Location: Hydrology and Remote Sensing LaboratoryTitle: Multiple scattering effects with cyclical terms in active remote sensing of vegetated surface using vector radiative transfer theory
|Liao, T. - University Of Washington|
|Kim, S. - Jet Propulsion Laboratory|
|Tan, S. - University Of Michigan|
|Tsang, L. - University Of Michigan|
|Su, C. - University Of Washington|
Submitted to: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/15/2016
Publication Date: 4/1/2016
Publication URL: http://handle.nal.usda.gov/10113/5729142
Citation: Liao, T., Kim, S., Tan, S., Tsang, L., Su, C., Jackson, T.J. 2016. Multiple scattering effects with cyclical terms in active remote sensing of vegetated surface using vector radiative transfer theory. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 9(4):1414-1429.
Interpretive Summary: Energy transport in a vegetated surface layer was examined by solving the vector radiative transfer equation using a numerical iterative approach. This approach accounts for higher order effects that include multiple scattering. Multiple scattering effects are important when the optical thickness and scattering albedo of the vegetation layer are large. The approach was validated against the a corn dataset collected in a field campaign. Since the ultimate goal of this work is improving soil moisture retrieval, the model’s performance was validated further in terms of soil moisture retrieval. Improved accuracy in microwave-based soil moisture retrieval will lead to wider integration in hydrologic and agricultural applications.
Technical Abstract: The energy transport in a vegetated (corn) surface layer is examined by solving the vector radiative transfer equation using a numerical iterative approach. This approach allows a higher order that includes the multiple scattering effects. Multiple scattering effects are important when the optical thickness and scattering albedo of the vegetation layer are large. When both the albedo and the optical thickness exceed 0.4, higher orders contribute significantly (e.g., v-pol at L-band; Ku-band). The approach is applied to vegetated surfaces using typical crop structure for backscattering from L-band to Ku-band. For corn fields at L-band, multiple scattering effect is more important for VV. For example, when VWC is 3 kg/m2, the deviation between 1st order and multiple scattering for VV could be 6.5 dB while 2dB for HH. The iterative approach also allows the separation of the contribution to backscattering from each scattering order and scattering mechanism. Each scattering mechanism is associated with a unique scattering path. By examining the duality of the paths, we are able to identify the cyclical terms with existence of a reflective boundary. The cyclical correction to the backscattering accounts for backscattering enhancement effects on the co-polarization by a factor of two. The approach is validated against the SMAPVEX12 L-band corn dataset over the entire crop growth and large soil moisture variations. The model prediction matches the observation with 1.93 dB and 1.46 dB RMSE for VV and HH, respectively, while correlations are 0.67 and 0.88. Time-series retrieval is also applied successfully for both soil moisture and VWC with 0.06 cm^3/cm^3 and 0.44 kg/m^2 RMSE, respectively, while correlations are 0.7 and 0.92. For large VWC, this approach corrects the underestimated backscatters in the single scattering caused by the attenuation and shows the increase of backscatter in dB from multiple scattering is proportional to the optical thickness.