Estimation of Heavy Metals in Agricultural Soils Using Vis-NIR Spectroscopy with Fractional-Order Derivative and Generalized Regression Neural Network

Estimation of Heavy Metals in Agricultural Soils Using Vis-NIR Spectroscopy with Fractional-Order Derivative and Generalized Regression Neural Network

With the development of industrialization and urbanization, heavy metal contamination in agricultural soils tends to accumulate rapidly and harm human health. Visible and near-infrared (Vis-NIR) spectroscopy provides the feasibility of fast monitoring of the variation of heavy metals. This study exp...

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Bibliographic Details
Main Authors: Xitong Xu, Shengbo Chen, Liguo Ren, Cheng Han, Donglin Lv, Yufeng Zhang, Fukai Ai
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
visible and near-infrared spectroscopy
heavy metals
fractional-order derivative
optimal band combination algorithm
generalized regression neural network
Online Access:https://www.mdpi.com/2072-4292/13/14/2718

Internet

https://www.mdpi.com/2072-4292/13/14/2718

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