Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis

Ningyu Zhang; Fuyun Xu; Shidong Zhuang; Changwei He

doi:10.1117/12.2246698

25 October 2016 Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis

Ningyu Zhang, Fuyun Xu, Shidong Zhuang, Changwei He

Proceedings Volume 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology; 1015616 (2016) https://doi.org/10.1117/12.2246698
Event: International Symposium on Optoelectronic Technology and Application 2016, 2016, Beijing, China

Abstract

Heavy metal pollution in soils is one of the most critical problems in the global ecology and environment safety nowadays. Hyperspectral remote sensing and its application is capable of high speed, low cost, less risk and less damage, and provides a good method for detecting heavy metals in soil. This paper proposed a new idea of applying regression analysis of stepwise multiple regression between the spectral data and monitoring the amount of heavy metal Cr by sample points in soil for environmental protection. In the measurement, a FieldSpec HandHeld spectroradiometer is used to collect reflectance spectra of sample points over the wavelength range of 325-1075 nm. Then the spectral data measured by the spectroradiometer is preprocessed to reduced the influence of the external factors, and the preprocessed methods include first-order differential equation, second-order differential equation and continuum removal method. The algorithms of stepwise multiple regression are established accordingly, and the accuracy of each equation is tested. The results showed that the accuracy of first-order differential equation works best, which makes it feasible to predict the content of heavy metal Cr by using stepwise multiple regression.

Citation Download Citation

Ningyu Zhang, Fuyun Xu, Shidong Zhuang, and Changwei He "Monitoring heavy metal Cr in soil based on hyperspectral data using regression analysis", Proc. SPIE 10156, Hyperspectral Remote Sensing Applications and Environmental Monitoring and Safety Testing Technology, 1015616 (25 October 2016); https://doi.org/10.1117/12.2246698

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