Discriminação de áreas de espesso regolito do leste do Estado do Amazonas usando estatística multivariada, algoritmo hiperespectral e modelagem de dados espaciais

Abstract

ABSTRACT.Areas with deep regolith profiles are widely distributed in the Amazonian region. Research on regolith geology in Brazil has concentrated, mainly, in geochemical and mineralogical aspects and where possible utilizing these in exploration. Although airborne geophysics and spatial data integration methods are being used increasingly for mineral resource assessments, the application in regolith-dominated terrains is new. The objective of this paper is to show the potential of a systematic approach, including the use of regional gamma-ray spectrometry, digital elevation model and image digital processing techniques for the identification of deep regolith areas characterized by potential economic interest in less well explored region of the eastern portion of Amazonas State. The application of multivariate statistics techniques (Principal Components Analysis and K-means) in airborne gamma-ray data allows the individualization of regoliths in comparison to the geologic units of this region. How exploratory guide, the following patterns were observed: low values of K (easily lixivied during the weathering) and K/eU ratio; high values of eTh, eTh/K ration and medium values of eU, besides the higher altitude (plateau). Based on these images, the hyperspectral algorithm named Spectral Angle Mapper (SAM) and the boolean and fuzzy logic spatial modeling techniques were applied to produce regolith potential maps that were compared with previous geological data in 1:250.000 scale. The quantitative relationships between geophysical and altimetric datasets have shown great capability for linking geological and geophysical interpretations, indicating potential areas that can direct new ways for mineral prospecting at the study area.Keywords: airborne gamma-ray spectrometry data, SRTM, Spectral Angle Mapper, spatial data modeling, Principal Components Analysis, K-means.RESUMO.Áreas com espessos regolitos estão amplamente distribuídas na região amazônica. Nasúltimas décadas, as pesquisas sobre geologia de regolitos no Brasil têm se concentrado, principalmente, nos aspectos geoquímicos e mineralógicos e seus possíveis usos para a exploração de recursos minerais. Embora a utilização da aerogeofísica e de métodos de integração de dados tenham se ampliado na avaliação de recursos minerais, a aplicação em terrenos regolíticos aindá e recente. O objetivo deste artigoé mostrar o potencial de uma abordagem sistemática, incluindo o uso de aerogamaespectrometria regional, modelo digital de elevação e processamento digital de imagens, para a identificação deáreas de espesso regolito com potencial interesse econômico em umaárea pouco explorada da porção leste do Estado do Amazonas. A aplicação de técnicas de estatística multivariada (Análise por Principais Componentes e K-médias) em dados aerogamaespectrométricos permitiu a individualização de regolitos frenteàs respostas provenientes de unidades geológicas da região. Como guias para a identificação deáreas de espesso regolito, os seguintes padrões foram observados: baixos valores de...

Boolean and fuzzy methods for identifying lateritic regoliths in the Brazilian Amazon using gamma-ray spectrometric and topographic data

“…The method developed in this work used airborne geophysical (gamma-ray spectrometric), and elevation (SRTM) images, which were analyzed using Boolean and fuzzy mathematical modeling techniques to create predictability maps for the occurrence of lateritic crusts and verify which of the techniques is more efficient. The theoretical base was extracted from An et al (1991); Zimmermann (1985); Bonham-Carter (1994); Moreira et al (2003); McBratney et al (2003); Lagacherie (2005); Carranza (2008); Carrino et al (2011) and da Silva et al (2015). However, some modifications were performed to improve the results.…”

“…The ternary composition (K, eTh, and eU) shows several areas with gamma spectrometric signatures related to high values of eTh, low values of K and low to intermediate values of eU that could be credited to the presence of lateritic crusts and weathering materials according to Dickson and Scott (1997); Dauth (1997); Carrino et al (2011); Minty (2011) and Wilford (2012). However, the airborne geophysical products alone were not sufficient to make a complete discrimination, as some areas mapped as lateritic crusts present inconclusive responses in the three channels (eU, eTh, and K).…”

“…The following step was performed to combine the fuzzified maps and reorganize them using fuzzy operators, such as algebraic product -Fuzzy Algebraic Product Operator -FAPO (minimizes the results), algebraic sum -Fuzzy Algebraic Sum Operator -FASO (maximizes the results), and fuzzy gamma operator -FGO (balances the results). Details regarding these operators are provided in Zimmermann (1985); An et al (1991); Bonham-Carter (1994); Eddy et al (2006); Nykänen et al (2008) and Carrino et al (2011).…”

“…The use of the airborne gamma-ray spectrometry and altimetric data in regolith studies must be investigated, especially when applied with mathematical techniques, raster image algebra, and in the evaluation of multi-source data (e.g., Darnley and Grasty, 1971, Tucker et al, 1984, Duval, 1990, Burrough et al, 1992, Graham and Bonham-Carter, 1993, Wilford et al, 1997, Dickson and Scott, 1997, McKenzie & Ryan 1999, Zhu et al, 2010, Carrino et al, 2011, Wilford, 2012and Dent et al, 2013.…”

Integration of Geochemical and Geophysical Data to Characterize and Map Lateritic Regolith: An Example in the Brazilian Amazon

“…Wilford (2012), for example, developed the weathering intensity index (WII) for Australia using gamma ray spectrometric and altimetric data and obtained excellent results at a regional scale defining areas with different levels of weathering. Other authors confirm that high values of U and Th (from aero geophysical data), often above the Earth's crustal average, together with low values of K, identify lateritic products (such as lateritic duricrust, gossan, and bauxites) and their respective parent rocks (Barbosa et al, 2013;Carrier et al, 2006;Carrino et al, 2011;Dauth, 1997;Dickson & Scott, 1997;Isles & Rankin, 2000;Iza et al, 2016). On the other hand, Minty (2011) states that radiometric ratios tend to remove environmental artifacts related to humidity and vegetation.…”