4.7 Article

Assessing soil organic matter of reclaimed soil from a large surface coal mine using a field spectroradiometer in laboratory

期刊

GEODERMA
卷 288, 期 -, 页码 47-55

出版社

ELSEVIER
DOI: 10.1016/j.geoderma.2016.10.033

关键词

Reclamation; Spectroscopy; Soil organic matter; Large surface mining; PLS-SVM

资金

  1. National Natural Science Foundation of China [41401233]
  2. Fundamental Research Funds for the Central Universities [N120801001]
  3. Geological Survey and Mineral Resources Assessment Project [12120113002600]

向作者/读者索取更多资源

Soil organic matter (SOM) for topsoil is one of most important indicators to support the success of mine ecological reclamation. SOM varies along the artificial mine landscape characterized by different bench-slopes of dump. Reflectance using field spectroscopy can provide useful information on the assessment of punctual soil variation, and has the advantages of speed and efficiency. The aims of this study were to 1) explore the characteristic spectrum of reclaimed soil of different landforms, 2) develop a key spectral-ratio index for evaluating SOM content, and 3) establish a SOM prediction model using the Partial Least Square Regression-Support Vector Machine (PLS-SVM) method. Based on comprehensive analysis of the relationship between SOM content and corresponding spectral reflectance in soils from different landforms, the results showed a new derived spectral index would be useful for estimating SOM. The ratio spectral index (R-2294nm/R-2286 (nm)), calculated using available wavebands in the 350-2500 nm region, was proposed for use in the reliable estimation of SOM from downslope and midslope. The PLS-SVM calibration model for the raw spectrum, showed a high predictive accuracy for estimating the SOM content, with cross-validated R-2 of 0.95, and RMSE of 0.12. These outcomes provide a theoretical basis and technical support for estimations of SOM content using visible/near-infrared spectra in reclamation areas. It is proposed that the spectral difference index and model undergo further testing and optimization prior to wider application for observation of mine-reclamation ecosystems. (C) 2016 Elsevier B.V. All rights reserved.

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