Predicting wheat production at regional scale by integration of remote sensing data with a simulation model

Raymond E.E. Jongschaap , Léon S.M. Schouten

Optical remote sensing satellite data (SPOT HRV XS, Landsat 5 TM) were used to estimate winter wheat area in a pilot area of 5 × 5 km in the Southeast of France. The approach was scaled up to a larger area of 45 × 50 km and finally to the regional level covering several departments. Microwave remote sensing data (ERS SAR C-band) were used to estimate regional wheat flowering dates to calibrate a wheat growth simulation model used to calculate wheat yields, subsequently used to estimate regional wheat production. Soil maps were used to spatially vary model input parameters for the region. Wheat area could be estimated with more than 80% users' accuracy and model-based estimates of regional wheat production were in agreement with agricultural statistics. These results demonstrate that results from point-based simulation models can be applied at spatially higher levels with the aid of remote sensing data.

Mots clés: Landsat; SPOT; ERS SAR C-band; classification; simulation model; calibration; point to region scaling; wheat; flowering date

Domaines: Sciences agricoles; Ecologie, Environnement

Raymond E.E. Jongschaap, Léon S.M. Schouten. Predicting wheat production at regional scale by integration of remote sensing data with a simulation model. Agronomy for Sustainable Development, 2005, 25 (4), pp.481-489. ⟨hal-00886312⟩