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.

Mapping leaf metal content over industrial brownfields using airborne hyperspectral imaging and optimized vegetation indices.

Monitoring plant metal uptake is essential for assessing the ecological risks of contaminated sites. While traditional techniques used to achieve this are destructive, Visible Near-Infrared (VNIR) reflectance spectroscopy represents a good alternative to monitor pollution remotely. Based on previous work, this study proposes a methodology for mapping the content of several metals in leaves (Cr, Cu, Ni and Zn) under realistic field conditions and from airborne imaging.

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.

Monitoring oil contamination in vegetated areas with optical remote sensing: A comprehensive review.

The monitoring of soil contamination deriving from oil and gas industry remains difficult in vegetated areas. Over the last decade, optical remote sensing has proved helpful for this purpose. By tracking alterations in vegetation biochemistry through its optical properties, multi- and hyperspectral remote sensing allow detecting and quantifying crude oil and petroleum products leaked following accidental leakages or bad cessation practices.

Estimating persistent oil contamination in tropical region using vegetation indices and random forest regression.

The persistence of soil contamination after cessation of oil activities remains a major environmental issue in tropical regions. The assessment of the contamination is particularly difficult on vegetated sites, but promising advances in reflectance spectroscopy have recently emerged for this purpose. This study aimed to exploit vegetation reflectance for estimating low concentrations of Total Petroleum Hydrocarbons (TPH) in soils.

Application of PROSPECT for estimating total petroleum hydrocarbons in contaminated soils from leaf optical properties.

Recent advances in hyperspectral spectroscopy suggest making use of leaf optical properties for monitoring soil contamination in oil production regions by detecting pigment alterations induced by Total Petroleum Hydrocarbons (TPH). However, this provides no quantitative information about the level of contamination. To achieve this, we propose an approach based on the inversion of the PROSPECT model.

Detection and discrimination of various oil-contaminated soils using vegetation reflectance.

The use of hyperspectral spectroscopy for oil detection recently sparked a growing interest for risk assessment over vegetated areas. In a perspective of image applications, we conducted a greenhouse experiment on a brownfield-established species, Rubus fruticosus L. (bramble), to evaluate the potential of vegetation reflectance to detect and discriminate among various oil-contaminated soils.

Assessing Soil Contamination Due to Oil and Gas Production Using Vegetation Hyperspectral Reflectance.

The remote assessment of soil contamination remains difficult in vegetated areas. Recent advances in hyperspectral spectroscopy suggest making use of plant reflectance to monitor oil and gas leakage from industrial facilities. However, knowledge about plant response to oil contamination is still limited, so only very few imaging applications are possible at this stage.

Estimation of soil moisture content from the spectral reflectance of bare soils in the 0.4-2.5 µm domain.

This work aims to compare the performance of new methods to estimate the Soil Moisture Content (SMC) of bare soils from their spectral signatures in the reflective domain (0.4-2.5 µm) in comparison with widely used spectral indices like Normalized Soil Moisture Index (NSMI) and Water Index SOIL (WISOIL).

Aggregation process of optical properties and temperature over heterogeneous surfaces in infrared domain.

We propose a modeling of the aggregation processes of optical properties and temperature over the heterogeneous landscape in the infrared domain (3-14 microm). The main objectives of the modeling are to understand how these parameters aggregate and to study their links at different spatial scales. As the landscape is described at each scale by its radiative parameters, general equations linking the radiative parameters at a given high spatial scale to those at a rough scale are proposed.

Thermal infrared radiance simulation with aggregation modeling (TITAN): an infrared radiative transfer model for heterogeneous three-dimensional surface--application over urban areas.

The thermal infrared radiance simulation with aggregation modeling (TITAN) model, presented here, is an innovative transfer radiative code in the infrared domain (3-14 microm). It takes into account the three-dimensional (3D) structure of the landscape and simulates all the radiative components introduced by this 3D structure, which are due to the reflection and emission of walls and sloping roofs. Examples are given to illustrate the new opportunities offered by TITAN over urban areas.