基于高光谱的土壤重金属镉、汞、铅含量估算研究
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摘要
使用ASD FieldSpec HR(350～2500nm)地物光谱仪,对采自陕西省扶风县、杨凌县、武功县的44个土壤样品进行原始光谱反射率测定。采用MSC、SNV、NOR,结合FD、SD、LOG变换,使用PLSR建立Cd、Hg、Pb三种土壤重金属元素的最优高光谱估算模型。研究结果表明:研究区域存在较为严重的Hg污染现象,Cd含量接近临界值;反射光谱经过NOR、MSC、SNV变换后显著提高了反射光谱的信噪比,结合不同微分变换有效提升模型的稳定性和普适性;采用PLSR法建立的Cd、Hg、Pb三种土壤重金属光谱最优模型的建模精度分别为0.545 1、0.991 2、0.618 2;针对不同重金属元素,基于不同的处理方法建立的最优估算模型预测能力较好,可以实现该区域重金属含量监测。
The original spectral reflectance of 44 soil samples collected from Fufeng county,Yangling county and Wugong county of Shaanxi province was measured using ASD FieldSpec HR(350～2500 nm)spectrometer.The optimal hyper spectral estimation model of three heavy metal elements of soil Cd,Hg,Pb in this area was established by using PLSR and transformation of MSC,SNV,NOR combined with FD,SD,LOG.The results show that there is a serious Hg pollution phenomenon in the study area,and the Cd content is close to the critical value.The reflection spectrum is significantly improved by the NOR,MSC and SNV transformation,and the stability and general applicability of the model is improved by combining different differential changes.The modeling accuracy of three heavy metal spectral optimal models of Cd,Hg and Pb established by PLSR method are 0.5451,0.9912 and 0.6182 respectively;the optimal estimation models based on different processing methods for different heavy metal elements are good,which have good predictive ability and can realize heavy metal content monitoring in this area.
The original spectral reflectance of 44 soil samples collected from Fufeng county,Yangling county and Wugong county of Shaanxi province was measured using ASD FieldSpec HR(350～2500 nm)spectrometer.The optimal hyper spectral estimation model of three heavy metal elements of soil Cd,Hg,Pb in this area was established by using PLSR and transformation of MSC,SNV,NOR combined with FD,SD,LOG.The results show that there is a serious Hg pollution phenomenon in the study area,and the Cd content is close to the critical value.The reflection spectrum is significantly improved by the NOR,MSC and SNV transformation,and the stability and general applicability of the model is improved by combining different differential changes.The modeling accuracy of three heavy metal spectral optimal models of Cd,Hg and Pb established by PLSR method are 0.5451,0.9912 and 0.6182 respectively;the optimal estimation models based on different processing methods for different heavy metal elements are good,which have good predictive ability and can realize heavy metal content monitoring in this area.
引文
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[12]解宪丽,孙波,郝红涛.土壤可见光-近红外反射光谱与重金属含量之间的相关性[J].土壤学报,2007,44(6):982-993.
[13]郭云开,周烽松,丁美青,等.水稻冠层与土壤高光谱反演土壤重金属对比研究[J].遥感信息,2017(2):173-179.
[14]张秋霞,张合兵,张会娟,等.粮食主产区耕地土壤重金属高光谱综合反演模型[J].农业机械学报,2017,48(3):148-155.
[15]董霁红,丁敏,赵银娣,等.矿区复垦土壤重金属含量分布与光谱特征研究---以徐州市柳新矿区为例[J].中国矿业大学学报,2012,41(5):827-832.
[16]邬登巍,吴昀昭,马宏瑞.基于中红外漫反射光谱的土壤重金属元素含量预测研究[J].光谱学与光谱分析,2010,30(6):1498-1502.
[17]刘硕,吴泉源,张龙龙,等.基于野外实测光谱的污灌区土壤重金属污染快速监测[J].安全与环境学报,2015,15(2):297-302.
[2]Wang J,Cui L,Gao W,et al.Prediction of low heavy metal concentrations in agricultural soils using visible and near-infrared reflectance spectroscopy[J].Geoderma,2014,216(4):1-9.
[3]Wu Y Z,Chen J,Wu X M,et al.Possibilities of reflectance spectroscopy for the assessment of contaminant elements in suburban soils[J].Applied Geochemistry,2005,20:1051-1059.
[4]韩春兰,刘金宝,付小梅,等.粗面岩质火山碎屑物发育土壤有机质含量的高光谱特征与建模[J].土壤通报,2017,47(1):39-44.
[5]Al-abbas A H,Swain P H,Baumgardner M F.Relating organic matter and clay content to the multispectral radiance of soils[J].Soil Science,1972,114(6):477-485.
[6]周清,周斌,张杨珠,等.成土母质对水稻土高光谱特性及其有机质含量光谱参数模型影响的初步研究[J].土壤学报,2004,41(6):905-911.
[7]刘红玉,毛罕平,朱文静,等.基于高光谱的番茄氮磷钾营养水平快速诊断[J].农业工程学报,2015,31(25):212-220.
[8]卢伟业,陆继东,姚顺春,等.复合肥氮磷钾元素含量的激光诱导击穿光谱同步测量[J].中国激光,2011,38(10):175-180.
[9]Kooistra L,Wehrens R,Leuven R S E W,et al.Possibilities of visible-near-infrared spectroscopy for the assessment of soil contamination in river floodplains[J].Analytica Chimica Acta,2001(446):97-105.
[10]Grzegorz S,Gregory W M,Tomasz I S,et al.Near and mid-infrared diffuse reflectance spectroscopy for measuring soil metal content[J].Journal of Environment Quality,2004(33):2056-2069.
[11]李巨宝,田庆久,吴昀昭.滏阳河两岸农田土壤Fe、Zn、Se元素光谱响应研究[J].遥感信息,2005(3):10-13.
[12]解宪丽,孙波,郝红涛.土壤可见光-近红外反射光谱与重金属含量之间的相关性[J].土壤学报,2007,44(6):982-993.
[13]郭云开,周烽松,丁美青,等.水稻冠层与土壤高光谱反演土壤重金属对比研究[J].遥感信息,2017(2):173-179.
[14]张秋霞,张合兵,张会娟,等.粮食主产区耕地土壤重金属高光谱综合反演模型[J].农业机械学报,2017,48(3):148-155.
[15]董霁红,丁敏,赵银娣,等.矿区复垦土壤重金属含量分布与光谱特征研究---以徐州市柳新矿区为例[J].中国矿业大学学报,2012,41(5):827-832.
[16]邬登巍,吴昀昭,马宏瑞.基于中红外漫反射光谱的土壤重金属元素含量预测研究[J].光谱学与光谱分析,2010,30(6):1498-1502.
[17]刘硕,吴泉源,张龙龙,等.基于野外实测光谱的污灌区土壤重金属污染快速监测[J].安全与环境学报,2015,15(2):297-302.