Spectrally-based quantification of plant heavy metal-induced stress

Recent developments in environmental studies are greatly related to worldwide ecological problems associated with anthropogenic impacts on the biosphere and first of all on vegetation. Modern remote sensing technologies are involved in numerous ecology-related investigations dealing with problems of global importance, such as ecosystems preservation and biodiversity conservation. Agricultural lands are subjected to enormous pressure and their monitoring and assessment have become an important ecological issue. In agriculture, remote sensing is widely used for assessing plant growth, health condition, and detection of stress situations. Heavy metals constitute a group of environmentally hazardous substances whose deposition in soils and uptake by species affect soil fertility, plant development and productivity. This paper is devoted to the study of the impact of heavy metal contamination on the performance of agricultural species. The ability of different spectral indicators to detect heavy metal-induced stress in plants is examined and illustrated. Empirical relationships have been established between the pollutant concentration and plant growth variables and spectral response. This allows not only detection but quantification of the stress impact on plant performance.