Early Detection of Vegetation Physiological Stress from Multispectral Data

Ecological issues relevant to anthropogenic impacts on the environment and first of all on the biosphere, are of global importance. They have drawn the attention of various scientists imposing the development of efficient means for assessing the affects of anthropogenic factors specifically on vegetation land covers. Heavy metal pollution is one of the most severe problems concerning natural vegetation resources as well as agricultural crops. Among other methods used for plant phytodiagnostics, an increasing role becomes to play the analysis of land covers radiation behavior. Visible and near infrared measurements have proved abilities in vegetation monitoring for the assessment of plant biophysical parameter. These parameters are associated with plant development and are closely related to vegetation physiological state. In this study multispectral data of peas (Pisum sativum) plants have been used to demonstrate the detection of plant physiological stress caused by heavy metal pollution. The effects of CdCl2 applied in different concentration are associated with plant biomass growth, chlorophyll and carotenoid variations.