摘要
土壤是可持续发展的重要自然资源,也是人类生存环境的重要组成部分。近年来,伴随中国工业化、城镇化的快速发展,土壤重金属污染问题已经成为直接影响人类健康和区域生态环境的重要问题之一。传统土壤重金属含量检测方法费时费力,而高光谱遥感技术具有光谱信息丰富且波段连续等特点,可以实现大范围、非破坏性的土壤重金属含量定量反演及区域监测。以北京典型废弃金矿及周边地区的土壤砷含量为研究对象,野外采集土壤样品,利用便携式地物光谱仪室内测定土壤光谱曲线,分析土壤光谱与重金属砷含量的相关性并确定特征谱段,选用地理加权回归模型(GWR)和极限梯度提升回归树模型构建砷元素含量的定量反演模型,验证两个模型的建模精度,最后提出高光谱技术反演土壤砷含量的最优建模方法。研究结果表明:选用地理加权模型充分考虑了重金属含量与光谱变量间的空间相关性,该模型可适用于土壤砷含量高光谱定量反演;光谱变换可有效提升土壤光谱与砷含量之间的相关性,其中反射率倒数对数一阶微分光谱是估算土壤砷含量较好的指标,决定系数(R2)为0.8。由此可见,高光谱定量反演土壤重金属砷含量技术可行,为进一步开展区域范围内土壤重金属含量预测提供借鉴,从而对土地质量保护与管理具有现实指导意义。
Soil is an important natural resource for sustainable development and part of human living environment.In recent years,with the rapid development of industralization and urbanization in China,soil heavy metal pollution has become one of the critical problem that directly affect human health and regional ecological environment.Traditional method of soil heavy metal content detection is time and labor waste.In this paper,a new technology,hyperspectral remote sensing,was used to investigate the soil pollution by the non-destructive detecting with quantitative inversion of arsenic content.A typical abandoned gold mines and surrounding areas in Beijing has been taken as the study object,soil samples in the field have been collected,spectral curve of the samples were measured in the laboratory.Then the diagnostic spectra was analyzed and the inversion model of soil arsenic content was established with GWR model and XGBoost model.The results show that GWR model is more suitable for estimating soil arsenic content with hyperspectral because of fully considering about the spatial correlation between heavy metal content and spectral variables.Spectral transformation can effectively improve the correlation between soil spectrum and arsenic content,and the reciprocal logarithm first-order differential spectrum of reflectance is a better index for estimating soil arsenic content with the determination coefficient(R2)0.8.Therefore,the hyperspectral quantitative inversion of soil arsenic content is feasible,which will provide a reference for further prediction of soil heavy metal content in the region,and guide the land quality protection and management in Beijing.
作者
王颖
王志一
黄勇
张海龙
WANG Ying;WANG Zhiyi;HUANG Yong;ZHANG Hailong(Beijing Institute of Geology,Beijing 100195,China;China Institute of Geo-Environment Monitoring,Beijing 100081,China;Beijing Institute of Ecological Geology,Beijing 100120,China;Key Laboratory of Mine Ecological and Systematic Restoration,Ministry of Natural Resources,Beijing 100081,China)
出处
《世界核地质科学》
CAS
2023年第1期89-97,共9页
World Nuclear Geoscience
基金
中国地质调查局地质调查项目“矿山生态修复地质调查监测与信息集成”(编号:DD20221781)资助。