Abstract

Technological advances in hyperspectral remote sensing have been widely applied in
heavy metal soil contamination studies, as they are able to provide assessments in a rapid and
cost-effective way. The present work investigates the potential role of combining field and laboratory
spectroradiometry with geochemical data of lead (Pb), zinc (Zn), copper (Cu) and cadmium (Cd) in
quantifying and modelling heavy metal soil contamination (HMSC) for a floodplain site located in
Wales, United Kingdom. The study objectives were to: (i) collect field- and lab-based spectra from
contaminated soils by using ASD FieldSpec® 3, where the spectrum varies between 350 and 2500 nm;
(ii) build field- and lab-based spectral libraries; (iii) conduct geochemical analyses of Pb, Zn, Cu
and Cd using atomic absorption spectrometer; (iv) identify the specific spectral regions associated
to the modelling of HMSC; and (v) develop and validate heavy metal prediction models (HMPM)
for the aforementioned contaminants, by considering their spectral features and concentrations in
the soil. Herein, the field- and lab-based spectral features derived from 85 soil samples were used
successfully to develop two spectral libraries, which along with the concentrations of Pb, Zn, Cu
and Cd were combined to build eight HMPMs using stepwise multiple linear regression. The results
showed, for the first time, the feasibility to predict HMSC in a highly contaminated floodplain
site by combining soil geochemistry analyses and field spectroradiometry. The generated models
help for mapping heavy metal concentrations over a huge area by using space-borne hyperspectral
sensors. The results further demonstrated the feasibility of combining geochemistry analyses with
filed spectroradiometric data to generate models that can predict heavy metal concentrations.