基于净初级生产力的春小麦生产潜力及估产研究——以甘肃省白银区为例

利用2010年白银区春小麦生长季(4—7月)空间分辨率为250 m的MODIS影像和气象站点的气象数据,通过CASA模型建立了基于MODIS数据的春小麦净初级生产力遥感估算模型,估算出白银区春小麦生长季的净初级生产力(NPP),通过春小麦NPP与干物质转换关系计算出春小麦生产潜力。结果表明:白银区南部春小麦的NPP和生产潜力均大于北部地区,其NPP最小值为42 g C·m-2·a-1,最大值为402 g C·m-2·a-1,且春小麦的生产潜力有明显的季节性规律。根据春小麦生产潜力与实际产量的拟合关系建立了产量估测模型,并对该模型做了精度验证与实用性评价,结果显示该估产模型均方根误差RMSE为76.33 g·m-2,相对均方根误差RMSEr为23.51%。

Potential productivity and yield estimation of spring wheat based on a Net Primary Production model---Taking Baiyin district in Gansu province as an example

Based on the Carnegie Ames Stanford Approach (CASA), a net primary productivity (NPP) model for spring wheat was established with 250 m ×250 m MODIS remote images and weather station-based meteorological data in the Baiyin District at wheat growing season from April to July 2010. Through calculation on the transform relationship between NPP and dry matter, the potential productivity of spring wheat was estimated. The results showed that the NPP and potential productivity of spring wheat in south area were both greater than those in the north area of Baiyin District. The minimal value of NPP was 42 gC·m^-2·a^-1 and the maximal value was 402 gC·m^-2·a^-1. In the meantime, it was found that the production potential of spring wheat showed clear correlations with seasons. According to the actual wheat yield of per unit area and the potential productivity of spring wheat, the estimation model by regression analysis was established. Further tests were carried out to evaluate the accuracy and utilization of the model with a root mean square error (RMSE) at 76.33 g·m^-2 and a relative root mean square error (RMSEr) at 23.51%.