Quantitative inversion of soil heavy metal Cd based on ensemble empirical mode decomposition

doi:10.13474/j.cnki.11-2246.2022.0008

Abstract

Abstract: In view of the lack of accuracy of the model for hyperspectral quantitative inversion of soil heavy metal content, this paper introduces the time-frequency analysis method seting ensemble empirical mode decomposition(EEMD) from the perspective of time-frequency space, and explores the application of EEMD method in hyperspectral quantitative inversion of soil heavy metal content.The EEMD method is used to decompose soil hyperspectral to obtain intrinsic mode function (IMF) components with different frequencies. By analyzing the correlation between IMF components and heavy metal content, characteristic spectra are extracted to construct an EEMD-SVM quantitative inversion model.The results show that the EEMD method can effectively extract the weak information in the soil spectrum.The determination coefficient R² of the EEMD-SVM model is 0.920 3, which is significantly higher than that of the SVM model based on the first-order differential processing of spectral data (0.786 6).It is explained that EEMD can be used as a new method of spectral treatment in the field of quantitative introspection of soil heavy metals.

Key words: EEMD, high optical spectrum, soil heavy metal, support vector machine

CLC Number:

P208

GUO Yunkai, CAO Xiao, XIE Xiaofeng, ZHANG Siai, XIE Qiong. Quantitative inversion of soil heavy metal Cd based on ensemble empirical mode decomposition[J]. Bulletin of Surveying and Mapping, 2022, 0(1): 44-49.

References

[1] 张静静,周卫红,邹萌萌,等.高光谱遥感监测大面积土壤重金属污染的研究现状、原理及展望[J].江苏农业科学,2018,46(12):9-13.
[2] 胡冠九,陈素兰,王光.中国土壤环境监测方法现状、问题及建议[J].中国环境监测,2018,34(2):10-19.
[3] MALLEY D F, WILLIAMS P C.Using of near infrared reflectance spectroscopy in prediction of heavy metals infreshwater sediment by their association with organicmatter[J].Environmental Science & Technology,1997,31(12):3461-3467.
[4] KEMPER T,SOMMER S.Estimate of heavy metal conta-mination in soils after a mining accident using reflectance spectroscopy[J].Environmental Science & Technology,2002,36(12):2742-2747.
[5] 郭云开,刘宁,刘磊,等.土壤Cu含量高光谱反演的BP神经网络模型[J].测绘科学,2018,43(1):135-139.
[6] 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.
[7] 蒋明,郭云开,钱佳,等.不同采样间隔下分数阶微分对土壤重金属高光谱数据的影响[J].测绘通报,2018(10):37-40.
[8] 雷宇斌,刘宁,郭云开,等.高光谱组合变换下土壤Cd含量GWR模型反演研究[J].测绘工程,2018,27(11):71-76.
[9] 袁中强,曹春香,鲍达明,等. 若尔盖湿地土壤重金属元素含量的遥感反演[J]. 湿地科学, 2016, 14(1):113-116.
[10] 龚绍琦,王鑫,沈润平,等. 滨海盐土重金属含量高光谱遥感研究[J]. 遥感技术与应用, 2010, 25(2):169-177.
[11] 褚小立,袁洪福,陆婉珍.近红外分析中光谱预处理及波长选择方法进展与应用[J].化学进展,2004(4):528-542.
[12] 孟繁林. 集合经验模态分解的理论及应用研究[D].镇江:江苏科技大学,2013.
[13] 汪海燕,黎建辉,杨风雷.支持向量机理论及算法研究综述[J].计算机应用研究,2014,31(5):1281-1286.
[14] 李丹娜,郭云开,朱善宽,等.利用PRO4SAIL与支持向量机回归的组合模型反演植被等效水厚度[J].测绘通报,2017(8):50-55.
[15] 郭云开,刘磊,刘宁,等.基于支持向量机回归的水稻地重金属Fe含量估算[J].北京测绘,2017(6):10-13.
[16] 雷宇斌,刘宁,郭云开,等.高光谱组合变换下土壤Cd含量GWR模型反演研究[J].测绘工程,2018,27(11):71-76.
[17] KEMPER T, SOMMER S. Estimate of heavy metal conta-mination in soil after a mining accident using reflectance spectroscopy[J].Enviromental Science & Technology 2002,36(12):2742-2747.
[18] WU Z H, HUANG N. Ensemble empirical mode decomposi-tion:a noise assisted data analysis method[J].Advances in Adaptive Data Analysis,2009,1(1):1-4.