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基于不同的光谱转换和建模方法,在金属废弃物区的土壤重金属的反转

Nannan Yang¹, Ling Han^1,2, Ming Liu¹

¹School of Land Engineering, Chang'an University, Xi'an, 710054, China.

|October 9, 2023

概括

超光谱遥感有效地监测矿山尾矿中的土壤重金属. 这项研究使用超光谱和模拟的多光谱数据开发了反转模型,证明了环境污染映射的可行性.

科学领域:

环境科学环境科学
遥感遥感遥感遥感
地质化学地质化学

背景情况:

矿产资源开采导致了严重的环境污染,特别是尾矿池土壤中的重金属污染.
传统的土壤分析方法对于大规模监测是劳动密集型和耗时的.
超光谱遥感为评估土壤重金属含量提供了一个强大的,非侵入性的替代方案.

研究的目的:

研究和开发用于估计金属尾矿地区重金属含量的反转模型.
评估超光谱和模拟多光谱数据对土壤重金属监测的有效性.
为了确定最佳的光谱变换和反转模型,以准确检测重金属.

主要方法:

获取和处理超光谱和模拟的Landsat8-OLI多光谱数据从金属废弃物地区.
频谱转换的应用,包括第二导数的光谱分析.
对八种重金属 (Cu,Cd,Cr,Ni,Pb,Zn,As,Hg) 进行倒置模型的开发和比较:逐步多重线性回归 (SMLR),部分最小平方回归 (PLSR) 和反向传播神经网络 (BPNN).

主要成果:

超频谱转换,特别是第二个导数,显著提高了模型准确性 (例如,Hg SMLR和PLSR训练调整R2至0.802).
使用denoised超频谱的BP神经网络模型显示了Cd,Ni和Hg的良好外推适用性 (训练和测试调整R2>0.5).
使用模拟多谱数据的PLSR模型在Cu和Hg方面取得了良好的结果 (训练和测试调整R2>0.5),Hg表现特别强 (调整R2为0.833和0.553).
通过使用最佳模拟多谱模型,成功检测和绘制Hg污染.

结论:

超光谱遥感,结合适当的数据转换和回归模型,是有效的监测土壤重金属污染在采矿区.
从高光谱数据中模拟多光谱数据是大规模重金属污染调查的可行方法,特别是对于像Hg.这样的元素.
该研究证明了遥感技术在环境管理和矿业受影响地区的修复方面的潜力.

关键词:

超光谱是指高光谱的模型反转模型的反转.多光谱模拟系统土壤中含有重金属.频谱变换的变化

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