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Inversion of vegetation biochemical material contents by remote sensing

机译:遥感植被生化材料含量的反演

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With remote sensing techniques, we could relate remote sensing measurements to the biochemical characteristics of the Earth surfaces in a reliable and operational way. It plays an important role in the estimate of the biochemical contents. The spectroscopic estimation of vegetation biochemical concentration was welcoming a new dawn with the developments of high spectral remote sensing technologies. Leafs of wheat at different grow period were used to measure reflectance spectra and biochemical components concentration. Reflectance spectra of leaf were measured by ASD field spectrometer in the spectra range of 350nm ~ 1650nm. Two kinds of statistical methods were used to inversion the biochemical concentrations: Stepwise regression analysis and partial least-squares regression, which were applied to established models of biochemical components concentrations (chlorophyll and water) with reflectance spectra of wheat's leaf at different grow period. The inversion results of two methods are: For chlorophyll, the correlation coefficient is 0.894, 0.898, and the relative standard deviation is 13.8%, 13.6% respectively; For water, the correlation coefficient is 0.983, 0.999, and the relative standard deviation is 2.3%, 0.3% respectively. Stepwise regression analysis method and partial least-squares regression method may inversion the chlorophyll and water of wheat' leaf at different grow periods.
机译:利用遥感技术,我们可以以可靠和运行的方式将遥感测量与地球表面的生物化学特性相关联。它在生化内容物的估计中起着重要作用。植被生化浓度的光谱估计是热心突发的新曙光,具有高光谱遥感技术的发展。使用不同长期的小麦叶子测量反射光谱和生物化学成分浓度。叶片的反射光谱通过ASD场光谱仪在350nm〜1650nm的光谱范围内测量。两种统计方法用于反转生化浓度:逐步回归分析和部分最小二乘回归,其应用于不同生长期间小麦叶片反射光谱的生化成分浓度(叶绿素和水)的建立模型。两种方法的反演结果是:对于叶绿素,相关系数为0.894,0.898,相对标准偏差分别为13.8%,13.6%;对于水,相关系数为0.983,0.999,相对标准偏差分别为2.3%,0.3%。逐步回归分析方法和部分最小二乘回归方法可以反转不同生长期小麦叶的叶绿素和水。

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