Abstract

An accurate determination of the soil organic matter (SOM) levels present in reclaimed mine soil is necessary to evaluate the success of the ecological reclamation of mines. Visible and near-infrared diffuse spectroscopy is a fast and efficient method for collecting data for soil management during the reclamation of soil removed from mines. In this work, we used spectroscopy to characterize and estimate the SOM of lands from different reclamation years after coal mining in semi-arid grasslands of North China. Our goals were: (1) to explore the SOM characteristics and the spectra of reclaimed mine soil with different reclamation ages, and (2) to establish a reliable and accurate SOM prediction model by comparing support vector machine (SVM), partial least-squares regression (PLSR), and random forest (RF) modeling methods by determining the optimal preprocessing method and input spectral region. The results showed that spectral characteristics are useful indicators for understanding progressive SOM changes in the topsoil at different reclamation ages. RF is a more appropriate method for assessing the performance of a selected spectral region and provides more accurate results with a root mean square error (RMSE) of 4.34 g·kg⁻¹ between predicted and observed SOM values. This study provides an alternative method that uses spectroscopy to estimate reclaimed soil conditions for the environmental monitoring of mining sites.

摘要

准确确定矿山复垦土壤中存在的土壤有机质（SOM）的水平对于评估矿山生态复垦的成功是必要的。可见和近红外漫射光谱法是一种快速有效的方法，用于在从矿井中清除土壤的开垦期间收集土壤管理数据。在这项工作中，我们使用光谱学来表征和估算华北半干旱草原上采煤后不同开垦年限的土地的SOM。我们的目标是：（1）探索不同开垦年龄的矿山复垦土壤的SOM特征和光谱；（2）通过比较支持向量机（SVM），偏最小二乘建立一个可靠且准确的SOM预测模型回归（PLSR），确定最佳的预处理方法和输入光谱区域，从而建立随机森林（RF）建模方法。结果表明，光谱特征是了解不同开垦年龄下表土中SOM进行性变化的有用指标。射频是一种评估所选光谱区域性能的更合适的方法，并提供更准确的结果，均方根误差（RMSE）为4.34 g·kg预测SOM值与观察到的SOM值之间为^-1。这项研究提供了一种替代方法，该方法使用光谱法来估计开垦的土壤条件，以用于采矿场所的环境监测。