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Studies on soil organic matter content mapping using EO-1 hyperion data

机译:利用EO-1高离子数据绘制土壤有机质含量图的研究

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Soil organic matter content is an important indicator for soil fertility. The use of hyper-spectrum can conduct quantitative inversion on soil organic matter content for precision agriculture. Taking soil types in Jilin province of China as the research object, the author conducted the spectral measurements on treated soil samples under laboratory conditions by using ASD FieldSpec FR, and established the multiple regression model through the correlation analysis between the different variations of the spectral reflectance of the soil samples and soil organic matter content (SOM). SOM distribution map of study area was then obtained by using Hyperion images applied from the regression model through the band calculation module of ENVI software. Results showed that SOM content inversion regression model, which was established by employing the first derivate differential spectral reflectance at the wavelength of 492 nm, 663 nm, 1221 nm, 1317 nm and 2130 nm, possessed the best prediction accuracy. The coefficient of determination R2 was 0.909. The precision of SOM distribution map by using Hyperion images was 0.737. The hyper spectral inversion model of SOM could provide a new approach for the rapid determination of SOM for the precision agriculture.
机译:土壤有机质含量是土壤肥力的重要指标。利用高光谱可以对精确农业的土壤有机质含量进行定量反演。以吉林省土壤类型为研究对象,利用ASD FieldSpec FR在实验室条件下对处理过的土壤样品进行光谱测量,并通过光谱反射率不同变化之间的相关性分析建立多元回归模型。土壤样品和土壤有机质含量(SOM)。然后,使用回归模型通过ENVI软件的波段计算模块应用的Hyperion图像获得研究区域的SOM分布图。结果表明,采用一阶导数微分光谱反射率在492 nm,663 nm,1221 nm,1317 nm和2130 nm处建立的SOM含量反演回归模型具有最佳的预测精度。测定系数R2为0.909。使用Hyperion图像进行SOM分布图的精度为0.737。 SOM的高光谱反演模型可以为精密农业中SOM的快速确定提供一种新方法。

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