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Type: Artigo de Periódico
Title: Characterization Of Mineral Substrates Impregnated With Crude Oils Using Proximal Infrared Hyperspectral Imaging
Author: Scafutto
RDM; de Souza
CR; Rivard
Abstract: The early identification of natural oil seepages or accidental leaks onshore is not a well explored theme in the literature. Location and mapping of contaminated areas can indicate the presence of a subsurface reservoir and guide direct exploration operations in the oil industry. Superficial occurrences of hydrocarbons (HCs) can also indicate damage to pipelines. Locating small leaks can guide containment, cleaning and repair operations. Remote sensing tools for such purposes usually focus on the effects that oil in the soil causes on the spectral signatures of vegetation. Studies investigating the spectral characteristics of soil and HC mixtures are not prevalent. This study comprises the conception and analysis of a spectral library of mixtures of several mineral substrates impregnated with various concentrations of light to heavy oils (API varying from 19.4 to 41.9), using data acquired with an automated hyperspectral imaging station and processed with wavelets. The wavelet transform allowed the extraction of key spectral features and the discard of secondary information (e.g. noise and continuum), resulting in hyperspectral imagery products that proved suitable to separate different phases in the soil-HC mixture, as well as to identify the type and concentration of HC in the soil. This comprehensive spectral library and the acquired information regarding spectral characteristics of soil-hydrocarbon mixtures, opens opportunities for the development of new processing methods for the direct mapping of onshore seeps and leaks using current and future orbital hyperspectral (Hyperion; EnMap; HyspIRI) and multispectral (WordView-3) sensors. (C) 2016 Elsevier Inc. All rights reserved.
Subject: Hyperspectral
Spectral Mixture
Citation: Remote Sensing Of Environment. ELSEVIER SCIENCE INC, n. 179, p. 116 - 130.
Rights: fechado
Identifier DOI: 10.1016/j.rse.2016.03.033
Date Issue: 2016
Appears in Collections:Unicamp - Artigos e Outros Documentos

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