Mapping of heavy metal pollution in stream sediments using combined geochemistry, field spectroscopy, and hyperspectral remote sensing: A case study of the Rodalquilar mining area, SE Spain

The aim of this study is to derive parameters from spectral variations associated with heavy metals in soil and to explore the possibility of extending the use of these parameters to hyperspectral images and to map the distribution of areas affected by heavy metals on HyMAP data. Variations in the spectral absorption features of lattice OH and oxygen on the mineral surface due to the combination of different heavy metals were linked to actual concentrations of heavy metals. The ratio of 610 to 500 nm (R610,500 nm) in the visible and near-infrared (VNIR) range, absorption area at 2200 nm (Area2200 nm), and asymmetry of the absorption feature at 2200 nm (Asym2200 nm) showed significant correlations with concentrations of Pb, Zn, and As, respectively. The resulting spectral gradient maps showed similar spatial patterns to geochemical gradient maps. The ground-derived spectral parameters showed a reliable quantitative relationship with heavy metal levels based on multiple linear regression. To examine the feasibility to applying these parameters to a HyMAP image, image-derived spectral parameters were compared with ground-derived parameters in terms of R2, one-way ANOVA, and spatial patterns in the gradient map. The R1344,778 nm and Area2200 nm parameters showed a weak relationship between the two datasets (R2 > 0.5), and populations of spectral parameter values, Depth500 nm, R1344,778 nm, and Area2200 nm derived from the image pixels were comparable with those of ground-derived spectral parameters along a section of the stream channel. The pixels classified in the rule image of Depth500 nm, R1344,778 nm, and Area2200 nm derived from a HyMAP image showed similar spatial patterns to the gradient maps of ground-derived spectral parameters. The results indicate the potential applicability of the parameters derived from spectral absorption features in screening and mapping the distribution of heavy metals. Correcting for differences in spectral and spatial resolution between ground and image spectra should be considered for quantitative mapping and the retrieval of heavy metal concentrations from HyMAP images.