensing of soil moisture, to include not only NASA missions, but ESA and JAXA missions.
Spectral reflectance of crops changes as crops emerge, grow, and mature. The temporal profiles of crop reflectance provide valuable information for identifying and estimating the areas of various crops of interest. Spectral reflectance and biophysical descriptors of various agronomic and horticultural crops were measured for selected crops as a function of crop growth and development. High resolution multispectral images were acquired to explore the spatial domain for identifying species.