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Optimal Vegetation Indices for Winter Wheat Growth Status Based on Multi-Spectral Reflectance

机译:基于多光谱反射率的冬小麦生长状况最佳植被指数

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In order to select appropriate vegetation indices for winter wheat, field experiments with four levels of N-fertilizer (0, 30, 60, and 90 kg ha~(?1)) in two repetitions were conducted for three years. Hyper-spectral reflectance data using a portable field spectroradiometer (351 to 2,500 nm) were recorded from 10 am to 2 pm under cloudless conditions at two different growth stages of winter wheat. All two-band and three-band combinations of several vegetation indices were subsequently calculated in an algorithm for determining linear regression analysis against SPAD value, protein content, and grain yield. R square matrices were used to make contour plots and 3-D scatters. Using overlaying in analysis tools of ArcMap the between first and second year results, a number of common hot spots with strong correlations were revealed. The selected hot spots were validated with the dataset of the third year to choose the best vegetation indices for crop variable estimations.
机译:为了选择合适的冬小麦植被指数,三年两次进行了四个水平的氮肥(0、30、60和90 kg ha〜(?1))的田间试验。在无云的条件下,在冬小麦的两个不同生长阶段,从上午10点至下午2点使用便携式光谱仪(351至2500 nm)记录了高光谱反射率数据。随后在一种算法中计算了几种植被指数的所有两波段和三波段组合,以确定针对SPAD值,蛋白质含量和谷物产量的线性回归分析。 R正方形矩阵用于绘制等高线图和3-D散射。通过在ArcMap的分析工具中叠加第一年和第二年的结果,可以发现许多具有强烈相关性的常见热点。使用第三年的数据集对选定的热点进行了验证,以选择最佳植被指数进行作物变量估计。

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