Polluted soils analysis and characterization is one of the basic step to perform in order to collect all the information to
design and set-up correct soil reclamation strategies. Soil analysis is usually performed through "in-situ" sampling and
laboratory analysis. Such an approach is usually quite expensive and does not allow to reach a direct and detailed
knowledge of large areas for the intrinsic limits (high costs) linked to direct sampling and polluting elements detection.
As a consequence numerical strategies are applied to extrapolate, starting from a discrete set of data, that is those related
to collected samples, information about the contamination level of areas not directly interested by physical sampling.
These models are usually very difficult to handle both for the intrinsic variability characterizing the media (soils) and
for the high level of interactions between polluting agents, soil characteristics (organic matter content, size class
distribution of the inorganic fraction, composition, etc.) and environmental conditions (temperature, humidity, presence
of vegetation, human activities, etc.). Aim of this study, starting from previous researches addressed to evaluate the
potentialities of hyperspectral imaging approach in polluting soil characterization, was to evaluate the results obtainable
in the investigation of an "ad hoc" polluted benthonic clay, usually utilized in rubbish dump, in order to define fast and
reliable control strategies addressed to monitor the status of such a material in terms of insulation.