Combining a crop growth model with satellite images to get better insight in wheat growth

Abstract

The overall goal of better crop management that is expected to contribute to food security relies on the idea of being able to predict end-of-season yield early in the growing season and adapt crop management strategies (e.g. fertilization) to the expected seasonality trend (weather forecasts). The goal of this study was to investigate the potential of combining crop growth models with satellite image-based information for prediction of in-season plant development. Satellite image-based leaf area index (LAI) estimates were compared to crop model simulations at two locations: Heidfeldhof and Eckartsweier, both University of Hohenheim research stations. Crop model simulated LAI was compared to vegetation index (VI) based LAI for the Heidfeldhof location resulting in RMSE 0.78 and 0.312 nRMSE based on 24 measurements. For the Eckartsweier location, VI-based LAI had 1.4 RMSE and 0.573 nRMSE based on 8 measurements.