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以浙江省临安市的山核桃为研究对象,基于2008—2011年连续4年的样地实测产量为基础,利用每年4个生长时期的Landsat TM遥感数据,系统地分析比较每个生长时期的植被指数与产量的关系。研究结果表明:NDVI在各个生长期均与产量的相关性最高;SAVI与产量的相关性居中,DVI最低。以每个时期的NDVI为因子,建立不同时期山核桃产量的预估模型。各时期模型的预估效果为果实膨大期>花芽分化及授粉期>采摘至落叶期>休眠期。以不同时期的NDVI为因子,利用逐步回归,建立多因子的山核桃产量的预估模型。最优预估模型为y=126.51_(x_2)+26.61_(x_1)+12.56_(x_3)-67.42(R~2=0.642,SEE=12.17),为山核桃产量的预测提供可行,快速,有效的方法。
Based on the actual production of plots in the four consecutive years from 2008 to 2011, Landsat TM remote sensing data of four growing periods were used to systematically analyze and compare the vegetation in each growth period The relationship between index and output. The results showed that: NDVI had the highest correlation with yield at each growth stage; the correlation between SAVI and yield was middle and DVI was the lowest. Using the NDVI of each period as a factor, a prediction model of hickory yield at different stages was established. The estimated results of the model for each period of fruit expansion period> flower bud differentiation and pollination period> picking to the deciduous period> dormant period. Using the NDVI in different periods as a factor, a stepwise regression was used to establish a multi-factor prediction model for the production of hickory. The optimal estimation model y = 126.51_ (x_2) + 26.61_ (x_1) + 12.56_ (x_3) -67.42 (R ~ 2 = 0.642, SEE = 12.17) provided a feasible, rapid, effective method.