Computer vision-based framework for extracting tectonic lineaments from optical remote sensing data

Abstract: The extraction of tectonic lineaments from digital satellite data is a fundamental application in remote sensing. The location of tectonic lineaments such as faults and dykes are of interest for a range of applications, particularly because of their association with hydrothermal mineralization. Although a wide range of applications have utilized computer vision techniques, a … Read more…

Modeling geochemical anomalies of stream sediment data through a weighted drainage catchment basin method for detecting porphyry Cu-Au mineralization

Abstract: Stream sediment surveying is a geochemical sampling method which is typically applied in the preliminary stages of mineral prospecting. Both continuous and discrete mapping approaches have been proposed to delineate geochemical anomalies at large scales using stream sediment samples. We aim to enhance the efficiency of a recent discrete mapping method called Weighted Drainage … Read more…

GPlates 2.2 software and data sets

GPlates Title Logo

GPlates 1.5 PromoGPlates is a free desktop software for the interactive visualisation of plate-tectonics. The compilation and documentation of GPlates 2.2 data was primarily funded by AuScope National Collaborative Research Infrastructure (NCRIS).

GPlates is developed by an international team of scientists and professional software developers at the EarthByte Project (part of AuScope) at the University of Sydney, the Division of Geological and Planetary Sciences (GPS) at CalTech, the Geodynamics team at the Geological Survey of Norway (NGU) and the Centre for Earth Evolution and Dynamics (CEED) at the University of Oslo. … Read more…

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GPlates 2.1 software and data sets

GPlates Title Logo

GPlates 1.5 PromoGPlates is a free desktop software for the interactive visualisation of plate-tectonics. The compilation and documentation of GPlates 2.1 data was primarily funded by AuScope National Collaborative Research Infrastructure (NCRIS).

GPlates is developed by an international team of scientists and professional software developers at the EarthByte Project (part of AuScope) at the University of Sydney, the Division of Geological and Planetary Sciences (GPS) at CalTech, the Geodynamics team at the Geological Survey of Norway (NGU) and the Centre for Earth Evolution and Dynamics (CEED) at the University of Oslo. … Read more…

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GPlates 2.0 software and data sets

GPlates 1.5 PromoGPlates is a free desktop software for the interactive visualisation of plate-tectonics. The compilation and documentation of GPlates 2.0 data was primarily funded by AuScope National Collaborative Research Infrastructure (NCRIS).

GPlates is developed by an international team of scientists and professional software developers at the EarthByte Project (part of AuScope) at the University of Sydney, the Division of Geological and Planetary Sciences (GPS) at CalTech, the Geodynamics team at the Geological Survey of Norway (NGU) and the Centre for Earth Evolution and Dynamics (CEED) at the University of Oslo.  … Read more…

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Prospectivity of Western Australian iron ore from geophysical data using a reject option classifier

Prospectivity of Western Australian iron ore from geophysical data using a reject option classifier - figure

Prospectivity of Western Australian iron ore from geophysical data using a reject option classifier - figureCitation
Merdith, A. S., Landgrebe, T. C., & Müller, R. D. (2015). Prospectivity of Western Australian iron ore from geophysical data using a reject option classifier. Ore Geology Reviews. http://dx.doi.org/10.1016/j.oregeorev.2015.03.014

Abstract
There has recently been a rapid growth in the amount and quality of digital geological and geophysical data for the majority of the Australian continent. Coupled with an increase in computational power and the rising impor- tance of computational methods, there are new possibilities for a large scale, low expenditure digital exploration of mineral deposits. Here we use a multivariate analysis of geophysical datasets to develop a methodology that utilises machine learning algorithms to build and train two-class classifiers for provincial-scale, greenfield min- eral exploration. … Read more…

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From data mining to opal mining

Opal NobbyDocuments
AJES Paper
CG Paper

Opal is Australia’s national gemstone, however most significant opal discoveries were made in the early 1900’s – more than 100 years ago – until recently. Currently there is no formal exploration model for opal, meaning there are no widely accepted concepts or methodologies available to suggest where new opal fields may be found. … Read more…

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