用气象卫星资料估算吉林省主要农作物产量

Estimating of Main Crop Yields in Jilin Province Using Meteorological Satellite Data

摘要:

净第一性生产力（Npp）分析是全球变化研究中广为利用的方法，利用气象卫星资料获得年际植被指数（Iv）估算Npp建立不同作物的Npp与其产量的关系模型，即可实现对粮食总产和不同作物产量的估算。文中介绍了应用净第一性生产力遥感（NPP—RS）模型对吉林省粮食总产和主要作物产量进行估算的方法。采用NPP—RS模型，对1995～2000年吉林省的粮食总产及主要农作物玉米、水稻产量进行了动态估算。对粮食总产估产的平均相对误差为13．6％，玉米的平均相对误差为17．6％，水稻的平均相对误差为6．7％。要提高用此方法进行遥感估产的精度，还需要对当年的种植制度、种植结构的变化有所了解，注意当年的灾情，增加灾害影响系数。

Abstract:

Net primary productivity ( N _ pp ) is one of useful indexes in global change studies. Utilization of remote sensing data from meteorological satellites is an objective way to estimate N _ pp . Using the processed annual normalization vegetation index, N _ pp values can be estimated from an experimental model (NPP-RS). The relationship between each crop's N _ pp and yields was then determined. The total yields can be assessed by the N _ pp value. The total yields and the yields of main crops from 1995 to 2000 in Jilin Province were estimated. The mean relative error is 13.6% for total yields, and 17.6% and 6.7% for maize and rice, respectively.