Crop growth monitoring by simulation using satellite data

在州一级监测作物状况和产量估计对粮食供应很重要。本研究的目的是：（1）利用静止气象卫星（GMS）资料估算地面太阳辐射;（2）建立利用逐日和逐时常规观测资料估算气象网格资料的方法;（3）通过作物生长模型与气象资料估算模型的耦合，模拟大面积作物生长。卫星图像是有效的。利用晴空识别算法和土地利用数据对现有的太阳辐射估算模型进行了改进，均方根误差为16%。其次，我们开发了方法来估计网格气象数据（气温，风速和日照时数）从日常观测数据的每日和每小时的基础上，通过使用地形因子分析方法。通过这种方法估计的气象值表明，精度提高了33%，而不是现有的method.In这项研究中，我们已经证明了使用的作物模拟模型与太阳辐射数据估计GMS图像和气象数据。该系统对北海道县2000年、2001年和2002年的水稻产量进行了预测，均方根误差为65.2 kg/10 a。本研究所开发的作物生长与产量模拟系统，可用于指导农户决策、分析气象灾害对作物的危害以及预测气候变化对作物产量的影响。

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.