Hyperspectral estimation model of soil Pb content and its applicability in different soil types
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ORIGINAL ARTICLE
Hyperspectral estimation model of soil Pb content and its applicability in different soil types Shiqi Tian1,2,3 • Shijie Wang2,3 • Xiaoyong Bai2,3 • Dequan Zhou1 Qian Lu2,3 • Mingming Wang2,3 • Jinfeng Wang2,3
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Received: 24 June 2019 / Revised: 10 October 2019 / Accepted: 11 December 2019 Ó Science Press and Institute of Geochemistry, CAS and Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract In order to obtain Pb content in soil quickly and efficiently, a multivariate linear regression (MLR) and a principal component regression (PCR) Pb content estimation model were established on the basis of hyperspectral techniques, and their applicability in different soil types was evaluated. Results indicated that Pb exhibited strong spatial heterogeneity in the study area, and more than 82% of the samples exceeded the background value. In addition, the pollution range was large. Pb was sensitive in the nearinfrared band, and the correlation of absorbance (AB) was most significant of all the transformed forms. Both models achieved optimal stability and reliability when AB was used as an independent variable. Compared with the PCR model, the stability, fitting accuracy, and predictive power of the MLR model were superior with a coefficient of determination, root mean square error, and mean relative error of 0.724%, 24.92%, and 28.22%, respectively. Both models could be applied to different soil types; however, MLR had better applicability compared with PCR. The PCR model that distinguished different soil types had better reliability than one that did not. Thus, the model & Xiaoyong Bai [email protected] 1
School of Geography and Environmental Sciences, Guizhou Normal University, Guiyang 550081, Guizhou Province, People’s Republic of China
2
State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, 99 Lincheng West Road, Guiyang 550081, Guizhou Province, People’s Republic of China
3
Puding Karst Ecosystem Observation and Research Station, Chinese Academy of Sciences, Puding 562100, Guizhou Province, People’s Republic of China
established via hyperspectral techniques can achieve largearea, rapid, and efficient soil Pb content monitoring, which can provide technical support for the treatment of heavy metal pollution in soil. Keywords Hyperspectral data Heavy metal Pb Estimation
1 Introduction A large amount of domestic and industrial wastes have been discharged into soils. Chemical fertilizers are also used in agriculture. Therefore, the soils accumulate heavy metal Pb, which enters the human body through the food chain and other means and poses a serious threat to human health (Li et al. 2013a; Song et al. 2017). Therefore, the estimation of soil Pb content is crucial. Traditionally, the determination of heavy metal content in soil requires extensive sampling and long-term laboratory measurement analysis. This method has high measurement accuracy but is costly in terms of time and economy and has low efficiency; monitori
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