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

Terrestrial oil spill mapping using satellite earth observation and machine learning: A case study in South Sudan

Terrestrial oil spills are a major threat to environmental and human well-being. Rapid, accurate, and remote spatial assessment of oil contamination is critical to implementing countermeasures that prevent potentially lasting ecological damage and irreversible harm to local communities. Satellite remote sensing has been used to support such assessments in inaccessible regions, although mapping small terrestrial oil spills is challenging - partly due to the pixel size of remote sensing systems, but also due to the distinguishability of small oil spill areas from other land cover types. We assessed the usability of freely available Sentinel satellite images to map terrestrial oil spills with machine learning algorithms. Using two test sites in South Sudan, we demonstrated that information from the Sentinel-1 and -2 instruments can be used to map oil spills with more than 90 % classification accuracy. Classification accuracy was significantly increased (>95 %) with the addition of multi-temporal information and spatial predictor variables that quantify proximity to oil production infrastructure such as pipelines and oil pads. The mapping of terrestrial oil spills with freely available Sentinel satellite images may thus represent an accurate and efficient means for the regular monitoring of oil-impacted areas.

Monitoring natural and anthropogenic plant stressors by hyperspectral remote sensing: Recommendations and guidelines based on a meta-review

This review outlines the advances achieved in monitoring natural and anthropogenic plant stressors by hyperspectral remote sensing over the last 50 years. A broad diversity of methods based on field and imaging spectroscopy were developed in that field for precision farming and environmental monitoring purposes. From the 466 articles reviewed, we identified the main factors to consider to achieve accurate monitoring of plant stress, namely: The plant species and the stressor to monitor, the goal (detection or quantification), and scale (field or broad-scale) of monitoring, and the need for controlled experiments. Based on these factors, we then provide recommendations and guidelines for the development of reliable methods to monitor 11 major biotic and abiotic plant stressors. For each stressor, the effects on plant health and reflectance are described and the most suited spectral regions, scale, spatial resolution, and processing approaches to achieve accurate monitoring are presented. As a perspective, we discuss two major components that should be implemented in future methods to improve stress monitoring: The discrimination of plant stressors with similar effects on plants and the transferability of the methods across scales.

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. For this purpose, the reflectance of Rubus fruticosus L., a pioneer species of industrial brownfields, was linked to leaf metal contents using optimized normalized vegetation indices. High correlations were found between the vegetation indices exploiting pigment-related wavelengths and leaf metal contents (r ≤ - 0.76 for Cr, Cu and Ni, and r ≥ 0.87 for Zn). This allowed predicting the metal contents with good accuracy in the field and on the image, especially Cu and Zn (r ≥ 0.84 and RPD ≥ 2.06). The same indices were applied over the entire study site to map the metal contents at very high spatial resolution. This study demonstrates the potential of remote sensing for assessing metal uptake by plants, opening perspectives of application in risk assessment and phytoextraction monitoring in the context of trace metal pollution.

Hydrocarbon-induced hormesis: 101 years of evidence at the margin?

Hydrocarbons are used worldwide for an array of purposes ranging from transportation to making plastics and synthetic fibers. Hydrocarbons pollution can occur from local to global scales, becoming a focus of regulatory authorities since a long time ago. While studies show numerous adverse effects on biota, such effects usually occur at very high doses. This paper collates significant evidence showing that hydrocarbons induce hormesis in biota, with dual effects of low versus high doses. Hydrocarbon-induced hormetic responses should be considered in relevant dose-response studies as well as in risk assessment. Dismissing hormesis could lead to incorrect predictions of hydrocarbons effects, which can occur at doses up to 100 times smaller than the traditional toxicological threshold, and would raise serious concerns regarding human and ecological health safety.

Chlorophyll hormesis: Are chlorophylls major components of stress biology in higher plants?

High oxidative stress inhibits the synthesis and accumulation of chlorophylls, the pigments that absorb and use light. We collated evidence from a diverse array of studies demonstrating that chlorophyll concentration increases in response to low-level stress and decreases in response to high-level stress. These observations were from 33 species, >20 stress-inducing agents, 43 experimental setups and 177 dose responses, suggesting generality. Data meta-analysis indicated that the maximum stimulatory response did not differ significantly among species and agents. The stimulatory response maximized within a defined time window (median = 150-160% of the control response), after which it decreased but remained elevated (median = 120-130% of control response). The common stimulation of chlorophylls by low-level stress indicates that chlorophylls are major components of stress biology, with their increased concentration at low-level stress suggestive of their requirement for normal functioning and health. Increased chlorophyll concentration in response to low-level stress may equip systems with an enhanced capacity for defense against high-level (health-threatening) challenges within defined time windows, such as pollution or herbivores. These developments have wide-ranging implications in ecophysiology, biotic interactions and evolution.

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. Recent advances in this field have led to the development of various methods that can be applied either in the field using portable spectroradiometers or at large scale on airborne and satellite images. Experiments carried out under controlled conditions have largely contributed to identifying the most important factors influencing the detection of oil (plant species, mixture composition, etc.). In a perspective of operational use, an important effort is still required to make optical remote sensing a reliable tool for oil and gas companies. The current methods used on imagery should extend their scope to a wide range of contexts and their application to upcoming satellite-embedded hyperspectral sensors should be considered in future studies.