During the past 150 years, most of the modern day creeks were the target of miners roaming the Cariboo Mountains, British Columbia, in the search for placer gold. In these days, the probability to locate new placer gold occurrence in recent river beds is therefore substantially reduced. New, promising exploration targets appear to be channels mostly buried under alluvial cover sediments. It is airborne geophysical methods that can reveal hidden channels fast and cost-effectively as these penetrate the sub-surface contactless and reflect physical properties of the sub-surface, such as electric conductivity and magnetic susceptibility or magnetization, respectively.We applied the airborne geophysical exploration approach on four exploration areas in the Cariboo gold district Helicopter-borne transient electromagnetic (TEM) and magnetic data were flown using the SkyTEM system. To our knowledge, it has been innovatory to apply high resolution, high density airborne geophysics in the search for placer gold deposited in pre-Holocene sedimentary channel fills of the Cariboo Mountains. A particular effort of our studies aimed at the Mary creek claims which straddle the boundary of the Quesnel and Kootenay terranes of the Canadian Cordillera and include the dormant Toop mine situated in the Mary creek area known for many finds of coarse nugget from the pre-glacial buried Toop channel. Our objective was to locate the southbound extension of the channel buried in Pleistocene sediments of the Toop plateau. Careful analysis of the airborne geophysical data sets provided indications from both the TEM and magnetic data sets favouring the existence of a hidden channel beneath the plateau.The evaluation of seven reverse circulation (RC) drill holes sunk into a promising elongated narrow conductor beneath the plateau was not conclusive as not clearly showing the sedimentary pattern of a channel with gravels typically at its bottom. Only electric conductivity-depth sections compiled from the airborne TEM and 2D direct current (DC) multi-electrode resistivity ground survey data enabled the interpretation of the airborne TEM and magnetic responses recorded over the Toop plateau. The sections suggest that the electric conductor is generated by an upwarp of a conductive layer extending at the bottom of the Pleistocene sediments. Another feature separated by :5100 m from the conductor line is reflected by low electric conductivity, but is rarely prominent through its neat magnetic signature. Fine accumulations of black minerals, i.e. magnetite grains, in sediments of the area are frequently met when panning material from the creeks. We therefore interpret this low conductivity, magnetic feature as expression of a gravel lense hosting accumulations of magnetite grains and possibly indicating the southbound extension of the Toop channel beneath the plateau.Careful analysis of the airborne magnetic data set led to the result in that magnetite is not only wide-spread in present day rivers and creeks, but also in buried channels and palaeo precipitation run-off paths. Magnetic data proved to be very helpful in this project with regard of pursuing not only present day, but buried valleys and channels, in particular.Our experience made on the Mary creek claims is summarized in a straightforward exploration concept for hidden, possibly gold-bearing channels in the Cariboo gold district. (C) 2016 Elsevier B.V. All rights reserved.

This paper demonstrates a methodology for the automatic joint interpretation of high resolution airborne geophysical and space-borne remote sensing data to support geological mapping in a largely automated, fast and objective manner. At the request of the Geological Survey of Namibia (GSN), part of the Gordonia Subprovince of the Namaqua Metamorphic Belt situated in southern Namibia was selected for this study.All data - covering an area of 120 km by 100 km in size - were gridded, with a spacing of adjacent data points of only 200 m. The data points were coincident for all data sets. Published criteria were used to characterize the airborne magnetic data and to establish a set of attributes suitable for the recognition of linear features and their pattern within the study area. This multi-attribute analysis of the airborne magnetic data provided the magnetic lineament pattern of the study area.To obtain a (pseudo-) lithology map of the area, the high resolution airborne gamma-ray data were integrated with selected Landsat band data using unsupervised fuzzy partitioning clustering. The outcome of this unsupervised clustering is a classified (zonal) map which in terms of the power of spatial resolution is superior to any regional geological mapping. The classified zones are then assigned geological/geophysical parameters and attributes known from the study area, e.g. lithology, physical rock properties, age, chemical composition, geophysical field characteristics, etc. This information is obtained from the examination of archived geological reports, borehole logs, any kind of existing geological/geophysical data and maps as well as ground truth controls where deemed necessary. To obtain a confidence measure validating the unsupervised fuzzy clustering results and receive a quality criterion of the classified zones, stepwise linear discriminant analysis was chosen. Only a small percentage (8%) of the samples was misclassified by discriminant analysis when compared to the result obtained from unsupervised fuzzy clustering. Furthermore, a comparison of the aposterior probability of class assignment with the trustworthiness values provided by fuzzy clustering also indicates only slight differences. These observed differences can be explained by the exponential class probability term which tends to deliver either fairly high or low probability values.The methodology and results presented here demonstrate that automated objective pattern recognition can essentially contribute to geological mapping of large study areas and mineral exploration target generation. This methodology is considered well suited to a number of African countries whose large territories have recently been covered by high resolution airborne geophysical data, but where existing geological mapping is poor, incomplete or outdated. (C) 2015 Elsevier Ltd. All rights reserved.

Hendrik Paasche1,10, Detlef Eberle2, Sonali Das3, Antony Cooper3, Pravesh Debba3, Peter Dietrich1, Nontembeko DudeniThlone3, Cornelia Gläßer4, Andrzej Kijko5, Andreas Knobloch6, Angela Lausch7, Uwe Meyer8, Ansie Smit5, Edgar Stettler9, Ulrike Werban1 1 UFZ Helmholtz Centre for Environmental Research, Department of Monitoring and Exploration Technologies, Permoserstr. 15, 04318 Leipzig, Germany 2 Council for Geoscience, Geophysics Unit, Private Bag X112, Pretoria 0001, South Africa; now: geotec Rohstoffe GmbH, Friedrichstr. 95, 10117 Berlin, Germany 3 Council for Scientific and Industrial Research (CSIR), Built Environment, Spatial Planning and Systems, P.O. Box 395, Pretoria 0001, South Africa 4 Martin-Luther University Halle-Wittenberg, Institute of Geoscience and Geography, von-Seckendorff-Platz 4, 06120 Halle, Germany 5 University of Pretoria Natural Hazard Centre, Africa, Private Bag X20, Hatfield 0028, Pretoria, South Africa 6 Beak Consultants GmbH, Am St. Niclas Schacht 13, 09599 Freiberg, Germany 7 UFZ Helmholtz Centre for Environmental Research, Department of Landscape Ecology, Permoserstr. 15, 04318 Leipzig, Germany 8 Federal Institute for Geosciences and Natural Resources, Geophysical Exploration and Technical Mineralogy, Stilleweg 2, 30655 Hannover, Germany 9 Afrika Gold AG, Firststr. 15, 8835 Feusisberg, Switzerland; University of the Witwatersrand, School of Geoscience, Private Bag 3, Wits 2050, Johannesburg, South Africa

(2013). Unsupervised soft clustering of high resolution airborne geophysical and satellite data suites from the Sperrgebiet, Karas region, Southern Namibia, to enhance lithology mapping. ASEG Extended Abstracts: Vol. 2013, ASEG2013 - 23rd Geophysical Conference, pp. 1-5.

This article reflects discussions German and South African Earth scientists, statisticians and risk analysts had on occasion of two bilateral workshops on Data Integration Technologies for Earth System Modelling and Resource Management. The workshops were held in October 2012 at Leipzig, Germany, and April 2013 at Pretoria, South Africa, and were attended by about 70 researchers, practitioners and data managers of both countries. Both events were arranged as part of the South African-German Year of Science 2012/2013. The South African National Research Foundation (NRF, UID 81579) has supported the two workshops as part of the South African–German Year of Science activities 2012/2013 established by the German Federal Ministry of Education and Research and the South African Department of Science and Technology.

The National Geology Directorate of Mozambique (DNG) and Maputo-based Eduardo-Mondlane University (UEM) entered a joint venture with the South African Council for Geoscience (CGS) to conduct a case study over the meso-Proterozoic Alto Ligonha pegmatite field in the Zambezia Province of northeastern Mozambique to support the local exploration and mining sectors. Rare-metal minerals, i.e. tantalum and niobium, as well as rare-earth minerals have been mined in the Alto Ligonha pegmatite field since decades, but due to the civil war (1977-1992) production nearly ceased. The Government now strives to promote mining in the region as contribution to poverty alleviation. This study was undertaken to facilitate the extraction of geological information from the high resolution airborne magnetic and radiometric data sets recently acquired through a World Bank funded survey and mapping project. The aim was to generate a value-added map from the airborne geophysical data that is easier to read and use by the exploration and mining industries than mere airborne geophysical grid data or maps. As a first step towards clustering, thorium (Th) and potassium (K) concentrations were determined from the airborne geophysical data as well as apparent magnetic susceptibility and first vertical magnetic gradient data. These four datasets were projected onto a 100 m spaced regular grid to assemble 850,000 four-element (multivariate) sample vectors over the study area. Classification of the sample vectors using crisp clustering based upon the Euclidian distance between sample and class centre provided a (pseudo-) geology map or value-added map, respectively, displaying the spatial distribution of six different classes in the study area. To learn the quality of sample allocation, the degree of membership of each sample vector was determined using a-posterior discriminant analysis. Geophysical ground truth control was essential to allocate geology/geophysical attributes to the six classes. The highest probability to meet pegmatite bodies is in close vicinity to (magnetic) amphibole schist occurring in areas where depletion of potassium as indication of metasomatic processes is evident from the airborne radiometric data. Clustering has proven to be a fast and effective method to compile value-added maps from multivariate geophysical datasets. Experience made in the Alto Ligonha pegmatite field encourages adopting this new methodology for mapping other parts of the Mozambique Fold Belt. (C) 2011 Elsevier Ltd. All rights reserved.

Partitioning cluster algorithms have proven to be powerful tools for data-driven integration of large geoscientific databases. We used fuzzy Gustafson-Kessel cluster analysis to integrate Landsat imagery, airborne radiometric, and regional geochemical data to aid in the interpretation of a multimethod database. The survey area extends over [Formula: see text] and is located in the Northern Cape Province, South Africa. We carefully selected five variables for cluster analysis to avoid the clustering results being dominated by spatially high-correlated data sets that were present in our database. Unlike other, more popular cluster algorithms, such as k-means or fuzzy c-means, the Gustafson-Kessel algorithm requires no preclustering data processing, such as scaling or adjustment of histographic data distributions. The outcome of cluster analysis was a classified map that delineates prominent near-to-surface structures. To add value to the classified map, we compared the detected structures to mapped geology and additional geophysical ground-truthing data. We were able to associate the structures detected by cluster analysis to geophysical and geological information thus obtaining a pseudolithology map. The latter outlined an area with increased mineral potential where manganese mineralization, i.e., psilomelane, had been located.

The fuzzy partitioning Gustafson-Kessel cluster algorithm is employed for rapid and objective integration of multi-parameter Earth-science related databases. We begin by evaluating the Gustafson-Kessel algorithm using the example of a synthetic study and compare the results to those obtained from the more widely employed fuzzy c-means algorithm. Since the Gustafson-Kessel algorithm goes beyond the potential of the fuzzy c-means algorithm by adapting the shape of the clusters to be detected and enabling a manual control of the cluster volume, we believe the results obtained from Gustafson-Kessel algorithm to be superior. Accordingly, a field database comprising airborne and ground-based geophysical data sets is analysed, which has previously been classified by means of the fuzzy c-means algorithm. This database is integrated using the Gustafson-Kessel algorithm thus minimising the amount of empirical data processing required before and after fuzzy c-means clustering. The resultant zonal geophysical map is more evenly clustered matching regional geology information available from the survey area. Even additional information about linear structures, e. g. as typically caused by the presence of dolerite dykes or faults, is visible in the zonal map obtained from Gustafson-Kessel cluster analysis.

Major parts of Mozambique were flown a few years ago to acquire high resolution magnetic and radiometric data. The National Geology Directorate of Mozambique intends to interpret these data generating value-added maps that are easier to handle by the exploration and mining industries than mere airborne geophysical data and maps. The National Geology Directorate of Mozambique and the Council for Geoscience have joined to conduct an example study case in the Alto Ligonha pegmatite fields, northern Mozambique. A valueadded map of the area was generated using crisp exploratory K-means clustering. Subsequent aposterior discriminant analysis served to establish the trustworthiness of the classification. The map is the result of grouping 850,000 four-element samples (Th- and K-surface concentrations, apparent magnetic susceptibility and the first vertical magnetic gradient) into a number of classes. These were associated with the major geology units known from the study area. Focus has been on amphibolitic magnetic gneisses which host mineralized pegmatites in many cases. The area covered by this kind of gneiss is clearly enhanced by our classification map expanding the area with increased potential of mineralised pegmatites. These results were confirmed on site. Ground truth control served to verify the role of amphibolites as geophysical marker, inspect the areas newly classified as having increased potential of mineralized pegmatites and try to locate occurrences not contained by the records of the Mozambique Geology Directorate. The automated integration of airborne geophysical data using well known K-means algorithm proved to be a fast, objective and effective tool to generate a value-added integrated map. The experience made in the Alto Ligonha pegmatite fields encourages the adoption of this methodology over other parts of the Mozambique Fold Belt.

Major parts of Mozambique were recently flown to acquire high resolution airborne magnetic and radiometric data. Since then it has been the intent of the National Geology Directorate of Mozambique (DNG) to interpret these data generating value-added maps that are easier to use by the exploration and mining industries than mere airborne geophysical grid data and maps. DNG and Maputo-based Eduardo-Mondlane University (UEM) entered a joint venture with the South African Council for Geoscience (CGS) to conduct a case study over the meso-Proterozoic Alto Ligonha pegmatite province in northern Mozambique to support the regional mining sector. Integration of the airborne geophysical data was achieved using the K-means algorithm for explorative unsupervised crisp clustering of the airborne geophysical data. Discriminant analysis was then used to obtain the degree of class membership of each sample previously classified by K-means. Prior to clustering, Th- and K-surface concentrations as well as apparent magnetic susceptibility and first vertical derivative data of the total magnetic intensity anomalies were determined to project a 100 m-spaced grid comprising 850,000 multivariate sample vectors on the study area. Compilation of the classification results provided the value-added map illustrating that the probability to meet pegmatite bodies is highest where amphibole gneiss occurs. The automated integration of airborne geophysical data using the K-means algorithm is a fast, objective and efficient method to compile value-added maps. The experience made in the Alto Ligonha pegmatite province encourages the adoption of this new methodology over other parts of the Mozambique Fold Belt, becoming integral part of geological mapping ongoing in the country.

The Council for Geoscience, South Africa, has embarked on a program of flying the country with high resolution - high density airborne magnetic and radiometric data to generate new exploration targets. It was during the seventies and the eighties of the past century when the existing regional coverage was flown with flight lines 1000 m apart at a nominal flight height of 120 m a.g.l. This kind of first generation data is not any longer satisfying the requirements of highest possible spatial resolution set up by the exploration and environmental industries. This demand was recently acknowledged by the South African Government and has been materialized by launching a new high resolution airborne survey program with 200 m line spacing and nominal flight height of 80 m a.g.l.

Unsupervised classification techniques, such as cluster algorithms, are routinely used for structural exploration and integration of multiple frequency bands of remotely sensed spectral datasets. However, up to now, very few attempts have been made towards using unsupervised classification techniques for rapid, automated, and objective information extraction from large airborne geophysical data suites. We employ fuzzy c-means (FCM) cluster analysis for the rapid and largely automated integration of complementary geophysical datasets comprising airborne radiometric and magnetic as well as ground-based gravity data, covering a survey area of approximately 5000 km(2) located 100 km east-south-east of Johannesburg, South Africa, along the south-eastern limb of the Bushveld layered mafic intrusion complex. After preparatory data processing and normalisation, the three datasets are subjected to FCM cluster analysis, resulting in the generation of a zoned integrated geophysical map delineating distinct subsurface units based on the information the three input datasets carry. The fuzzy concept of the cluster algorithm employed also provides information about the significance of the identified zonation. According to the nature of the input datasets, the integrated zoned map carries information from near-surface depositions as well as rocks underneath the sediment cover. To establish a sound geological association of these zones we refer the zoned geophysical map to all available geological information, demonstrating that the zoned geophysical map as obtained from FCM cluster analysis outlines geological units that are related to Bushveld-type, other Proterozoic- and Karoo-aged rocks.

In the workflow of airborne gamma-ray spectrometry processing, background correction is the most substantial component. The major part of this correction requires knowing the contribution of atmospheric 222Rn and its daughter products within airborne recorded spectra. To evaluate the atmospheric Rn component, specific calibration flights are needed. Two types of techniques are commonly used: i) upward looking detector technique, ii) spectral ratio technique. For both, the issue lies first in the ability to get the spectra of atmospheric radon and the spectra of uranium from ground. This ability is strongly dependent on local conditions. Two local conditions have to be satisfied: (i) presence in the vicinity of the survey of a wide water surface, (ii) presence of high radon content in the air during calibration flights. BRGM, the French Geological survey, has designed, quality controlled and processed a wide variety of surveys. The experience gained assisted in the monitor atmospheric Rn spectra depending on local condition. Examples from BRGM experience in Tropical forest and temperate climate zones are presented. Constraints and limitations of atmospheric background correction techniques are debated.

Major parts of Mocambique were flown a few years ago to acquire high resolution magnetic and radiometric data. It has been since then the intent of the National Geology Directorate of Moçambique to interpret these data generating value-added maps that are easier to use by the exploration and mining industries than mere airborne geophysical grid data and maps. The National Geology Directorate of Moçambique and the Council for Geoscience have joined with the financial support of the National Research Foundation of South Africa to conduct an example study case in the Alto de Ligonha pegmatite fields, northern Moçambique, with a special view to support the small scale-mining sector of the region. Analysis of the airborne geophysical, satellite imagery and geology data, in combination with ground geophysical data acquired over specific mineral showings, reveals that the occurrence of pegmatites is mostly confined to amphibolitic gneiss, which is part of the meso-Proterozoic Namama Thrust Belt. Generation of the respective value-added map was achieved using crisp exploratory K-means clustering of the airborne geophysical data. The map is the result of clustering 850,000 four-element samples (Th- and K-surface concentration, apparent magnetic susceptibility and the vertical magnetic gradient) into a number of classes. It clearly enhances the outcrop area of the amphibolitic gneiss where the occurrence of mineralised pegmatites is the most probable. The automated integration of airborne geophysical data using the well known K-means algorithm proved to be a fast, objective and effective tool to generate a value-added integrated map. The experience made in the Alto de Ligonha pegmatite fields encourages the adoption of this methodology over other parts of the Moçambique Fold Belt. This makes it an integral part of geological mapping ongoing in the country.

The earthquake and the resulting tsunami on December 26, 2004, damaged the freshwater supply system in the coastal areas of northern Sumatra. In response to this natural disaster, the German-Indonesian HELicopter Project ACEH was initiated to assist the Indonesian government in its effort to plan and realize a sustainable reconstruction of community infrastructure by providing geophysical and hydrogeological data to serve as a basis for spatial planning. After two successful airborne geophysical surveys funded by the Federal Institute for Geosciences and Natural Resources of Germany, conducted on the north coast near the city of Banda Aceh and along the west coast between the towns of Calang and Meulaboh, Coca-Cola Foundation Indonesia funded an additional survey on the northeast coast around the town of Sigli. Helicopter-borne electromagnetics (HEM) revealed shallow freshwater resources up to several kilometers inland. Along the coast, however, the investigation depth of the HEM system was constrained due to near-surface saltwater. Here, ground-based transient electromagnetics was utilized on several profiles close to the town of Sigli, revealing deep coastal freshwater resources. The combination of airborne and ground-based electromagnetic techniques has proven to be highly effective to estimate the freshwater potential of the Sigli marshlands. Numerous sites for planned water wells could be identified as promising freshwater sources and approximate drilling depths provided.