1. 新疆大学资源与环境科学学院绿洲生态教育部重点实验室
2. 新疆大学生态学博士后流动站
纸质出版:2020
移动端阅览
[1]阿不都艾尼·阿不里,尼加提·卡斯木,师庆东,等.假木贼重金属含量的高光谱估算研究[J].新疆大学学报(自然科学版)(中英文),2020,37(03):309-320.
[1]阿不都艾尼·阿不里,尼加提·卡斯木,师庆东,等.假木贼重金属含量的高光谱估算研究[J].新疆大学学报(自然科学版)(中英文),2020,37(03):309-320. DOI: 10.13568/j.cnki.651094.651316.2019.05.30.0004.
DOI:10.13568/j.cnki.651094.651316.2019.05.30.0004.
植物作为生态环境的主要组成部分
植物受污染状况能够反映区域生态环境污染状况
因此植物重金属污染快速监测
对其周围生态环境预警具有重要意义.本研究利用传统化学分析方法和高光谱技术
采用多元逐步回归分析法(SMLR)和偏最小二乘回归分析方法(PLSR)对假木贼体内的重金属(Zn、Cu、Cr、Hg和As)含量进行估算和预测.结果表明:(1)由相关性分析结果发现
二阶导数处理之后的光谱反射率与重金属含量之间的相关性较敏感
且通过0.01水平上的特征波段数量明显增加;而一阶导数处理后的光谱数据及原始光谱对重金属的敏感程度较弱.(2)SMLR估算模型精度分析发现
Zn、Cu、Cr、Hg和As的估算精度(R2)分别达到0.61、0.57、0.50、0.60和0.42;PLSR估算模型精度分析发现
Zn、Cu、Cr、Hg和As的估算精度(R2)分别达到0.79、0.74、0.75、0.72和0.51.(3)对PLSR和SMLR估算模型精度进行分析可知
PLSR模型估算的决定系数高(R2=0.79)
误差比较小(RMSE=2.03)
更接近于实测值.PLSR估算模型能够较好地估算假木贼体内重金属含量
可为干旱地区植被重金属污染快速监测提供技术支持和理论依据.
Plant is one of the most important components in the eco-environment
and the pollution status of the plant can reflect the status of the regional eco-environment. Therefore
how to quickly monitor the heavy metal contents in the plant has great meaning in the regional sustainable development. In this study we combined the traditional chemical analysis and hyperspectral methods to predict the heavy metal contents(Zn
Cu
Cr
Hg and As) of Anabasis L. using stepwise multiple linear regression(SMLR) and partial least squares regression(PLSR)model. The results showed that(1) the correlation analysis revealed that the correlations between the spectral reflectance and heavy metals contents were more sensitive and higher after the second derivative processing of the original bands and the amounts of the special bands were greatly increased.(2) Estimation results from SMLR model showed that the estimation accuracies of the Zn
Cu
Cr
Hg and As were 0.61
0.57
0.50
0.60 and 0.42 respectively
while the estimation accuracies of the Zn
Cu
Cr
Hg and As using PLSR model were 0.79
0.74
0.75
0.72 and 0.51 respectively. Comparing the prediction accuracy about different elements in A.aphylla
it is shown the prediction of element Zn achieved high accuracy
while the prediction of element As presented low accuracy.(3) Comparison results of the two models revealed that a higher determination coefficient and smaller root mean square error(R2=0.79
RMSE =2.03) were achieved for PLSR
which were closer to the measured values.PLSR model can preferably estimate the heavy metal contents of A. aphylla
and this method can provide techniques and theoretical basis for rapidly monitoring the heavy metal pollution of the plant in arid region.
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