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Estimation of Heavy-Metal Contamination in Soil Using Remote Sensing Spectroscopy and a Statistical Approach
Liu, Kai1; Zhao, Dong2; Fang, Jun-yong2; Zhang, Xia2; Zhang, Qing-yun3; Li, Xue-ke4,5
2017-10-01
Source PublicationJOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING
ISSN0255-660X
Volume45Issue:5Pages:805-813
Corresponding AuthorZhao, Dong(zhaodong@radi.ac.cn)
AbstractHeavy-metal-contaminated soil is a critical environmental issue in suburban regions. This paper focuses on utilizing field spectroscopy to predict the heavy metal contents in soil for two suburban areas in the Jiangning District (JN) and the Baguazhou District (BGZ) in China. The relationship between the surface soil heavy metal contents and spectral features was investigated through statistical modeling. Spectral features of several spectral techniques, including reflectance spectra (RF), the logarithm of reciprocal spectra (LG) and continuum-removal spectra (CR), were employed to establish and calibrate models regarding to Cd, Hg and Pb contents. The optimal bands for each spectral feature were first selected based on the spectra of soil samples with artificially added heavy metals using stepwise multiple linear regressions. With the chosen bands, the average predictive accuracies of the cross-validation, using the coefficient of determination R-2, for estimating the heavy metal contents in the two field regions were 0.816, 0.796 and 0.652 for Cd; 0.787, 0.888 and 0.832 for Pb; and 0.906 and 0.867 for Hg based on partial least squares regression. Results show that better prediction accuracies were obtained for Cd and Hg, while the poorest prediction was obtained for Pb. Moreover, the performances of the LG and CR models were better than that of the RF model for Pb and Hg, indicating that LG and CR can provide alternative features in determining heavy metal contents. Overall, it's concluded that Cd, Hg and Pb contents can be assessed using remote-sensing spectroscopy with reasonable accuracy, especially when combined with library and field-collected spectra.
KeywordHeavy-metal contamination Remote sensing spectroscopy Statistical approach
DOI10.1007/s12524-016-0648-4
WOS KeywordREFLECTANCE SPECTROSCOPY ; COMBINED GEOCHEMISTRY ; FIELD SPECTROSCOPY ; MINING AREA ; REMEDIATION ; ELEMENTS ; REMOVAL ; CHINA
Indexed BySCI
Language英语
Funding ProjectNatural Science Foundation of China[41001214]
Funding OrganizationNatural Science Foundation of China
WOS Research AreaEnvironmental Sciences & Ecology ; Remote Sensing
WOS SubjectEnvironmental Sciences ; Remote Sensing
WOS IDWOS:000413689600008
PublisherSPRINGER
Citation statistics
Cited Times:6[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/61211
Collection中国科学院地理科学与资源研究所
Corresponding AuthorZhao, Dong
Affiliation1.Chinese Acad Sci, Inst Geog Sci & Nat Resources, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
2.Chinese Acad Sci, Inst Remote Sensing & Digital Earth, 3 Datun Rd, Beijing 100101, Peoples R China
3.Shandong Univ Sci & Technol, Geomat Coll, Qingdao 266590, Peoples R China
4.Univ Connecticut, Dept Geog, Mansfield, CT 06269 USA
5.Univ Connecticut, Ctr Environm Sci & Engn, Mansfield, CT 06269 USA
Recommended Citation
GB/T 7714
Liu, Kai,Zhao, Dong,Fang, Jun-yong,et al. Estimation of Heavy-Metal Contamination in Soil Using Remote Sensing Spectroscopy and a Statistical Approach[J]. JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING,2017,45(5):805-813.
APA Liu, Kai,Zhao, Dong,Fang, Jun-yong,Zhang, Xia,Zhang, Qing-yun,&Li, Xue-ke.(2017).Estimation of Heavy-Metal Contamination in Soil Using Remote Sensing Spectroscopy and a Statistical Approach.JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING,45(5),805-813.
MLA Liu, Kai,et al."Estimation of Heavy-Metal Contamination in Soil Using Remote Sensing Spectroscopy and a Statistical Approach".JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 45.5(2017):805-813.
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