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

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.

Net primary productivity （Npp） is one of useful indexes in global change studies. Utilization of remote sensing data from meteorological satellites is an objective way to estimate Npp. Using the processed annual normalization vegetation index, Npp values can be estimated from an experimental model （NPP-RS）. The relationship between each crop＇s Npp and yields was then determined. The total yields can be assessed by the Npp 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.