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张家港市农田土壤重金属含量高光谱遥感监测模型构建
引用本文:钱家炜,刘晓青,张静静,周卫红,李建龙.张家港市农田土壤重金属含量高光谱遥感监测模型构建[J].浙江农业学报,2020,32(8):1437.
作者姓名:钱家炜  刘晓青  张静静  周卫红  李建龙
作者单位:1.南京大学 生命科学学院 应用生态研究所,江苏 南京 210093;2.江苏科技大学 苏州理工学院,江苏 张家港 215600
基金项目:国家重点研发计划(2018YFD0800201); 苏州科技项目(SNG201447); 江苏省科技支撑计划(农业)重点项目(BE2016341)
摘    要:以张家港农田土壤作为研究对象,在实验室测定土壤重金属元素As、Cd、Cr、Cu、Zn、Ni、Pb、Hg的含量,并与土壤可见近红外高光谱数据建立土壤重金属含量的定量估测模型,以快速获取研究区农田的土壤重金属含量。为保证模型预测的精度和稳定性,首先,对原始高光谱数据进行平滑处理,并进行一阶导数、倒数一阶导数、倒数的对数一阶导数、平方根一阶导数和连续统去除等形式的光谱变换;然后,提取不同变换光谱的特征波段进行相关性分析;最后,通过逐步回归法建立重金属含量的定量估算模型。结果表明:张家港市农田土壤中Cd、Hg、Cu、Zn存在一定的污染风险。在高光谱的不同变换形式中,一阶导数和连续统去除与重金属含量的相关系数高于其他变换形式。基于8种土壤重金属含量与高光谱数据建立的定量估算模型具有良好的预测精度。Cd、Hg、Cr、As、Cu、Zn、Ni、Pb估算模型的实际值与验证值的拟合度分别为0.874、0.879、0.800、0.646、0.513、0.655、0.603和0.542,可用于预测张家港市的农田土壤重金属含量。

关 键 词:农田土壤污染  重金属含量  高光谱遥感监测  模型精度  
收稿时间:2020-02-17

Constructions of hyperspectral remote sensing monitoring models for heavy metal contents in farmland soil in Zhangjiagang City
QIAN Jiawei,LIU Xiaoqing,ZHANG Jingjing,ZHOU Weihong,LI Jianlong.Constructions of hyperspectral remote sensing monitoring models for heavy metal contents in farmland soil in Zhangjiagang City[J].Acta Agriculturae Zhejiangensis,2020,32(8):1437.
Authors:QIAN Jiawei  LIU Xiaoqing  ZHANG Jingjing  ZHOU Weihong  LI Jianlong
Institution:1. Institute of Applied Ecology, School of Life Sciences, Nanjing University, Nanjing 210093, China;
2. Suzhou Institute of Technology, Jiangsu University of Science and Technology,Zhangjiagang 215600, China
Abstract:In the present study, soil samples were prepared from Zhangjiagang City to establish the quantitative inversion models of the soil heavy metals contents. The contents of the soil heavy metals and the visible and near-infrared spectra of the soil samples were obtained in a darkroom. Firstly, the original hyperspectral data was smoothed and the spectral transformations such as first derivative, reciprocal of first derivative, logarithm of reciprocal of first derivative, square root of first derivative and continuum removal were carried out. Secondly, the characteristic bands of different transform spectra were extracted through correlation analysis. Finally, quantitative estimation models of heavy metals contents were established by stepwise regression. The results showed that Cd, Hg, Cu and Zn in the farmland soil of Zhangjiagang City exhibited certain pollution risk. The correlation coefficient within the first derivative or the continuum removal and heavy metals contents were higher than that of other transformation forms. Eight quantitative estimation models of soil heavy metals contents and hyperspectral data possessed good prediction accuracy. The fitting degrees of the actual and verified values of the estimated models for Cd, Hg, Cr, As, Cu, Zn, Ni and Pb were 0.874, 0.879, 0.800, 0.646, 0.513, 0.655, 0.603 and 0.542, respectively. Therefore, hyperspectral data could be used to predict the contents of soil heavy metals in farmland in Zhangjiagang City.
Keywords:farmland soil pollution  heavy metal contents  hyperspectral remote sensing monitoring  model accuracy  
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