A Comparison of Different Remotely Sensed Data for Classifying Bedrock Types in Canada’s Arctic: Application of the Robust Classification Method and Random Forests

The Geological Survey of Canada, under the Remote Predictive Mapping project of the Geo-mapping for Energy and Minerals program, Natural Resources Canada, has the mandate to produce up-to-date geoscience maps of Canada’s territory north of latitude 60°. Over the past three decades, the increased availability of space-borne sensors imaging the Earth’s surface using increasingly higher spatial and spectral resolutions has allowed geologic remote sensing to evolve from being primarily a qualitative discipline to a quantitative discipline based on the computer analysis of digital images.    Classification of remotely sensed data is a well-known and common image processing application that has been used since the early 1970s, concomitant with the launch of the first Landsat (ERTS) earth observational satellite. In this study, supervised classification is employed using a new algorithm known as the Robust Classification Method (RCM), as well as a Random Forest (RF) classifier, to a variety of remotely sensed data including Landsat-7, Landsat-8, Spot-5, Aster and airborne magnetic imagery, producing predictions (classifications) of bedrock lithology and Quaternary cover in central Victoria Island, Northwest Territories. The different data types are compared and contrasted to evaluate how well they classify various lithotypes and surficial materials; these evaluations are validated by confusion analysis (confusion matrices) as well as by comparing the generalized classifications with the newly produced geology map of the study area. In addition, three new Multiple Classification System (MCS) methods are proposed that leverage the best characteristics of all remotely sensed data used for classification.     Both RCM (using the maximum likelihood classification algorithm, or MLC) and RF provide good classification results; however, RF provides the highest classification accuracy because it uses all 43 of the raw and derived bands from all remotely sensed data. The MCS classifications, based on the generalized training dataset, show the best agreement with the new geology map for the study area.SOMMAIREDans le cadre de son projet de Télécartographie prédictive du Programme de géocartographie de l’énergie et des minéraux de Ressources naturelles Canada, la Commission géologique du Canada a le mandat de produire des cartes géoscientifiques à jour du territoire du Canada au nord de la latitude 60°. Au cours des trois dernières décennies, le nombre croissant des détecteurs aérospatiaux aux résolutions spatiales et spectrales de plus en plus élevées a fait passer la télédétection géologique d’une discipline principalement qualitative à une discipline quantitative basée sur l'analyse informatique d’images numériques.     La classification des données de télédétection est une application commune et bien connue de traitement d'image qui est utilisée depuis le début des années 1970, parallèlement au lancement de Landsat (ERST) le premier satellite d'observation de la Terre. Dans le cas présent, nous avons employé une méthode de classification dirigée en ayant recours à un nouvel algorithme appelé Méthode de classification robuste (MRC), ainsi qu’au classificateur Random Forest (RF), appliqués à une variété de données de télédétection dont celles de Landsat-7, Landsat-8, Spot-5, Aster et d’imagerie magnétique aéroportée, pour produire des classifications prédictives de la lithologie du substratum rocheux et de la couverture Quaternaire du centre de l'île Victoria, dans les Territoires du Nord-Ouest. Les différents types de données sont comparés et contrastés pour évaluer dans quelle mesure ils classent les divers lithotypes et matériaux de surface; ces évaluations sont validés par analyse de matrices de confusion et par comparaison des classifications généralisées des nouvelles cartes géologiques de la zone d'étude. En outre, trois nouvelles  méthodes par système de classification multiple (MCS) sont proposées qui permettent d’exploiter les meilleures caractéristiques de toutes les données de télédétection utilisées pour la classification.     Tant la méthode MRC (utilisant l'algorithme de classification de vraisemblance maximale ou MLC que la méthode RF donne de bons résultats de classification; toutefois c’est la méthode RF qui offre la précision de classification la plus élevée car elle utilise toutes les 43 les bandes de données brutes et dérivées de toutes les données de télédétection. Les classifications MCS, basées sur le jeu de données généralisées d’apprentissage, montrent le meilleur accord avec la nouvelle carte géologique de la zone d'étude

Caracterização e estudo comparativo de exsudações de hidrocarbonetos e plays petrolíferos em bacias terrestres das regiões central do Irã e sudeste do Brasil usando sensoriamento remoto espectral

Orientador: Carlos Roberto de Souza FilhoTese (doutorado) - Universidade Estadual de Campinas, Instituto de GeociênciasResumo: O objetivo desta pesquisa foi explorar as assinaturas de exsudações de hidrocarbonetos na superfície usando a tecnologia de detecção remota espectral. Isso foi alcançado primeiro, realizando uma revisão abrangente das capacidades e potenciais técnicas de detecção direta e indireta. Em seguida, a técnica foi aplicada para investigar dois locais de teste localizados no Irã e no Brasil, conhecidos por hospedar sistemas ativos de micro-exsudações e afloramentos betuminosos, respectivamente. A primeira área de estudo está localizada perto da cidade de Qom (Irã), e está inserida no campo petrolífero Alborz, enterrado sob sedimentos datados do Oligoceno da Formação Upper Red. O segundo local está localizado perto da cidade de Anhembi (SP), na margem oriental da bacia do Paraná, no Brasil, e inclui acumulações de betume em arenitos triássicos da Formação Pirambóia. O trabalho na área de Qom integrou evidências de (i) estudos petrográficos e geoquímicos em laboratório, (ii) investigações de afloramentos em campo, e (iii) mapeamento de anomalia em larga escala através de conjuntos de dados multi-espectrais ASTER e Sentinel-2. O resultado deste estudo se trata de novos indicadores mineralógicos e geoquímicos para a exploração de micro-exsudações e um modelo de micro-exsudações atualizado. Durante este trabalho, conseguimos desenvolver novas metodologias para análise de dados espectroscópicos. Através da utilização de dados simulados, indicamos que o instrumento de satélite WorldView-3 tem potencial para detecção direta de hidrocarbonetos. Na sequência do estudo, dados reais sobre afloramentos de arenitos e óleo na área de Anhembi foram investigados. A área foi fotografada novamente no chão e usando o sistema de imagem hiperespectral AisaFENIX. Seguiu-se estudos e amostragem no campo,incluindo espectroscopia de alcance fechado das amostras no laboratório usando instrumentos de imagem (ou seja, sisuCHEMA) e não-imagem (ou seja, FieldSpec-4). O estudo demonstrou que uma abordagem espectroscópica multi-escala poderia fornecer uma imagem completa das variações no conteúdo e composição do betume e minerais de alteração que acompanham. A assinatura de hidrocarbonetos, especialmente a centrada em 2300 nm, mostrou-se consistente e comparável entre as escalas e capaz de estimar o teor de betume de areias de petróleo em todas as escalas de imagemAbstract: The objective of this research was to explore for the signatures of seeping hydrocarbons on the surface using spectral remote sensing technology. It was achieved firstly by conducting a comprehensive review of the capacities and potentials of the technique for direct and indirect seepage detection. Next, the technique was applied to investigate two distinctive test sites located in Iran and Brazil known to retain active microseepage systems and bituminous outcrops, respectively. The first study area is located near the city of Qom in Iran, and consists of Alborz oilfield buried under Oligocene sediments of the Upper-Red Formation. The second site is located near the town of Anhembi on the eastern edge of the Paraná Basin in Brazil and includes bitumen accumulations in the Triassic sandstones of the Pirambóia Formation. Our work in Qom area integrated evidence from (i) petrographic, spectroscopic, and geochemical studies in the laboratory, (ii) outcrop investigations in the field, and (iii) broad-scale anomaly mapping via orbital remote sensing data. The outcomes of this study was novel mineralogical and geochemical indicators for microseepage characterization and a classification scheme for the microseepage-induced alterations. Our study indicated that active microseepage systems occur in large parts of the lithofacies in Qom area, implying that the extent of the petroleum reservoir is much larger than previously thought. During this work, we also developed new methodologies for spectroscopic data analysis and processing. On the other side, by using simulated data, we indicated that WorldView-3 satellite instrument has the potential for direct hydrocarbon detection. Following this demonstration, real datasets were acquired over oil-sand outcrops of the Anhembi area. The area was further imaged on the ground and from the air by using an AisaFENIX hyperspectral imaging system. This was followed by outcrop studies and sampling in the field and close-range spectroscopy in the laboratory using both imaging (i.e. sisuCHEMA) and nonimaging instruments. The study demonstrated that a multi-scale spectroscopic approach could provide a complete picture of the variations in the content and composition of bitumen and associated alteration mineralogy. The oil signature, especially the one centered at 2300 nm, was shown to be consistent and comparable among scales, and capable of estimating the bitumen content of oil-sands at all imaging scalesDoutoradoGeologia e Recursos NaturaisDoutor em Geociências2015/06663-7FAPES