Estimation of soil total nitrogen using the synthetic color learning machine (SCLM) method and hyperspectral data
作者： Lixin Lin , Zhiqiu Gao , Xixi Liu
DOI: 10.1016/J.GEODERMA.2020.114664
关键词:
摘要: Hyperspectral remote sensing is a potentially feasible, nondestructive and rapid tool for monitoring soil total nitrogen (TN) content. Nevertheless, soil color often decreases spectral reflectance and severely affects the accuracy of TN estimations. To improve TN estimation accuracy, the synthetic color learning machine (SCLM) method was presented in this study. This method combines machine learning concepts with rapid decoloring functions. Soil samples were collected from Renqiu, Cangzhou and Fengfeng, all located in Hebei …
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