首页|基于光谱分析的土壤重金属含量估算研究——以三江源区玉树县和玛多县为例

基于光谱分析的土壤重金属含量估算研究——以三江源区玉树县和玛多县为例

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以三江源区玉树县和玛多县为研究区,利用实验室测定的As、Cu、Pb、Zn、Cr、Cd、Hg元素含量和室内采集的土壤原始光谱及其4种转换形式,建立了光谱指标与重金属含量的多元回归模型,利用决定系数(R2)、相对分析误差(RPD)及均方根误差(RMSE)评价模型的精度.研究结果表明,土壤As、Cu、Pb、Zn、Cr、Cd含量与SOM、Fe、Mn、A1、Mg等元素具有显著相关关系,Hg元素则未达到显著性水平.As、Cu、Pb、Zn、Cr和Cd元素估算模型回归方程R2达到了0.5以上,均通过了显著性检验,其中Pb、Zn和Cr元素验证样本RPD均达到了1.4以上,模型具备粗略估算能力;As、Cu和Cd元素验证样本RPD均低于1.4,模型不具备粗略估算能力.Hg元素估算模型回归方程的R2为0.28,未能通过显著性检验,无法用于对Hg含量的估算.
Estimating Heavy Metal Contents for Topsoil Based on Spectral Analysis——A Case Study of Yushu and Maduo Counties in the Three-River Source Region
Based on soil reflectance spectral measured indoor by ASD Field Spec 4 and heavy metal contents including As,Cu,Pb,Zn,Cr,Cd,Hg measured in laboratory,the stepwise regression equations were established between spectral indices and soil heavy metal contents respectively,and prediction ability of models was assessed using coefficient of determination (R2),the ratio of standard error of prediction to standard deviation (RPD),root mean square error (RMSE).The results showed that the soil heavy metals (As,Cu,Pb,Zn,Cr,Cd) was well correlated with the soil organic,Fe,Mn,Al and Mg.The coefficients of determination (R2) of estimation models on As,Cu,Pb,Zn,Cr and Cd were all over 0.5,higher than the significance level.The ratio of standard error of prediction to standard deviation (RPD) of verification samples on Pb,Zn and Cr were all reached 1.4,which showed that the model had rough estimating capacity.The ratio of standard error of prediction to standard deviation (RPD) of verification samples on As,Cu and Cd were all below 1.4,which showed the lower precision.The coefficient of determination (R2) of estimation model of Hg was 0.28,lower than significance level,which showed the model is unreliable.

Soil heavy metalHyperspectralSoil spectral featuresthe Three-River Source RegionYushu CountiesMaduo Counties

张威、高小红、杨扬、李金山、张艳娇、田成明、贾伟、冯玲、马永录

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青海师范大学生命与地理科学学院,青藏高原环境与资源教育部重点实验室,青海省自然地理与环境过程重点实验室,西宁810008

华东理工大学资源与环境工程学院,国家环境保护化工过程环境风险评价与控制重点实验室,上海200237

青海省有色地质测试中心,西宁810008

土壤重金属 高光谱 土壤光谱特征 三江源区 玉树县 玛多县

青海省科技厅自然科学基金青海师范大学创新基金资助

2011-Z-903

2014

土壤
中国科学院南京土壤研究所

土壤

CSTPCDCSCD北大核心
影响因子:1.052
ISSN:0253-9829
年,卷(期):2014.46(6)
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