FutureWater has started a project that evaluates the added value of high-resolution satellite imagery above coarse resolution satellite imagery in crop yield forecasting. FutureWater undertakes this project in collaboration with the Soil Physics and Land Management Group of Wageningen University and eLeaf. This project is commissioned by CCAFS and funded by CIAT.
The question of high vs. coarse-resolution satellite imagery in crop yield forecasting is especially relevant if the focus is on small-scale farming where the distribution of crop types is often extremely heterogeneous; meaning that the uncertainty in the spatially distributed model input parameters (soil properties, crop parameters, etc.) becomes larger. For the current study we will use the Soil-Water-Atmosphere-Plant (SWAP) model in combination with LAIs and crop factors (KCs) which were retrieved from remote sensing. Subsequently the SWAP model will be run for i) a representative MODIS pixel (coarse-resolution), containing a mixture of berseem, wheat, build-up area, and another crop, and ii) for 256 ASTER pixels (high-resolution) in which each pixel represents a unique land-use class within that MODIS pixel. The test area for this project is the Meet Yazid command area in Egypt.