Abstract
In this paper, an analysis of the possibility of passive determination of the degree of environmental pollution based on data from the leaf blade of mulberry is made. With existing solutions in this area, the mulberry has been found to be under-researched. A disadvantage of the available solutions is that spectral indices are used, which is not a sufficient criterion for passively determining the degree of air pollution based on the surface characteristics of the mulberry leaves. Methods have been used to reduce the amount of data by latent variables and principal components. It has been found that a kernel variant of the principal components, combined with linear discriminant analysis, is an appropriate method for distinguishing the degree of air pollution from mulberry leaf data. The results obtained can be used to refine the approaches used to passively determine the degree of air pollution in the habitat area of the plant. Methods and software tools could be used to develop mobile applications and new approaches to remote sensing, in express determination of the degree of environmental pollution, according to data from the mulberry leaves.
Highlights
Environmental quality monitoring in urban areas is a method that offers the opportunity to avoid adverse effects on human health
Effective application of mulberry leaves data to determine the degree of pollution of the habitat area is entirely aimed at using methods that would be sufficiently effective with respect to rapid and simple classification, and at the same time giving satisfactory accuracy according to generally accepted standards to that end
It is seen that the coefficient of variation (CV) is below 30% (CV = SD/mean)
Summary
Environmental quality monitoring in urban areas is a method that offers the opportunity to avoid adverse effects on human health. Passive and active biomonitoring of air quality has both advantages and disadvantages. Passive biomonitoring has the advantage of using tree species already present in the ecosystem, making this approach affordable and effective over time [1]. Detailed studies have been conducted on passive bio-monitoring of air quality based on leaf data from Tilia (Tilia sp.) [2], hornbeam (Carpinus betulus) [3], and white willow (Salix mucronata) [4]. The requirements for the application of different types of plants to passively determine the quality of the air in cities include identifying features of pollution that alter plant characteristics, needing to develop new methods, or refining existing ones [5,6,7,8,9].
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