Annual rates of gain in crop yields are far below those needed to meet global food needs at 2050. Accelerating progress depends on finding highly efficient methods for measuring plant traits in crop improvement programs. While great progress is being made in using image-based approaches, especially from unmanned aerial vehicles, these methods become limited when the canopy becomes too dense to see into. The work to be reported shows the potential to overcome this problem by using microwave radar to which plant canopies are moderately transparent. Exploiting this technology requires a combination of 3D modeling, microwave scattering calculations, and scattering inversion methods, all of which are computationally intensive (e.g. repeated pseudoinverse solving of 80K x 40K matrices for each plot). An overview of the computational methods will be included in the talk. 

Presenter(s)

Stephen Welch