Inversion of heavy metal content in soil using hyperspectral characteristic bands-based machine learning method

Author:

Zou Zhiyong,Wang Qianlong,Wu Qingsong,Li Menghua,Zhen Jiangbo,Yuan Dongyu,Zhou Man,Xu ChongORCID,Wang Yuchao,Zhao Yongpeng,Yin Shutao,Xu Lijia

Funder

Sichuan Province Science and Technology Support Program

Publisher

Elsevier BV

Reference66 articles.

1. Prediction of the concentration of cadmium in agricultural soil in the Czech Republic using legacy data, preferential sampling, Sentinel-2, Landsat-8, and ensemble models;Agyeman;J. Environ. Manag.,2023

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3. Rapid retrieval of cadmium and lead content from urban greenbelt zones using hyperspectral characteristic bands;Arif;J. Clean. Prod.,2022

4. Using an ensemble model coupled with portable X-ray fluorescence and visible near-infrared spectroscopy to explore the viability of mapping and estimating arsenic in an agricultural soil;Biney;Sci. Total Environ.,2022

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