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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #361025

Research Project: Integrating Remote Sensing, Measurements and Modeling for Multi-Scale Assessment of Water Availability, Use, and Quality in Agroecosystems

Location: Hydrology and Remote Sensing Laboratory

Title: Development of high resolution soil moisture validation networks in Central Iowa, USA

item Cosh, Michael
item THOMAS, JACKSON - Collaborator
item COLLIANDER, A. - Jet Propulsion Laboratory
item Prueger, John
item KRAJEWSKI, W. - University Of Iowa
item HORNBUCKLE, B. - University Of Iowa
item CHAN, S. - Jet Propulsion Laboratory
item McKee, Lynn

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 3/1/2019
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Traditional satellite validation requires substantial in situ resources across large scales to match passive microwave satellite resolutions. With current and future active microwave missions, the need for higher resolution validation sites is increasing at multiple scales. Typical scales for passive remote sensing validation networks are in the 25 km by 25 km range, but new technologies are pushing this scale down to 100 m or less. Landscape heterogeneity decreases as the resolution increases, especially for agricultural areas with large field sizes. The land management practices also have a spectrucm of influences across these scales, so a one size fits all approach to landscape scaling functions may no longer be valid. This study analyzes the ability of a permanent network to estimate field scale soil moisture, from physical sampling, and temporary networks. The field site used for this study was the South Fork watershed, which was the study domain of the Soil Moisture Active Passive Validation Experiment 2016 (SMAPVEX16). This is a primarily row crop agriculture watershed with 50 % corn and 25% soybean fields as of 2016. There are twenty semi-permanent soil moisture stations deployed across a pixel of approximately 36 km by 36 km. These sites have been validated at resolutions of 36, 9, and 3 km with various degrees of success. During the summer of 2016, a large scale temporary network was also deployed in the region with several scaling resolutions to provide a greater number of stations with which to compute large scale soil moisture estimates. Lastly, field sampling was conducted by scientists during intensive observation periods in the spring and summer of 2016, providing a detailed map of soil moisture variation from the 100 m to 3 km scale. Results of this study will provide an estimate of the average and variation of soil moisture across these scales with implications on the remote sensing of large scale agricultural regions.