Produção Nacional
Detecção de exsudações de hidrocarbonetos por geobotânica e sensoriamento remoto multi-temporal: estudo de caso no Remanso do Fogo (MG)
2008; Sociedade Brasileira de Geologia; Volume: 38; Issue: 2 Linguagem: Inglês
10.5327/rbg.v38i2.1404
ISSN2317-4889
AutoresCarlos Roberto de Souza Filho, Vagney Aparecido Augusto, Wilson Jose ́ de Oliveira, Talita Lammoglia,
Tópico(s)Remote-Sensing Image Classification
ResumoThis work focus on the spectral characterization of a set of vegetation comprised in the Sao Francisco Basin, particularly in an area known as Remanso do Fogo (Minas Gerais State), where seepages have already been detected visually and by geochemistry. The main objective was to evaluate the likely correlation between areas rich in hydrocarbons and geobotanical anomalies. The investigation was based on multitemporal and multispectral ASTER images and gasometrical data. The processing included: (i) statistical evaluation of gasometrical data, (ii) spectral characterization of vegetation in tracts inside and outside hydrocarbon geochemical anomalies, and (iii) ASTER imagery spectral classification using n-dimensional spectral angle and multi-criteria partial spectral unmixing methods, which were applied with the ultimate purpose of remote detection of areas with hydrocarbon seepages, mainly guided by vegetation spectra. Spectral analysis of image pixels in areas with known HC anomalies make it possible to distinguish areas affected or not by HCs seeps. Vegetation spectra collected within HC anomalies indicate key signatures in ASTER bands 2 (0.63-0.69 µm), 3 (0.76-0.86 µm), 4 (1.60-1.70 µm) and 6 (2.18 - 2.22 µm), strengthening the spatial association of geochemical and geobotanical anomalies. Furthermore, areas mapped remotely as spectrally anomalous showed evidences of seeps in numerous sites verified in the field, proving the efficiency of the detecting model. The research strategy here introduced in a unique case study reveals its vast potential for detection and characterization of seepages, which are important vectors for of oil and gas resources.
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