Assessing interactions between crop biophysical parameters and X-band backscattering using empirical data and model sensitivity analysis

Active microwave remote sensing data at different frequencies can provide crucial information on crop morphology and conditions, thus effectively supporting agronomic management at different scales. In this work, we used variance-based global sensitivity analysis (GSA) as a quantitative framework for investigating the sensitivity of X-band backscattering to agronomic and morphological features typical of two different crops, maize and rice. To this end, we jointly exploited empirical data on crop status and growth, high-resolution TerraSAR-X data, and microwave radiative transfer model (RTM) simulations. Phenology-informed simulations allowed us to quantify the contributions of different scattering mechanisms for the two crops under varying observation setups, to assess the sensitivity of X-band backscattering to morpho-structural crop biophysical parameters (and their interactions), and to evaluate the effects of crop biomass on backscatter across growth stages.