Inversion of soil properties in rare earth mining areas (southern Jiangxi, China) based on visible-near-infrared spectroscopy
文献类型：期刊论文
| 作者 | Guo, Jiaxin2,4; Zhao, Xiaomin2,4; Guo, Xi2,4; Zhu, Qing1; Luo, Jie2,4; Xu, Zhe3; Zhong, Liang2,4; Ye, Yingcong2,4 |
| 刊名 | JOURNAL OF SOILS AND SEDIMENTS
 |
| 出版日期 | 2022-06-17 |
| 页码 | 16 |
| 关键词 | Visible-near-infrared spectroscopy Rare earth mine Soil organic carbon Extreme gradient boosting |
| ISSN号 | 1439-0108 |
| DOI | 10.1007/s11368-022-03242-8 |
| 通讯作者 | Zhao, Xiaomin(zhaoxm889@126.com) |
| 英文摘要 | Purpose Traditional measurement for soil properties is time-consuming and costly, while visible-near-infrared spectroscopy enables the rapid prediction of soil properties. In this study, visible-near-infrared spectroscopy was used to predict these four soil properties including OC (organic carbon) content, TN (total nitrogen) content, pH value, and clay content in rare earth mining areas based on different spectral transformation and calibration methods. Materials and methods A total of 232 soil samples were collected from unexploited, in situ leaching, and heap leaching mining areas in southern Jiangxi Province, China. The chemical properties and reflectance spectra of air-dried samples were measured. Spectral transformations including first-order derivative (FOD), continuum removal (CR), and continuous wavelet transform (CWT) were selected to improve the prediction accuracy of the model. Partial least-squares regression (PLSR), the support vector machine (SVM), and extreme gradient boosting (XGBoost) were used to construct prediction models. Results and discussion The highest prediction accuracies in terms of the coefficient of determination (R-2), root mean square error (RMSE), and relative prediction deviation (RPD) were obtained using CWT spectra with XGBoost for organic carbon content (R-2 = 0.89, RMSE = 0.24, RPIQ = 4.67), total nitrogen content (R-2 = 0.86, RMSE = 0.01, RPIQ = 4.14), and pH value (R-2 = 0.73, RMSE = 0.19, RPIQ = 1.66). The best prediction result for clay content was obtained using CWT spectra with the SVM (R-2 = 0.67, RMSE = 6.45, RPIQ = 2.75). Conclusions The CWT coupled with a non-linear model, such as XGBoost, is an effective method for the accurate prediction of soil properties in rare earth mining areas. |
| WOS关键词 | ORGANIC-MATTER ; TOTAL NITROGEN ; REFLECTANCE SPECTROSCOPY ; LEAST-SQUARES ; REGRESSION ; SPECTRA ; CARBON ; MODEL ; DECOMPOSITION ; EXTRACTION |
| 资助项目 | National Key R&D Program of China[2020YFD1100603-02] |
| WOS研究方向 | Environmental Sciences & Ecology ; Agriculture |
| 语种 | 英语 |
| WOS记录号 | WOS:000812467300002 |
| 出版者 | SPRINGER HEIDELBERG |
| 资助机构 | National Key R&D Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/179788]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhao, Xiaomin |
| 作者单位 | 1.Shanghai Jiao Tong Univ, Sch Design, Shanghai 200240, Peoples R China 2.Key Lab Poyang Lake Watershed Agr Resources & Eco, Nanchang 330045, Jiangxi, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 4.Jiangxi Agr Univ, Acad Land Resource & Environm, Nanchang 330045, Jiangxi, Peoples R China |
| 推荐引用方式 GB/T 7714 | Guo, Jiaxin,Zhao, Xiaomin,Guo, Xi,et al. Inversion of soil properties in rare earth mining areas (southern Jiangxi, China) based on visible-near-infrared spectroscopy[J]. JOURNAL OF SOILS AND SEDIMENTS,2022:16. |
| APA | Guo, Jiaxin.,Zhao, Xiaomin.,Guo, Xi.,Zhu, Qing.,Luo, Jie.,...&Ye, Yingcong.(2022).Inversion of soil properties in rare earth mining areas (southern Jiangxi, China) based on visible-near-infrared spectroscopy.JOURNAL OF SOILS AND SEDIMENTS,16. |
| MLA | Guo, Jiaxin,et al."Inversion of soil properties in rare earth mining areas (southern Jiangxi, China) based on visible-near-infrared spectroscopy".JOURNAL OF SOILS AND SEDIMENTS (2022):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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