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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 #343485

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: Modeling L-band synthetic aperture radar observations through dielectric changes in soil moisture and vegetation over shrublands

item KIM, S. - Jet Propulsion Laboratory
item ARII, M. - Collaborator
item Jackson, Thomas

Submitted to: IEEE Journal of Selected Topics in Applied Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/22/2017
Publication Date: 11/1/2017
Citation: Kim, S., Arii, M., Jackson, T.J. 2017. Modeling L-band synthetic aperture radar observations through dielectric changes in soil moisture and vegetation over shrublands. IEEE Journal of Selected Topics in Applied Remote Sensing. 10:4753-62.

Interpretive Summary: An electromagnetic model to support the retrieval of soil moisture using radar observation over shrublands was developed and validated using aircraft-based observations. Radar instruments are capable of very high spatial resolution measurements; however, confounding factors such as vegetation structure and dielectric properties require more complex models that can adequately represent specific canopy types. Here, studies were conducted over shrublands, which cover approximately 20% of the global land surface. Airborne observations were used to validate the model over a site in California. A new finding was that a physics-based approach (the use of the dielectric control of vegetation water content) was necessary in order to accurately simulate the observations, instead of calibrating the model as commonly performed. The results contribute to a more robust set of soil moisture retrieval algorithms that can be implemented with current and future radar satellites.

Technical Abstract: L-band airborne synthetic aperture radar observations were made over California shrublands to better understand the effects by soil and vegetation parameters on backscatter. Temporal changes in radar backscattering coefficient (s0) of up to 3 dB were highly correlated to surface soil moisture but not to vegetation, even though vegetation water content (VWC) varied by a factor of two seasonally. HH was always greater than VV, suggesting the importance of double-bounce scattering by the woody parts. However, the geometric and dielectric properties of the woody parts did not vary significantly over time. Instead the changes in VWC occurred primarily in thin leaves that may not meaningfully influence absorption and scattering. A physically-based model for single scattering by discrete elements of plants successfully simulated the magnitude of the temporal variations in HH, VV, and HH/VV with a difference of less than 0.9 dB for both the mean and standard deviation when compared with the airborne data. In order to simulate the observations, the VWC input of the plant to the model was formulated as a function of plant’s dielectric property (water fraction) while the plant geometry remains static in time. In comparison, when the VWC input was characterized by the geometry of a growing plant, the model performed poorly in describing the observed patterns in the s0 changes. The analysis of the model result indicates that the dominant mechanisms for HH and VV are double-bounce scattering by trunk, and soil surface scattering, respectively. The time-series inversion of the physical model was able to retrieve soil moisture with the difference of -0.037 m3/m3 (mean), 0.025 m3/m3 (standard deviation), and 0.89 (correlation), which demonstrates the efficacy of the model-based time-series soil moisture retrieval for shrublands.