Impact of potentially toxic elements on pines in a former ore processing mine: Exploitation of hyperspectral response from needle and canopy scales.

Anthropic potentially toxic element (PTE) releases can lead to persistent pollution in soil. Monitoring PTEs by their detection and quantification on large scale is of great interest. The vegetation exposed to PTEs can exhibit a reduction of physiological activities, structural damage … Such vegetation trait changes impact the spectral signature in the reflective domain 0.4-2.5 µm. The objective of this study is to characterize the impact of PTEs on the spectral signature of two pine species (Aleppo and Stone pines) in the reflective domain and ensure their assessment. The study focuses on nine PTEs: As, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Zn. The spectra are measured by an in-field spectrometer and an aerial hyperspectral instrument on a former ore processing site. They are completed by measurements related to vegetation traits at needle and tree scales (photosynthetic pigments, dry matter, morphometry …) to define the most sensitive vegetation parameter to each PTE in soil. A result of this study is that chlorophylls and carotenoids are the most correlated to PTE contents. Context-specific spectral indices are specified and used to assess metal contents in soil by regression. These new vegetation indices are compared at needle and canopy scales to literature indices. Most of the PTE contents are predicted at both scales with Pearson correlation scores between 0.6 and 0.9, depending on species and scale.

Unsupervised Monitoring Vegetation after the Closure of an Ore Processing Site with Multi-Temporal Optical Remote Sensing.

Ore processing is a source of soil heavy metal pollution. Vegetation traits (structural characteristics such as spatial cover and repartition; biochemical parameters-pigment and water contents, growth rate, phenological cycle…) and plant species identity are indirect and powerful indicators of residual contamination detection in soil. Multi-temporal multispectral satellite imagery, such as the Sentinel-2 time series, is an operational environment monitoring system widely used to access vegetation traits and ensure vegetation surveillance across large areas. For this purpose, methodology based on a multi-temporal fusion method at the feature level is applied to vegetation monitoring for several years from the closure and revegetation of an ore processing site. Features are defined by 26 spectral indices from the literature and seasonal and annual change detection maps are inferred. Three indices-CIred-edge (CIREDEDGE), IRECI (Inverted Red-Edge Chlorophyll Index) and PSRI (Plant Senescence Reflectance Index)-are particularly suitable for detecting changes spatially and temporally across the study area. The analysis is conducted separately for phyto-stabilized vegetation zones and natural vegetation zones. Global and specific changes are emphasized and explained by information provided by the site operator or meteorological conditions.