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Inversion of a canopy reflectance model using hyperspectral imagery for monitoring wheat growth and estimating yield

机译：利用高光谱图像对冠层反射率模型进行反演，以监测小麦生长并估算产量

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Applications of hyperspectral remote sensing data to derive relevant properties for precision agriculture are described. Green leaf area index, fraction of senescent material and grain yield are retrieved from the hyperspectral data. Two sensors were used to obtain these data; the airborne visible/infrared imaging spectrometer AVIS and the space-borne compact high-resolution imaging spectrometer CHRIS; they show the applicability of the methods to different spatial scales. In addition, the bi-directional observation capability of the CHRIS sensor is used to derive information about the average leaf angle of the canopies which are used to link canopy structure with phenological development. Derivation of the canopy properties, green leaf area index and fraction of senescent material was done with the radiative transfer model, SLC (soil–leaf–canopy). The results were used as input into the crop growth model PROMET-V to calculate grain yield. Two years of data from the German research project preagro are presented.
机译：描述了高光谱遥感数据在推导精密农业相关特性方面的应用。从高光谱数据中检索绿叶面积指数，衰老物质的比例和谷物产量。使用两个传感器获取这些数据。机载可见/红外成像光谱仪AVIS和星载紧凑型高分辨率成像光谱仪CHRIS；他们显示了该方法在不同空间尺度上的适用性。此外，CHRIS传感器的双向观察功能可用于获取有关冠层平均叶角的信息，该信息用于将冠层结构与物候发展联系起来。冠层特性，绿叶面积指数和衰老物质的比例的推导是通过辐射传递模型SLC（土壤-叶-冠层）进行的。将结果用作作物生长模型PROMET-V的输入，以计算谷物产量。介绍了德国研究项目preagro的两年数据。

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