The remote sensing-based estimation and spatial-temporal dynamic analysis of SOM in coal mining
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摘要: 土壤是储存碳的最大潜在储层,土壤有机质(soil organic matter,SOM)含量则是影响土壤碳的关键驱动因素,因此,SOM是分析土壤碳储量变化的重要指标。了解煤矿开采过程中光谱对SOM含量最佳响应波段以及整体煤矿区的SOM时空动态格局变化情况,以位于陕蒙交界的典型煤矿区为研究区,利用实测SOM、近地高光谱反射率和卫星多光谱反射率线性回归分析,对研究区2019年6月1日、7月4日和9月21日SOM变化进行定量分析,同时监测井工矿(大海则、巴拉素、纳林河二号、营盘壕)及其所在流域周边的SOM变化情况。结果表明: 与实测SOM对比,近地高光谱反射率一阶微分变换的SOM反演效果最佳。通过对高光谱、多光谱特征波段提取以及SOM相关性分析,建立回归反演模型,验证精度结果表明,反演SOM预测值与SOM实测值相关性达到0.90; 研究区内土壤有机质含量呈东高西低态势,河流上、中、下游及河口处SOM逐渐降低。采矿前模拟SOM含量得到结果与采矿过程中遥感估算的SOM相比高5%,说明煤矿开采在一定程度影响SOM含量。证明线性回归SOM反演模型具有推广应用前景。上述结果将对研究区土壤资源和生态环境定量研究、管理以及可持续发展提供依据。
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关键词:
- 成像高光谱 /
- 土壤有机质(SOM) /
- 煤矿 /
- 土壤含水量 /
- 高光谱遥感
Abstract: Soil is the largest potential reservoir of carbon, and the content of soil organic matter (SOM) is the key influencing factor of soil carbon storage. Therefore, SOM is an important index in the analysis of the changes in soil carbon storage. This paper aims to understand the optimal response bands in spectra to the SOM content in the process of coal mining and the changes in the temporal-spatial dynamic patterns of the SOM in a whole coal mining area. Based on the linear regression analysis of measured SOM, near-earth hyperspectral reflectance, and satellite multispectral reflectance, the SOM changes in the study area on June 1, July 4, and September 21, 2019 were quantitatively analyzed, and the SOM changes in underground coal mines (named Dahaize, Balasu, Nalinhe 2, and Yingpanhao) and their surrounding river basins were monitored. The SOM inversion results obtained using the first-order differential transformation of the near-earth hyperspectral reflectance were the closest to the measured SOM. A regression inversion model was established based on the extracted hyperspectral and multispectral characteristic bands and their correlation with the SOM. As indicated by the precision verification results, the correlation between the values predicted through SOM reversion and measured SOM values reached 0.90. Meanwhile, the SOM content in the study area was high in the east and low in the west and it gradually decreased along the upper, middle, and lower reaches of rivers and estuaries. The SOM content obtained through pre-mining simulation was 5% higher than that acquired via remote sensing-based estimation, indicating that coal mining affects the SOM content to a certain extent. It is also proven that the linear regression model of SOM inversion has the prospect of wide application. The above results will provide bases for quantitative research, management, and sustainable development of soil resources and ecological environment in the study area. -
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