Dissertations / Theses on the topic 'Mineral Mapping'

Evaporate minerals were very important raw materials in very different and broad industries for years. Since gypsum became important raw material especially in construction industry as plaster, demand to these minerals rises each following year. The aim of this thesis is to map out these industrial raw materials by using remote sensing techniques. Ankara Bala region has very rich Gypsum sites and this region is showed as one of the best gypsum potential sites of Turkey according to the studies of MTA so that this area is selected for the usage of remotely sensed data. For the remote sensing analyses ASTER images which have high spatial and spectral resolution are used. The analyses are applied using PCI Geomatica software and ARCGIS software is used for mapping purposes. Band ratio, decorrelation stretch, principal component analysis and thermal indices are used in order to map gypsum minerals. For gypsum minerals previously known Crosta method is modified and by the selection of suitable bands and principle components, gypsum minerals are tried to map and it is seen that it has a high success. For TIR indices previously known Quartz index is modified as Sulfate index and used for gypsum mapping. For relative accuracy all the results are add, percentages of the results are estimated. According to results<br>288 km2 area is mapped as gypsum with the total of four methods but it is seen that only 8 km2 is found by every methods. According to these percentages modified Crosta method and Sulfate Index methods are showed the highest success.

This investigation included characterisation of diverse sources for rust resistance and identification of genomic regions underpinning rust resistance in wheat. Markers linked to the adult plant leaf rust resistance gene Lr49 were identified using the 90K SNP (single nucleotide polymorphisms) array genotyping of the VL404/WL711 RIL population and alignment of flow-sorted chromosome sequences of chromosome 4B of parents VL404 and WL711. The Lr49-linked markers were tested on a large VL404/Avocet ‘S’ F2 population for fine mapping of the region. A RIL population of VL404/Avocet ‘S’ was evaluated against stripe rust pathotypes in the greenhouse and the underlying locus was named YrVL. Molecular mapping using the 40K Illumina XT SNP array placed YrVL (769.08-779.3 Mb) on the chromosome arm 2BL and found likely to be a new locus. A stripe rust resistant Tunisian landrace Aus26670 was crossed with the susceptible parent Avocet ‘S’ to develop the Aus26670/AvS RIL population. Seedling tests on this population indicated the presence of a single seedling stripe rust resistance gene and this locus was named YrAW12. Targeted genotyping-by-sequencing assay mapped YrAW12 in the 754.9-763.9 Mb region of chromosome 2BL. QTL (Quantitative trait loci) mapping of adult plant stripe rust response variation suggested the involvement of four QTL for stripe rust resistance in chromosomes 1BL, 5AL, 5BL and 6DS. Two QTL, QYr.sun-5AL (654.5Mb) and QYr.sun-6DS (1.4Mb), appear to be new. Genome-wide association study (GWAS) in a HarvestPlus panel was also undertaken to identify genomic regions conferring rust resistance and 10 minerals. This panel was genotyped using the 90K Infinium SNP array and 13 markers linked with rust resistance genes. GWAS identified six new QTL for rust resistance and 27 known genes/QTL. Forty-one known and 76 new QTL were identified for mineral content. Accessions carrying alien translocations (1B:1R and 2NS) displayed higher accumulation of some minerals.

The research contained within this thesis was directed at examining the spectral properties of regolith-dominated terrains using airborne and proximal hyperspectral instruments. The focus of the investigation was to identify the mineralogy of the regolith and determine if surficial materials were indicative of the underlying bedrock in the regolithdominated terrain of the eastern Olary Domain, South Australia. The research area was constrained to a 250 km2 area around the Cu-Au mineralisation of the White Dam Prosect. Integrated remote sensing, using airborne hyperspectral datasets (HyMap), Landsat imagery and gamma-ray spectroscopy data, was performed to map regolith-landforms and extract information on surficial materials. Detailed calibration of the HyMap dataset, using a modified model-based/empirical line calibration technique, was required prior to information extraction. The White Dam area was able to be divided into: alluvial regolith-dominated; in situ regolith-dominated; and bedrock-dominated terrains, based on mineralogical interpretations of the regolith, using the remotely sensed hyperspectral data. Alluvial regions were characterised by large abundances of vegetation and soils with a hematite-rich mineralogy. Highly weathered areas of in situ material were discriminated by the presence of goethite and kaolinite of various crystallinities, whereas the bedrock-dominated regions displayed white mica-/muscovite-rich mineralogy. Areas flanking bedrock exposures commonly consisted of shallow muscovite-rich soils containing regolith carbonate accumulations. Traditional mineral mapping processes were performed on the HyMap data and were able to extract endmembers of regolith and other surficial materials. The Mixture Tuned Matched Filter un-mixing process was successful at classifying regolith materials and minerals. Spectral indices performed on masked data were effective at identifying the key regolith mineralogical features of the HyMap imagery and proved less time consuming than un-mixing processes. Processed HyMap imagery was able to identify weathering halos, highlighted in mineralogical changes, around bedrock exposures. Proximal spectral measurements and XRD analyses of samples collected from the White Dam Prospect were used to create detailed mineralogical dispersion maps of the surface and costean sections. Regolith materials of the logged sections were found to correlate with the spectrally-derived mineral dispersion profiles. The HyLogger drill core scanning instrument was used to examine the mineralogy of the fresh bedrock, which contrasted with the weathering-derived near-surface regolith materials. The overall outcomes of the thesis showed that hyperspectral techniques were useful for charactering the mineralogy of surficial materials and mapping regolith-landforms.<br>Thesis (Ph.D.)--School of Earth & Environmental Sciences, 2004.

This thesis evaluates the combined use of multispectral remotely sensed data from the 0.45-2.35µm and 8µm-12µm wavelength regions for lithological mapping and mineral exploration in weathered, vegetated terrain. The area studied is located in N. E. Queensland, Australia, and consists of a mixture of igneous, metamorphic and sedimentary rocks. The extrusive and intrusive igneous rocks of acid to intermediate composition are currently the focus of active exploration for gold mineralisation. The results from this study indicate data from the 0.45-2.35µm wavelength region are of more use for mineral exploration than data from the 8-12µm wavelength region in this terrain. Evaluation of data from the 0.45-2.35µm wavelength region resulted in the discovery of an area of epithermal alteration with potential for gold mineralisation at Blackfellow Mountain. Data from both wavelength regions proved useful for litholgical mapping but certain lithological units could only be discriminated with the data from the 8-12µm wavelength region. In order to obtain these results the data were reduced to physically meaningful parameters (reflectance, temperature and emittance). This necessitated the removal of radiometric and geometric distortions. The techniques used to remove these distortions are outlined, including two new methods for the removal of atmospheric effects from data from the 8-12µm wavelength region. After correction, the data from the 0.45-2.35µm wavelength region were analysed by a variety of techniques to extract the relevant reflectance information. These included compositing, channel ratios, log residuals, directed principal components and least squares fit residuals (LRES). The log residual and LRES techniques proved most effective for lithological mapping and mineral exploration respectively. The corrected data from the 8-12µm wavelength region were also analysed by several techniques for extracting emittance and temperature information. These techniques were the decorrelation stretch, model emittance calculation and thermal log residuals. The latter technique, developed during this study, proved most effective for lithological mapping.

O mapeamento geológico dos depósitos siliciclásticos aflorantes nas bacias marginais do nordeste brasileiro tem gerado um alto volume de designações estratigráficas ainda abertas às discussões. No intuito de subsidiar a resolução deste problema cartográfico foi escolhida a parte emersa da Bacia Paraíba, mais especificamente as sub-bacias Alhandra e Mirirí. Para isto foi realizada a caracterização mineralógica e petrográfica dos arenitos cenozóicos da Bacia Paraíba, com vistas a identificação de critérios discriminadores entre os diversos depósitos siliciclásticos aflorantes. Derivado deste processo é acrescentado o reconhecimento das áreas fontes desses arenitos e suas implicações na evolução do Cenozóico da Bacia Paraíba. Análises laboratoriais incluíram análises granulométricas, de minerais pesados e morfológica de grãos em 134 amostras de superfície e subsuperfície. Foram estudadas também 5 seções delgadas para testar a petrografia sedimentar como ferramenta no auxílio do mapeamento geológico. A identificação dos minerais pesados transparentes foi feita através microscópio petrográfico, com quantificação dos principais minerais transparentes (100 grãos/lâmina), além de várias contagens independentes (100 grãos/lâmina) das relações transparentes/opacos, do par rutilo/zircão e sobre as formas e grau de arredondamento de zircão e turmalina. Em superfície foram mapeadas como unidades siliciclásticas de base para topo a Formação Barreiras (Mioceno), Depósitos Pós-Barreiras I (Neopleistoceno) e Depósitos Pós-Barreiras II (Holoceno). Em subsuperfície, o furo estudado atravessa toda seção cenozóica e mesozóica, inclusive as unidades basais da bacia, as formações Beberibe e Itamaracá. A mineralogia acessória é dominada por minerais opacos com porcentagens superiores a 60% em todas as unidades. Em toda sucessão cenozóica, as assembléias de minerais transparentes são muito homogêneas e apresentam como minerais principais zircão, turmalina, cianita e rutilo e, subordinadamente, estaurolita, andaluzita, topázio e anfibólios cálcicos. Ocorrem como traços sillimanita, epidoto, monazita e granada. Em subsuperfície, no entanto, na unidade basal é reportada a existência de granada como mineral principal. A análise de formas de zircão e turmalina permitiu diferenciar, tanto em superfície como em subsuperfície, os depósitos estudados. Em termos gerais, existe um maior grau de arredondamento das formas de zircão e turmalina na direção do topo das unidades. Os dados de petrografia, ainda que poucos, apontam diferenças texturais, composicionais e inclusive diagenéticas entre os arenitos aflorantes na bacia. Esta ferramenta mostrou-se promissora para a caracterização das unidades da bacia. A mineralogia acessória em superfície não permite diferenciar as unidades aflorantes, mas, em subsuperfície, mostra que a Formação Beberibe tem uma assinatura de granada que a caracteriza muito bem e permite concluir, de maneira categórica, que esta unidade não aflora na área estudada. Os resultados do estudo de formas em zircão e principalmente em turmalina permitem diferenciar as unidades aflorantes pelo grau de arredondamento dos grãos, o que evidencia uma reciclagem sedimentar inclusive das unidades cretáceas. Este dado é reproduzível em subsuperfície, onde as categorias euédricas concentram-se nas unidades basais. Assim, considera-se que as principais fontes para os depósitos cenozóicos são resultantes do retrabalhamento de unidades sedimentares preexistentes, e subordinadamente, de fontes primárias relacionadas às rochas metamórficas da Zona Transversal da Província Borborema.<br>The geologic mapping of siliciclastic deposits which outcrop in the marginals basins of Brazilian northeast have generated a high volume of stratigraphic designations that are opened to actual discussions. In order to solve this cartographic problem, the emerging part of the Paraiba basin was chosen, specifically the sub-basins of Alhandra and Mirirí. For this reason were realized the mineralogic and petrographic characterizations of the Cenozoic sands and sandstones of the Paraiba Basin, with the purpose of identifying the discriminating criteria between the diverse siliciclastic deposits. Additionally were realized the recognition of the sandstones´ source areas and its implications in the evolution of the Paraíba Basin in the Cenozoic times. The laboratory analysis included heavy minerals, granulometric, morphology from grains in 134 surface and subsurface samples. Five thin sections were studied to testify the sedimentary petrography as a tool for geological mapping. The identify of heavy minerals was done under petrographic microscope for species descriptions, with counting of 100 grains per slide. Several independent counts (100 grains/slide) of the ratio transparent/opaque, the rutile/zircon index and shape and grain roundness of the zircon and tourmaline were also done. On the geological mapping, the siliciclastic units were considered, from the base to the top, Barreiras Formation (Miocene), deposits Post-Barreiras I (Neopleistocene) and deposits Post-Barreiras II (Holocene). On subsurface, the drill hole studied crosses through the whole Cenozoic and Mesozoic stratigraphy of the basin, including the basal units (Beberibe and Itamaracá formations). The accessory mineralogy is dominated by opaque heavy minerals with higher percentages than 60% in all units. In the whole Cenozoic succession, the assembly of transparent heavy minerals is very homogeneous and is essentially composed by zircon, tourmaline, kyanite and rutile, containing also staurolite, andalusite, topaz and calcic amphibole subordinately. Sillimanite, epidote, monazite and garnet occur as a trace minerals. Otherwise, on subsurface, garnet is reported as a principal mineral in the basal unit. The analysis of zircon and tourmalines shapes allowed to distinguish all the studied deposits. In general, the grade of roundness in grains of zircon and tourmaline increases to the top of succession. The petrografic data showed textural, compositional and diagenetic differences between the cropping out sands - sandstones of the basin. This tool seemed to be a promising to characterize the stratigraphic units of Paraíba Basin. The accessory mineralogy permitted to distinguish the Beberibe Formation, which is well characterized by the presence of garnet. On the other hand, the absence of garnet in the described sandstones let to conclude the Beberibe Formation not exposed in the mapped area. The data from shape studies in grains of zircon and tourmaline allowed to differentiate the cropping out units by the roundness grade, evidencing a sedimentary recycling, including the Cretaceous units. This data is reproducible on subsurface samples where the euedrical categories are concentrated on the basal units. At last, the main sources of the Cenozoic deposits are considered to be reworked preexistence sedimentary units, and subordinately, the primary sources comprise the metamorphic rocks from Transversal Zone of Borborema Province.

Foram desenvolvidos trabalhos de prospeção de argilas comuns em terrenos atribuídos ao Jurássico superior e Cretácico inferior. Através da cartografia geológica temática foi possível a definição das principais zonas de ocorrência de argilas comuns. Os afloramentos argilosos cartografados estão alinhados NE-SW ao longo de cerca de 15 km, principalmente no topo do Jurássico superior. As matérias-primas caracterizadas são maioritariamente silto-argilosas, sendo predominantemente caulinítico-ilítico-quártzicas e exibem grande semelhança composicional entre si. As propriedades tecnológicas indicam também uma relativa homogeneidade das argilas. As condições ambientais que estiveram na génese dos depósitos não terão portanto divergido significativamente. As argilas possuem aptidão para o fabrico de tijolo e telha, no entanto, requerem lotação, armazenamento e maturação. Comprova-se que a região estudada constitui uma das principais áreas no país em argilas comuns para cerâmica de construção, possuindo recursos avultados (240 Mt) de características homogéneas em matérias-primas essenciais para a indústria cerâmica; ABSTRACT: Exploration work for common clays has been carried out in geological formations from Upper Jurassic to Lower Cretaceous. Through geological mapping of selected areas it was possible to define the major occurrences of common clay deposits. The mapped clay outcrops are aligned in NE-SW trend, along 15 km, and are mainly situated on the top of Upper Jurassic age deposits. Characterized raw materials are mostly within the silt-clayed domain, being predominately kaolinitic-ilitic-quartzic and exhibit great compositional similarity; technological properties also indicate relative homogeneity, showing the same genetic environmental formation conditions. Sampled materials are suitable to manufacture bricks and tiles, however they requires a previous treatment (blending, stocking and maturation). These raw materials show homogeneous characteristics, essential to regional ceramic industry, and regarding the Portuguese resources of common clays with application in construction ceramic, it was demonstrated that the studied region constitutes one of the major areas, having huge resources (240Mt).

The application of sensor technologies for raw material characterization is rapidly growing, and innovative advancement of the technologies is observed. Sensors are being used as laboratory and in-situ techniques for characterization and definition of raw material properties. However, application of sensor technologies for underground mining resource extraction is very limited and highly dependent on the geological and operational environment. In this study the potential of RGB imaging and FTIR spectroscopy for the characterization of polymetallic sulphide minerals in a test case of Freiberg mine was investigated. A defined imaging procedure was used to acquire RGB images. The images were georeferenced, mosaicked and a mineral map was produced using a supervised image classification technique. Five mineral types have been identified and the overall classification accuracy shows the potential of the technique for the delineation of sulphide ores in an underground mine. FTIR data in combination with chemometric techniques were evaluated for discrimination of the test case materials. Experimental design was implemented in order to identify optimal pre-processing strategies. Using the processed data, PLS-DA classification models were developed to assess the capability of the model to discriminate the three material types. The acquired calibration and prediction statistics show the approach is efficient and provides acceptable classification success. In addition, important variables (wavelength location) responsible for the discrimination of the three materials type were identified.

The application of sensor technologies for raw material characterization is rapidly growing, and innovative advancement of the technologies is observed. Sensors are being used as laboratory and in-situ techniques for characterization and definition of raw material properties. However, application of sensor technologies for underground mining resource extraction is very limited and highly dependent on the geological and operational environment. In this study the potential of RGB imaging and FTIR spectroscopy for the characterization of polymetallic sulphide minerals in a test case of Freiberg mine was investigated. A defined imaging procedure was used to acquire RGB images. The images were georeferenced, mosaicked and a mineral map was produced using a supervised image classification technique. Five mineral types have been identified and the overall classification accuracy shows the potential of the technique for the delineation of sulphide ores in an underground mine. FTIR data in combination with chemometric techniques were evaluated for discrimination of the test case materials. Experimental design was implemented in order to identify optimal pre-processing strategies. Using the processed data, PLS-DA classification models were developed to assess the capability of the model to discriminate the three material types. The acquired calibration and prediction statistics show the approach is efficient and provides acceptable classification success. In addition, important variables (wavelength location) responsible for the discrimination of the three materials type were identified.

This Master´s Thesis studies the applicability of existing numerical model to predict the conditions in the drifts at the mine. Damage mapping, covering the existing production levels, has been carried out to study the condition of the surface support, i.e. shotcrete, mesh and rock bolts to quantify the amount of deformation visible in the tunnels. Irregularities in the floor levels were also mapped. The rock support applied varies between different areas, from only a layer of shotcrete to areas where shotcrete, mesh and cable bolts are applied sequentially. The large amount of support in some regions is required because of high in situ rock stresses in Kemi Mine. The geological conditions are challenging, with large local variation making efficient supporting and damage prediction difficult. Access drifts at the mine have varying service times, on average 6 years, which is a long time in a difficult environment. The results from this work are a mine specific damage classification, used in the mapping to capture the range of damages seen on site. A reoccurrence of same areas showing damages on several production levels is noted. Digitized versions of the damage maps were made and these have been compared to simulation results. The comparisons were made to plots of deviatoric strain, deviatoric stress and total displacement. Based on the work done during this project it can be concluded that the studied parameters have varying levels of agreement with the drifts, both when comparing the levels with each other and the results in the same level between spring and autumn. The best agreement is found with the deviatoric strain increment and the yielded elements. Rock mechanics and geological reasons for the variations seen between the mapping results and the simulations results can be further studied in the future, as can the alternatives for increasing the accuracy through changes in the numerical model or model type used for comparison.

<p>The Morokweng impact structure which is located in the North West province of South Africa, has attracted attention as a potential host for Ni-PGE mineralization. Geochemical exploration techniques using hydroxylamine partial extraction were used to determine the nature and source of surface geochemical anomalies known to occur in the overlying aeolian sang regolith. About 40 aeolian samples were taken from an area of about 35 square kilometer, located in the north eastern sector of the Morokweng impact structure. The samples were sieved to various grain size fractions and partially extracted using varying concentration of hydroxylamine hydrochloride at 50&deg<br>C.</p>

Lithium represents one of the strategic elements for the rest of the 21st century due to its increasing demand in technological applications. Therefore, new efforts should be focused on the optimization of mineral characterization processes, which link the ore properties with its behaviour during downstream processes. These efforts should result in reducing operational risks and increasing resources utilization. The methodology presented in this study is based on the application of several classification techniques, aiming the mineral and textural characterization of two spodumene pegmatite deposits within the Keliber Lithium Project. Twelve textural classes have been proposed for the textual classification of the ore, which have been defined through the recognition of the main mineral features at macro- and micro-scale. The textural classification was performed through the application of drill core logging and scanning electron microscopy. Six classes are proposed to describe the characteristics of the spodumene ore. Six additional classes describe the main properties of the rocks surrounding the ore zone. Image analysis was implemented for the generation of mineral maps and the subsequent quantification of spodumene and Li2O within the analysed drill core images. The image segmentation process was executed in Fiji-ImageJ and is based on eight mineral classes and a set of seven feature extraction procedures. Thus, quantification of spodumene and Li2O is estimated by textural class. Hyperspectral images were used as a reference for assessing the estimations made through images analysis. A machine learning model in Weka allowed forecasting the behaviour of the twelve textural classes during spodumene flotation. This model is fed by metallurgical data from previous flotation tests and uses Random Forest classifier. The proposed methodology serves as an inexpensive but powerful approach for the complete textural characterization of the ore at Keliber Lithium Project. It provides information about: (1) mineral features at different scales, (2) spatial distribution of textures within the pegmatite body, (3) quantification of spodumene and Li2O within the drill cores and (4) processing response of each textural class. However, its application requires wide knowledge and expertise in the mineralogy of the studied deposits.<br><p>Thesis Presentation.</p><p>Textural and Mineralogical Characterization of Li-pegmatite Deposit: Using Microanalytical and Image Analysis to Link Micro and Macro Properties of Spodumene in Drill Cores.  Keliber Lithium Project, Finland.</p><p></p>

The application of fuzzy logic in a GIS framework is a valuable method to assist in mineral resource assessments (MRA) in areas where data are sparse. This study uses a digital geological map, backed by a digital geological data model, derived from published legends and reports. Together they function as a 'spatial-attribute relational data model' that provides evidence, in the form of derivative maps, to support mineral potential according to deposit model criteria. A knowledge-base is created with fuzzy membership functions linked to the classes of each derivative map that indicate favourability between geological features present in the database with those required by model criteria. A fuzzy-logic-based 'inference net', as implemented in the GIS modelling language, is used to combine spatial evidence to determine mineral resource potential for three mineral deposit sub-types: (1) MVT Pb-Zn, (2) Sedimentary Cu and (3) Sediment-Hosted Sulphides. This method is shown to be valuable for providing an 'audit trial' for the complex decision-making process associated with resource assessment; it provides a means for experimenting and testing various hypotheses and viewpoints associated with mineral deposit models, and mimics some aspect of how geologists determine mineral potential for a region using information provided in geological maps and mineral deposit model literature.

Diese Dissertation befasst sich mit räumlichen Wahrnehmungen und Diskursen, mit denen man den Raum und seine Bestandteile behandelte. Die Eroberung Sibiriens im 17. Jahrhundert bewirkte einen tiefgreifenden Wandel in den russischen Vorstellungen über die weit entfernte Peripherie sowie deren Ressourcen. Die neuen Denkweisen kristallisierten sich in einer diskursiven Formation heraus, die Macht über Raum und Rohstoffe Sibiriens symbolisierte und organisierte. Dieser „Berg-Diskurs“ trug moderne Züge, denn er bedurfte sich neuer Formen der Kontrolle über die Raumsproduktion. Diese Einstellung wurde allmählich zu einer erstaunlich überlebensfähigen räumlichen Ideologie und zum festen Bestandteil des russischen Bodenschätzediskurses der Zukunft. Die Rolle der Wissensproduzenten wechselte zwischen den zentralen und regionalen Institutionen und Netzwerken. Der „Altai“, der den kaiserlichen Bergbau-Bezirk und die Gebirgslandschaft umfasste, wurde auf Grund seines Rohstoffreichtums von Repräsentanten des russischen Staates als Region erfunden. Die Dissertation stellt die imaginären und realen Geographien des Altai in drei unterschiedlichen Dimensionen dar. Dabei geht es um den Wandel der Repräsentationen von geographischen Räumen und der Berglandschaften in Russland insgesamt (Makroebene), die Mehrschichtigkeit des russischen Diskurses über Bergregionen und Gebirgslandschaften (Mesoebene) und den Altai als facettenreiches Konzept einer komplexen imperialen geographischen Imagination (Mikroebene). Die Beschreibung des Altai faßte in sich zahlreiche inkohärente Bilder verschiedener sozialer Gruppen. Der Ort wurde durch mentale Geographien erfolgreich instrumentalisiert, z.B. „die Goldenen Gebirge“ und „die sibirische Schweiz“. Diese Bilder machten die Region sichtbar, sowohl für nationalistisch gesinnte Gruppen als auch die breiteren Bervölkerungsschichten.<br>This dissertation focuses on the production of imperial space with a particular emphasis on the role of power discourses concerning mineral resources. By relying on published materials, it aims to establish a new conceptual framework for the examining of cultural patterns and practices of imagining of space and mineral wealth. For that purpose, it introduces a concept of the ”Berg-Discourse” that expands our understanding of the Russian engagement with geographical space. It begins by exploring Russian exposure to the mountains and mineral resources of Siberia in terms of the spatial knowledge production. It then examines how Russian imperial strategies and aspirations were embedded in the making of the Altai, a vast mining territory in West Siberia that once formed a private domain of the Russian rulers. The dissertation argues that the making of the Altai was in many ways part of the same imperial impulse towards mineral exploitation. It explores the ways in which the Altai was imagined through its enormous mineral endowment; how the imagined place became real; and how this real place became imagined from various vantage points. As the study shows, the region acquired multiple mental representations, enjoying a near mythological presence across imperial culture. Finally, the dissertation concludes by showing how this landscape was incorporated into imperial and national myths in the course of production and consumption of spatial knowledge about the remote location.

The Pacific oceanic plate segment known as the Clarion Clipperton Zone (CCZ), contains polymetallic nodules of superior consistency, tonnage and quality, to those known from other deep seabed areas. Regional scale mapping reveals structural and geomorphological features that result from variance in plate segment motion rates, and other trans-plate factors, which help to contextualise and better define the environment and exploration potential of this deposit. Exploration survey datasets from the central and eastern parts of the CCZ area allow for local geological mapping that contribute to regional models on nodule formation and distribution. Stratigraphically, basement abyssal hills include flatter areas with chain(s) of volcanic knolls. Mid Eocene and younger deep-sea chalks of the Marquesas Formation, include fault escarpment exposure, potholes and “carbonate strata breccias”. Early Miocene to present silicious clayooze of the Clipperton Formation show surficial development of ripples, slumping and sediment drifts. The clay-ooze hosts the deposit of polymetallic nodules. Unconformable volcanic rock units include single and composite knolls, seamounts, dykes and sills. Nodule forms and abundance relate to the facies scale conditions of their formation. The thickness and stability of the geochemically active layer is shown to play a crucial role on their growth. Multielement chemistry indicates differing metal contributions from silicic versus calcic primary productivity. This study confirms nodule densities, host clay-ooze bulk densities and packing densities, as well as moisture content. Moreover, it is shown that nodule handling forms attrition fines that may affect safe transport at sea. Mineral resource estimation is important to resource owner and developers. Further conversion of mineral resources to reserves requires multidisciplinary modifying factors, which include: logging of fauna; concepts behind a nodule collection system; and pyrometallurgical experiments. This study aims to improve the resource classification of the CCZ deposit in specific contract areas of the International Seabed Authority; Resumo: Geologia da Zona de Fratura de Clarion-Clipperton: Atributos Fundamentais no Desenvolvimento dos Nódulos Polimetálicos como Recurso Geológico - A área do fundo marinho conhecida por zona de fratura de Clarion-Clipperton (CCZ), no Pacífico, alberga um depósito de nódulos polimetálicos de tonelagem e qualidade superiores quando comparado com outros depósitos minerais do oceano profundo. A cartografia à escala regional permite reconhecer estruturas e características morfológicas que resultam da variação da taxa de alastramento do fundo marinho, bem como de outros fatores que afetam a evolução da CCZ e que contribuem para definir com mais detalhe o potencial envolvido na prospeção daquele depósito mineral. Os dados recolhidos no decurso de campanhas conduzidas nas zonas central e oriental da CCZ permitem realizar cartografia geológica que contribui para a formulação de modelos regionais para a formação e distribuição dos nódulos polimetálicos. Estes ocorrem associados à formação de Clipperton, com idade entre o Miocénico inferior e a atualidade. Neste trabalho é particularmente evidenciado o papel da espessura e estabilidade da camada geoquimicamente ativa no crescimento e forma dos nódulos, bem como da sua distribuição. A geoquímica multi-elementar indica diferentes contributos da produtividade primária (siliciosa versus carbonatada) para a distribuição dos diferentes metais que constituem os nódulos. Neste estudo são, igualmente, estabelecidos valores para diferentes parâmetros físicos relevantes para as atividades de prospeção, como sejam a densidade dos nódulos e dos sedimentos argilosos onde ocorrem. A classificação e estimativa de recursos minerais é relevante quer para as entidades que detêm a jurisdição sobre esses recursos quer para as entidades interessadas no seu desenvolvimento. A conversão de recursos para reservas minerais requer a aplicação dos designados por modifying factors, os quais incluem, entre outros: a descrição da fauna, o conceito associado ao desenvolvimento de colectores, testes pirometalúrgicos. Este trabalho pretende melhorar, de forma significativa, a classificação de recursos da CCZ em áreas associadas a contratos administrados pela Autoridade Internacional dos Fundos Marinhos.

This thesis study employs textural classification techniques applied to four different data groups: (1) visible light photography, (2) high-resolution drill core line scan imaging (3) scanning electron microscopy backscattered electron (SEM-BSE) images, and (4) 3D data from X-ray microtomography (μXCT). Eleven textural classes from Aitik ores were identified and characterized. The distinguishing characteristics of each class were determined such as modal mineralogy, sulphide occurrence and Bond work indices (BWI). The textural classes served as a basis for machine learning classification using Random Forest classifier and different feature extraction schemes. Trainable Weka Segmentation was utilized to produce mineral maps for the different image datasets. Quantified textural information for each mineral phase such as modal mineralogy, mineral association index and grain size was extracted from each mineral map.  Efficient line local binary patterns provide the best discriminating features for textural classification of mineral texture images in terms of classification accuracy. Gray Level Co-occurrence Matrix (GLCM) statistics from discrete approximation of Meyer wavelets decomposition with basic image statistical features[PK1]  (e.g. mean, standard deviation, entropy and histogram derived values) give the best classification result in terms of accuracy and feature extraction time. Differences in the extracted modal mineralogy were observed between the drill core photographs and SEM images which can be attributed to different sample size[PK2] . Comparison of SEM images and 2D μXCT image slice shows minimal difference giving confidence to the segmentation process. However, chalcopyrite is highly underestimated in 2D μXCT image slice, with the volume percentage amounting to only half of the calculated value for the whole 3D sample. This is accounted as stereological error. Textural classification and mineral map production from basic drill core photographs has a huge potential to be used as an inexpensive ore characterization tool. However, it should be noted that this technique requires experienced operators to generate an accurate training data especially for mineral identification and thus, detailed mineralogical studies beforehand is required.<br>Primary Resource Efficiency by Enhanced Prediction (PREP)<br>Center for Advanced Mining and Metallurgy (CAMM)

Machine learning describes an array of computational and nested statistical methods whereby a computer can ‘learn’ and subsequently make predictions or identify patterns in data. With the increasing volume and variety of numerical data in the geosciences, and widespread availability of the needed computing power, machine learning techniques are a logical addition to the numerous possible approaches that can be applied to the search for ore deposits. The three core research chapters in this thesis develop the application of machine learning in the context of mineral exploration. Emphasis is placed on the Random Forests algorithm for mapping lithology in a range of settings and at a variety of stages in the exploration process. Information entropy is used to assist both in assessing and communicating any complex combinations, and potential inaccuracy, of classification results. Through the thesis, methods are employed with future practical usage in mind, such that machine learning may be used by the geologist (as domain expert) in an objective manner. The first of these core studies uses the Random Forests algorithm to re-classify the solid geology lithology map of the Heron South project, located in the Eastern Goldfields ofWestern Australia. This study uses geophysical and remote sensing data, in the absence of geochemical samples and geological ground truthing with most of the project under transported cover. This is characteristic of an early stage, reconnaissance exploration project. A sparse training sample of 1.6 percent of the total area, is taken as training data, allowing much of the areas geology the freedom to be reclassified. This study demonstrates that Random Forests, with proper consideration given to sampling and training data selection, can be used effectively to produce or improve geological mapping in little-explored areas. Information entropy is shown to be valuable in predicting where classification was likely to be inaccurate or a region highly complex. The second core study uses Random Forests to produce a solid geology map of the Kliyul porphyry prospect of British Columbia, Canada, using a fusion of available geophysical and geochemical data, typical of a greenfields stage exploration project. Soil and rock chip sample sites were taken as training data, used to classify the remainder of the project area. Assessment of the probability distributions produced using the Random Forests algorithm enabled regions with an elevated probabilityof intrusions (a key indicator lithology) to be mapped, even where not observed in training data. The results of this study highlight the value of a soft, ensemble classifier such as Random Forests, and the value to be gained from an assessment of the spatial distribution of class probabilities as opposed to viewing a final map as a solution in isolation. In the third and final core study, a range of training data sampling paradigms are tested in a data rich area located in the Domes region of the Central African Copper belt hosting the Sentinel (Ni) and Enterprise (Cu) deposits. This study simulates early and advanced stage exploration project maturity in incorporating a priori geological Information. It culminates in the use of Random Forests to undertake an objective audit of the present company geological map. Further to this, unsupervised clustering is used in the production of a geological map in the absence of training or constraint through identifying the natural grouping of data. The results of these studies highlight the importance of proper sample balancing and explore the repercussions of limited and/or non-representative training data. The use of the information entropy proxy is developed to identify where a classification may depart from the domain represented by training data. The ranking of input data that is performed in association with the Random Forests classification can be used to improve clustering results through optimising dataset selection. Through the three core research chapters, a set of practical considerations and recommendations for explorers are provided. It is demonstrated that Random Forests can provide an objective audit and subsequent refinement of a pre-existing geological map. The expression of uncertainty using information entropy, and the assessment of class probabilities, can be used to appraise the results from the machine learning analyses. This includes validation in the case of complex outcome combinations, and generation of new insights. Ranking of input datasets via Random Forests can enhance understanding of data and improve both Random Forests classification results and improve clustering. With the proper selection of appropriate datasets, clustering (for example immobile trace elements) and scaling can indeed produce results that correspond well with lithology. Studies presented in this thesis use data from current/active exploration projects and methods are distilled to streamlined workflows using industry standard software and data formats. In summary, these methods, previously the domain of computer and data scientists, are now developed to be more widely accessible to mineral explorers.

Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy. School of Animal, Plant and Environmental Science, University of the Witwatersrand, Johannesburg, South Africa. October 2016.<br>Mining has negative impacts on the environment in many different ways. One method developed to quantify some of these impacts is Landscape Function Analysis (LFA) and this has been accepted by some mining companies and regulators. In brief, LFA aims at quantifying the organization of vegetative and landscape components in a landscape into patches along a transect and quantifying, in a relative manner, three basic processes important to landscape functioning, namely: soil stability or susceptibility to erosion, infiltration or runoff, and nutrient cycling or organic matter decomposition. However, LFA is limited in large heterogeneous environments, such as those around mining operations, due to its localized nature, and the man hours required to collect a representative set of measurements for such large and complex environments. Remote sensing using satellite-acquired data can overcome these limitations by sampling the entire environment in a rapid and objective manner. What is required is a method of connecting these satellite-based measurements to LFA measurements and then being able to extrapolate these measurements across the entire mine surface. The aim of this research was to develop a method to use satellite-based hyperspectral imagery to predict landscape function analysis (LFA) using partial least squares regression (PLSR). This was broken down into three objectives: (1) Collection of the LFA data in the field and validation of the LFA indices against other environmental variables collected at the same time, (2) validation of PLSR models predicting LFA indices and various environmental variables from ground-based spectra, and (3) production of risk maps based on predicting LFA indices and above-ground biomass using PLSR models and Hyperion satellite-based hyperspectral imagery. Although the study was based in grasslands at two mining regions, West Wits and Vaal River, a suitable Hyperion image was only available for Vaal River. A minimum of 374 points were sampled for LFA indices, ground-based spectra, above-ground biomass and soil cores along 2880 m of LFA transect from both mine sites. Soil cores were weighed fresh before sieving with a 2 mm sieve to separate root and stone fractions. The sieved soil fraction was tested for pH, EC, SOM, and for the West Wits samples, organic nitrogen and total extractable inorganic nitrogen. There was one modification to the LFA method where grass patches were collapsed into homogenous units as it was deemed not feasible to sample 180 m transects at grass tuft scales of 10 – 30 cm, but other patch definitions followed the LFA manual (Tongway and Hindley, 2004). Evidence suggested that some of the different patch types, in particular the bare/biological soil crust – bare grass – sparse grass patch types, represented successional stages in a continuum although this was not conclusive. There also was evidence that the presence or absence of cattle play a role in some processes active in these grasslands and erosion is mainly through deflation, rain splash and sheet wash. Generally the environmental variables supported the LFA indices although the nutrient cycling index was representative of above-ground nutrient cycling but not below-ground nutrient cycling. Models derived with PLSR to predict the LFA indices from ground-based spectral measurements were strong at both mine sites (West Wits: LFA stability r2 = 0.63, P < 0.0001; LFA infiltration r2 = 0.75, P < 0.0001; LFA nutrient cycling r2 = 0.73, P < 0.0001; Vaal River: LFA stability r2 = 0.39, P < 0.0001, LFA infiltration r2 = 0.72, P < 0.0001, LFA nutrient cycling r2 = 0.54, P < 0.0001), as were PLSR models predicting above-ground biomass (West Wits above-ground biomass r2 = 0.55, P = 0.0003; Vaal River above-ground biomass r2 = 0.79, P < 0.0001) and soil moisture (West Wits soil moisture r2 = 0.45, P = 0.0017; Vaal River soil moisture r2 = 0.68, P < 0.0001). However, for soil organic matter (r2 = 0.50, P < 0.0001) and EC (r2 = 0.63, P < 0.0001), Vaal River had strong prediction models while West Wits had weak models for these variables (r2 = 0.31, P = 0.019 and r2 = 0.10 and P < 0.18, respectively). For EC, the wide range of soil values at Vaal River in association with gypsum crusts, and low values throughout West Wits explained these model results but for soil organic matter, no clear explanation for these site differences was identified. Patch-based models could accurately discriminate between spectrally well-defined patch types such S. plumosum patches but were less successful with patch types that were spectrally similar such as the bare/biological soil crust – bare grass – sparse grass patch continuum. Clustering similar patch types together before PLSR modelling did improve these patch-based spectral models. To test the method proposed to predict LFA indices from satellite-based hyperspectral imagery, a Hyperion image matching 6 transects at Vaal River was acquired by NASA’s EO-1 satellite and downloaded from the USGS Glovis website. LFA transects were partitioned to match and extract pixel spectra from the Hyperion data cube. Thirty-one spectra were separated into calibration (20) and validation (11) data. PLSR models were derived from the calibration data, tested with validation data to select the optimum model, and then applied to the entire Hyperion data cube to produce prediction maps for five LFA indices and above-ground biomass. The patch area index (PAI) produced particularly strong models (r2 = 0.79, P = 0.0003, n =11) with validation data, whereas the landscape organization index (LOI) produced weak models. It is argued that this difference between these two essentially similar indices is related to the fact that the PAI is a 2-dimensional index and the LOI is a 1-dimensional index. This difference in these two indices allowed the PAI to compensate for some burned pixels on the transects by “seeing” the density pattern of grass tufts and patches whereas the linear nature of the LOI was more susceptible to the changing dimensions of patch structure due to the effects of fire. Although validation models for the three LFA indices of soil stability, infiltration and nutrient cycling were strong (r2 = 0.72, P = 0.004; r2 = 0.66, P = 0.008; r2 = 0.70, P = 0.005, n = 9 respectively), prediction maps were confounded by the presence of fire on some transects. The poor quality of the Hyperion imagery also meant great care had to be taken in the selection of models to avoid poor quality prediction maps. The 31 bands from the VNIR (478 – 885 nm) portion of the Hyperion spectra were generally the best for PLSR modelling and prediction maps, presumably because of better signal-to-noise ratios due to higher energy in the shorter wavelengths. With two satellite-based hyperspectral sensors already operational, namely the US Hyperion and the Chinese HJ-1A HSI, and a number expected to be launched by various space agencies in the next few years, this research presents a method to use the strengths of LFA and hyperspectral imagery to model and predict LFA index values and thereby produce risk maps of large, heterogeneous landscapes such as mining environments. As this research documents a method of partitioning the landscape rather than the pixel spectra into pure endmembers, it makes a valuable contribution to the fields of landscape ecology and hyperspectral remote sensing.<br>LG2017

The research contained within this thesis was directed at examining the spectral properties of regolith-dominated terrains using airborne and proximal hyperspectral instruments. The focus of the investigation was to identify the mineralogy of the regolith and determine if surficial materials were indicative of the underlying bedrock in the regolithdominated terrain of the eastern Olary Domain, South Australia. The research area was constrained to a 250 km2 area around the Cu-Au mineralisation of the White Dam Prosect. Integrated remote sensing, using airborne hyperspectral datasets (HyMap), Landsat imagery and gamma-ray spectroscopy data, was performed to map regolith-landforms and extract information on surficial materials. Detailed calibration of the HyMap dataset, using a modified model-based/empirical line calibration technique, was required prior to information extraction. The White Dam area was able to be divided into: alluvial regolith-dominated; in situ regolith-dominated; and bedrock-dominated terrains, based on mineralogical interpretations of the regolith, using the remotely sensed hyperspectral data. Alluvial regions were characterised by large abundances of vegetation and soils with a hematite-rich mineralogy. Highly weathered areas of in situ material were discriminated by the presence of goethite and kaolinite of various crystallinities, whereas the bedrock-dominated regions displayed white mica-/muscovite-rich mineralogy. Areas flanking bedrock exposures commonly consisted of shallow muscovite-rich soils containing regolith carbonate accumulations. Traditional mineral mapping processes were performed on the HyMap data and were able to extract endmembers of regolith and other surficial materials. The Mixture Tuned Matched Filter un-mixing process was successful at classifying regolith materials and minerals. Spectral indices performed on masked data were effective at identifying the key regolith mineralogical features of the HyMap imagery and proved less time consuming than un-mixing processes. Processed HyMap imagery was able to identify weathering halos, highlighted in mineralogical changes, around bedrock exposures. Proximal spectral measurements and XRD analyses of samples collected from the White Dam Prospect were used to create detailed mineralogical dispersion maps of the surface and costean sections. Regolith materials of the logged sections were found to correlate with the spectrally-derived mineral dispersion profiles. The HyLogger drill core scanning instrument was used to examine the mineralogy of the fresh bedrock, which contrasted with the weathering-derived near-surface regolith materials. The overall outcomes of the thesis showed that hyperspectral techniques were useful for charactering the mineralogy of surficial materials and mapping regolith-landforms.<br>Thesis (Ph.D.)--School of Earth & Environmental Sciences, 2004.

This study provides one of the first accounts of the relationships between termites, termitaria and the pedolith, towards developing their application as a biogeochemical sampling medium for mineral exploration. Mapping regolith–landforms, termitaria, and the associated termitaria biogeochemistry show that termites are an integral control on the organisation of trace metals in the landscapes of northern Australia. In particular, termites are important for transporting geochemical signatures from depth, through the pedolith and to the ground surface. This occurs by way of bioturbative and constructional activities of the mound-building termites, which in this study included Nasutitermes triodiae, Amitermes vitiosus, Drepanotermes rubriceps, Tumulitermes hastilis and T. pastinator. Termitaria from these species are mappable regolith– landform attributes at the local scale; this highlights their specific preferences for colony sites, such as access to vegetation, drainage, and the availability of construction materials. The mound-building termites featured in this study are also soil modifiers, altering the pedolith terms of both structure and chemistry. Developing an understanding of these processes has helped to refine a model for pedolith development through biotic processes, which is applicable to subtropical and tropical climatic regions, where termites act as important ecosystem engineers. This research project fills a niche for new scientific investigation of deeper regolith profiles and associated terrains; it moves away from theories of shallow soil development overlying an abiotic deep regolith, towards understanding pedolith development as wholly biotically driven. For mineral explorers this means that ore-related elements, such as Au, As and Zn, are re-organised and moved towards the land surface in settings such as buried Au-deposits and mineralisation in the Tanami region, and Pine Creek Orogen. A key finding within the study of the application of this technique is that the fine, silt-clay (>79 μm) from termitaria is capable of accurately delineating the surficial expression of buried Au mineralisation. Termitaria can therefore provide an accessible surficial biogeochemical sampling media that can be used in mineral exploration programs<br>http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1369217<br>Thesis (Ph.D.) - University of Adelaide, School of Earth and Environmental Sciences, 2009

Die hyperspektrale Bildgebung stellt eine Schlüsseltechnologie in der nicht-invasiven Mineralanalyse dar, sei es im Labormaßstab oder als fernerkundliche Methode. Rasante Entwicklungen im Sensordesign und in der Computertechnik hinsichtlich Miniaturisierung, Bildauflösung und Datenqualität ermöglichen neue Einsatzgebiete in der Erkundung mineralischer Rohstoffe, wie die drohnen-gestützte Datenaufnahme oder digitale Aufschluss- und Bohrkernkartierung. Allgemeingültige Datenverarbeitungsroutinen fehlen jedoch meist und erschweren die Etablierung dieser vielversprechenden Ansätze. Besondere Herausforderungen bestehen hinsichtlich notwendiger radiometrischer und geometrischer Datenkorrekturen, der räumlichen Georeferenzierung sowie der Integration mit anderen Datenquellen. Die vorliegende Arbeit beschreibt innovative Arbeitsabläufe zur Lösung dieser Problemstellungen und demonstriert die Wichtigkeit der einzelnen Schritte. Sie zeigt das Potenzial entsprechend prozessierter spektraler Bilddaten für komplexe Aufgaben in Mineralexploration und Geowissenschaften.<br>Hyperspectral imaging (HSI) is one of the key technologies in current non-invasive material analysis. Recent developments in sensor design and computer technology allow the acquisition and processing of high spectral and spatial resolution datasets. In contrast to active spectroscopic approaches such as X-ray fluorescence or laser-induced breakdown spectroscopy, passive hyperspectral reflectance measurements in the visible and infrared parts of the electromagnetic spectrum are considered rapid, non-destructive, and safe. Compared to true color or multi-spectral imagery, a much larger range and even small compositional changes of substances can be differentiated and analyzed. Applications of hyperspectral reflectance imaging can be found in a wide range of scientific and industrial fields, especially when physically inaccessible or sensitive samples and processes need to be analyzed. In geosciences, this method offers a possibility to obtain spatially continuous compositional information of samples, outcrops, or regions that might be otherwise inaccessible or too large, dangerous, or environmentally valuable for a traditional exploration at reasonable expenditure. Depending on the spectral range and resolution of the deployed sensor, HSI can provide information about the distribution of rock-forming and alteration minerals, specific chemical compounds and ions. Traditional operational applications comprise space-, airborne, and lab-scale measurements with a usually (near-)nadir viewing angle. The diversity of available sensors, in particular the ongoing miniaturization, enables their usage from a wide range of distances and viewing angles on a large variety of platforms. Many recent approaches focus on the application of hyperspectral sensors in an intermediate to close sensor-target distance (one to several hundred meters) between airborne and lab-scale, usually implying exceptional acquisition parameters. These comprise unusual viewing angles as for the imaging of vertical targets, specific geometric and radiometric distortions associated with the deployment of small moving platforms such as unmanned aerial systems (UAS), or extreme size and complexity of data created by large imaging campaigns. Accurate geometric and radiometric data corrections using established methods is often not possible. Another important challenge results from the overall variety of spatial scales, sensors, and viewing angles, which often impedes a combined interpretation of datasets, such as in a 2D geographic information system (GIS). Recent studies mostly referred to work with at least partly uncorrected data that is not able to set the results in a meaningful spatial context. These major unsolved challenges of hyperspectral imaging in mineral exploration initiated the motivation for this work. The core aim is the development of tools that bridge data acquisition and interpretation, by providing full image processing workflows from the acquisition of raw data in the field or lab, to fully corrected, validated and spatially registered at-target reflectance datasets, which are valuable for subsequent spectral analysis, image classification, or fusion in different operational environments at multiple scales. I focus on promising emerging HSI approaches, i.e.: (1) the use of lightweight UAS platforms, (2) mapping of inaccessible vertical outcrops, sometimes at up to several kilometers distance, (3) multi-sensor integration for versatile sample analysis in the near-field or lab-scale, and (4) the combination of reflectance HSI with other spectroscopic methods such as photoluminescence (PL) spectroscopy for the characterization of valuable elements in low-grade ores. In each topic, the state of the art is analyzed, tailored workflows are developed to meet key challenges and the potential of the resulting dataset is showcased on prominent mineral exploration related examples. Combined in a Python toolbox, the developed workflows aim to be versatile in regard to utilized sensors and desired applications.

<p>Combination of remote sensing data with <i>in-situ</i> measurements provides a fuller understanding of Mars phenomena. This dissertation focuses on integrating macroscopic and microscopic scales of measurement with regard to spectroscopy and magnetization. In the first chapter high resolution orbital spectroscopy (~18 m/px) and imagery (~30 cm/px) are used to identify potential sources for some of the sedimentary rocks investigated by the Curiosity rover and expand the accessible stratigraphy. While we find mineralogies in common outside and inside the crater as well as transport mechanisms, we conclude that additional sedimentary sources and/or modification after transport are required to explain chemical differences and that strata point to multiple episodes of a lake in Gale crater. In the third chapter we conducted a laboratory photometric study on candidate calibration target materials for the Mars-2020 rover. We characterized these target materials for proper calibration and monitoring of the Mastcam-Z instrument to enable mineral identification through reflectance spectroscopy. The fourth and fifth chapters focus on the microscopic magnetizations found within Martian meteorite ALH84001. Chapter four reports on paleomagnetic experiments conducted on isolated carbonate crystals which contain magnetite previously reported to be biogenic. We compare paleomagnetic test results which distinguish between biogenic and abiogenic origin hypotheses and find that the magnetization within the carbonates is most consistent with a shock processes. In chapter five we analyzed the distribution of dipoles within slices of ALH84001 and determined that they lie in a girdle distribution which could be interpreted as resulting from a true polar wander event on Mars. Looking at kilometer scale observations outside of Gale enlightened observations made along the rover transverse path. A high resolution laboratory analysis of calibration materials will enable future multispectral mineralogical explorations. Microscopic analyses of magnetization inform ancient surface processes on Mars and hint at large-scale global change. In each of these chapters our results were only made possible or greatly enhanced by the combination of data sources and scales.</p>