Crop growth monitoring by simulation using satellite data

使用卫星数据进行模拟监测作物生长

• 批准号: 13660259
• 负责人: TANI Hiroshi
• 金额: $ 2.18万
• 依托单位: HOKKAIDO UNIVERSITY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2001
• 资助国家: 日本
• 起止时间: 2001 至 2002
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-13660259/
• 关键词: Satellite data; Solar radiation; AMeDAS Data; Crop growth model; Simulation

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.

在地级监测作物状况和产量估计对粮食供应很重要。本文的研究目标是：(1)利用地球同步气象卫星（GMS）数据估算地面太阳辐射；(2)利用日常观测资料逐日和逐时估算气象网格数据；(3)利用作物生长模型和气象数据估算模型耦合模拟大面积作物生长。为了获得太阳辐射的分布，卫星观测图像是有效的。利用晴空识别算法和土地利用数据对现有太阳辐射估算模型进行改进，均方根误差为16%。其次，我们开发了利用地形因子分析法，从每日和每小时的常规观测数据估计网格气象数据（气温、风速和日照时数）的方法。用该方法估算的气象值精度比现有方法提高了33%。在这项研究中，我们演示了将作物模拟模型与GMS图像和气象数据估计的太阳辐射数据结合使用。该系统显示，2000年、2001年和2002年北海道地区水稻产量预测的均方根误差为65.2kg/10a。我们期望通过本研究开发的模拟系统，可以为农民提供咨询，分析气象灾害对作物的危害，预测气候变化对作物产量的影响。