Crop growth monitoring by simulation using satellite data

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Monitoring crop condition and production estimates at the prefecture level is important for food supply. The objectives of the study are (1) to estimate solar radiation on the ground by use of Geostationary Meteorological Satellite (GMS) data, (2) to develop a method estimating meteorological grid data by routine observation data on daily and hourly basis, and (3) to simulate crop growth on large areas by coupling of crop growth model and estimation model for meteorological data.In order to obtain solar radiation distribution, satellite observed images are effective. We have improved existing model for estimating solar radiation by use of clear sky recognition algorithm and land use data with RMS Error of 16%. Next, we have developed method for estimating grid meteorological data (air temperature, wind speed and sunshine duration) from routinely observed data on daily and hourly basis, by use of terrain factor analysis method. Estimated meteorological values by this method indicated an improvement of accuracy by 33% rather than existing method.In this study, we have demonstrated the use of a crop simulation model together with solar radiation data estimated by GMS images and meteorological data. The system showed rice yield predictions at RMS Error of 65.2kg/10a for Hokkaido prefecture in 2000, 2001 and 2002. We expect that the distribution of crop growth and crop yield by the simulation system developed in this study will be used for consulting farmers, analyzing crop damage by meteorological disaster and predicting crop yield change by climate change.