A simple model of regional wheat yield based on NDVI data

The application of crop simulation models to yield estimation on a regional scale is generally constrained by the lack of spatially distributed information on major environmental and agronomic factors affecting crop conditions. The use of remote sensing data can circumvent this problem by providing actual estimates of these conditions with various spatial and temporal resolutions. The current paper presents the development and testing of a methodological framework which utilizes NDVI data taken from satellite platforms and a simulation model (CROPSYST) to estimate wheat yield. This operation relies on two main steps, the first being the computation of wheat above-ground biomass obtained through the use of NDVI-derived FAPAR estimates. The second step consists of the final repartition of the estimated biomass into crop yield, which is obtained through the use of an harvest index computed by integrating the CROPSYST development sub-model and NDVI data. The proposed methodology was applied in two Italian provinces where wheat is widely grown (Grosseto and Foggia). In both cases, attention was first devoted to the production of multi-year NDVI data sets descriptive of wheat conditions. Next, the current methodology was applied to estimate wheat yield. The results obtained showed the high accuracy of the method in estimating wheat yield at the provincial level. Correlation coefficients equal to 0.77–0.73 were obtained between measured and simulated crop yield, with corresponding root mean square errors (RSME) of 0.47 and 0.44 Mg/ha for Grosseto and Foggia, respectively.