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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 #326223

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

Location: Hydrology and Remote Sensing Laboratory

Title: Retrieving soil moisture for non-forested areas using PALS radiometer measurements in SMAPVEX12 field campaign

Author
item Colliander, Andreas - Jet Propulsion Laboratory
item Njoku, Eni - Jet Propulsion Laboratory
item Jackson, Thomas
item Chazanoff, Seth - Jet Propulsion Laboratory
item Mcnairn, H. - Agriculture And Agri-Food Canada
item Powers, J. - Agriculture And Agri-Food Canada
item Cosh, Michael

Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/1/2016
Publication Date: 10/1/2016
Publication URL: http://handle.nal.usda.gov/10113/5566140
Citation: Colliander, A., Njoku, E., Jackson, T.J., Chazanoff, S., Mcnairn, H., Powers, J., Cosh, M.H. 2016. Retrieving soil moisture for non-forested areas using PALS radiometer measurements in SMAPVEX12 field campaign. Remote Sensing of Environment. 184:086-100.

Interpretive Summary: Aircraft-based Passive Active L-band System radiometer measurements conducted in the Soil Moisture Active Passive (SMAP Validation Experiment 2012 were used in combination with ground truth measurements to parameterize a soil moisture retrieval algorithm and to map soil moisture in the experiment domain. The vegetation and surface roughness model parameterization was done using radiometer-based low-altitude high-resolution measurements for three distinctively different land types. A reflectivity correction parameter was defined and tuned for each land type. It was found that for croplands on clay textured soils a constant roughness parameter is inadequate for modeling the range of observed brightness temperature values and soil moisture and rain event dependent reflectivity correction was applied. Sandy textured soils required only relatively modest tuning. The complex surface of grasslands (pastures) required larger adjustment. Using land cover, soil texture and other ancillary information with the derived algorithm parameters the mapping of the soil moisture in the domain was successfully carried out. The result was further improved by using a sub-grid modeling to decrease the effect of heterogeneity within the pixels. The experiment added to a series of field campaigns conducted in the context of SMAP pre-launch activities. These results will help refine the operational algorithms currently used with the SMAP satellite resulting in more accurate and reliable estimates.

Technical Abstract: In this paper we investigate retrieval of soil moisture based on L-band brightness temperature under diverse conditions and land cover types. We apply the PALS (Passive Active L-band System) radiometer data collected in the SMAPVEX12 (Soil Moisture Active Passive Validation Experiment 2012) field experiment which took place in southern Manitoba, Canada in 2012. The experiment domain covers croplands with high clay content as well as croplands and grasslands with sandy soils. A retrieval algorithm was parameterized for these land types. The formulation of the retrieval algorithm is based on a traditional surface scattering assumption. Based on this data set we found that for the clayey croplands the surface scattering assumption is inadequate, and that the algorithm needed significant tuning for the sandy soils. Empirically-based parameters for retrieving soil moisture under these conditions were developed. We also applied the parameterized algorithm to the retrieval of soil moisture for the entire experiment domain. We found that the use of sub-grid modeling improves the retrieval performance to a satisfactory level despite the challenging land types encountered.