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Proceedings Paper

Hyperspectral imaging based techniques applied to polluted clay characterization
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Paper Abstract

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.

Paper Details

Date Published: 23 October 2006
PDF: 8 pages
Proc. SPIE 6381, Optics for Natural Resources, Agriculture, and Foods, 638101 (23 October 2006); doi: 10.1117/12.684660
Show Author Affiliations
Giuseppe Bonifazi, Univ. degli Studi di Roma La Sapienza (Italy)
Silvia Serranti, Univ. degli Studi di Roma La Sapienza (Italy)


Published in SPIE Proceedings Vol. 6381:
Optics for Natural Resources, Agriculture, and Foods
Yud-Ren Chen; George E. Meyer; Shu-I Tu, Editor(s)

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