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Algorithms for the Estimation of the Concentrations of Chlorophyll A and Carotenoids in Rice Leaves from Airborne Hyperspectral Data

机译:估计水稻叶片叶绿素A和类胡萝卜素浓度的算法从机载高光谱数据

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Algorithms based on reflectance band ratios and first derivative have been developed for the estimation of chlorophyll a and carotenoid content of rice leaves by using airborne hyperspectral data acquainted by Pushbroom Hyperspectral Imager (PHI). There was a strong R680/R825 and chlorophyll a relationship with a linear relationship between the ratio of reflectance at 680nm and 825nm. The first derivative at 686 nm and 601 nm correlated best with carotenoid. The relationship between the ratio of R680/R825 and chlorophyll a relationship, the first derivative at 686 nm and carotenoid concentration were used to develop predictive regression equations for the estimation of canopy chlorophyll a and carotenoid concentration respectively. The relationship was applied to the imagery, where a chlorophyll a concentration map was generated in XueBu, which is one of the sites for rice.
机译:基于反射带比和第一衍生物的算法已经开发用于估计水稻叶片的叶绿素A和类胡萝卜素含量通过使用推车高光谱数据仪(PHI)识别。在680nm和825nm的反射率比与825nm之间的反射比率之间存在强大的R680 / R825和叶绿素的关系。在686nm和601nm处的第一种衍生物最佳地与类胡萝卜素相关。 R680 / R825和叶绿素的关系与叶绿素的关系,在686nm处的第一种衍生物和类胡萝卜素浓度分别用于分别开发用于估计冠层叶绿素A和类胡萝卜素浓度的预测回归方程。该关系被应用于图像,其中在Xuebu产生叶绿素浓度图,这是米饭的一个位点。

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