Predicting gold-rich epithermal and porphyry systems in the central Andes with a continental-scale metallogenic GIS

Billa, Mario; Cassard, Daniel; Lips, Andor L.W.; Bouchot, Vincent; Tourlière, Bruno; Stein, G.; Guillou-Frottier, Laurent

doi:10.1016/j.oregeorev.2004.01.002

Cited by 50 publications

(24 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Each of the continuous-value fuzzy evidence maps created in this paper can also be used in multi-index overlay modeling (e.g., Bonham-Carter, 1994;Harris et al, 2001;Chico-Olmo et al, 2002;De Araújo and Macedo, 2002;Billa et al, 2004). In all of these methods, continuous evidential scores of distances in each proximity value of evidential features can be derived directly using a suitable logistic function even without using the locations of known mineral deposit occurrences as in traditional data-driven MPM approaches and even without discretization of evidential values into some arbitrary classes and assigning weights to classes based on an analyst's expert opinion as in traditional knowledgedriven MPM approaches.…”

Section: Discussionmentioning

confidence: 99%

Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping

Yousefi

Carranza

2015

Computers & Geosciences

165

View full text Add to dashboard Cite

Section: Discussionmentioning

confidence: 99%

Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping

Yousefi

Carranza

2015

Computers & Geosciences

165

View full text Add to dashboard Cite

“…Multi-class index overlay is traditionally applied to knowledge-driven MPM (Bonham-Carter 1994;Chico-Olmo et al 2002;Billa et al 2004;Carranza 2008b) whereby evidential maps are categorized into some arbitrary classes, and are then integrated considering weights subjectively assigned to each evidential map. Each of the jth classes of the ith evidential map is assigned a score S ij according to their relative importance.…”

Section: Data-driven Multi-index Overlaymentioning

confidence: 99%

Data-Driven Index Overlay and Boolean Logic Mineral Prospectivity Modeling in Greenfields Exploration

2015

View full text Add to dashboard Cite

Index overlay and Boolean logic are two techniques customarily applied for knowledgedriven modeling of prospectivity for mineral deposits, whereby weights of values in evidential maps and weights of every evidence map are assigned based on expert opinion. In the Boolean logic technique for mineral prospectivity modeling (MPM), threshold evidential values for creating binary maps are defined based on expert opinion as well. This practice of assigning weights based on expert opinion involves trial-and-error and introduces bias in evaluating relative importance of both evidential values and individual evidential maps. In this paper, we propose a data-driven index overlay MPM technique whereby weights of individual evidential maps are derived from data. We also propose a data-driven Boolean logic MPM technique, whereby thresholds for creating binary maps are defined based on data. For assigning weights and defining thresholds in these proposed data-driven MPM techniques, we applied a prediction-area plot from which we can estimate the predictive ability of each evidential map with respect to known mineral occurrences, and we use that predictive ability estimate to assign weights to evidential map and to select thresholds for generating binary predictor maps. To demonstrate these procedures, we applied them to an area in the Kerman province in southeast Iran as a MPM case study for porphyry-Cu deposits.

show abstract

“…2B). Though this approach allows to define rigorously and objectively quantitative index assigned to qualitative spatially-distributed controlling factors, the key aspect resides in ensuring that the inventory of the collected data (number of underground structures, number of ground disturbances) is representative as outlined in Billa et al (2004).…”

Section: Managing Expert Uncertainty (Step 3)mentioning

confidence: 99%

Managing expert-information uncertainties for assessing collapse susceptibility of abandoned underground structures

Nachbaur¹,

Rohmer²

2011

Engineering Geology

View full text Add to dashboard Cite

Assessing the collapse susceptibility of abandoned cavities at a regional scale is associated with large uncertainties that are mainly related to the very nature of the phenomena, but also to the difficulty in collecting exhaustive information at such a scale on often "forgotten" structures. In this context, the expert's role is essential, because he is able to synthesize the information resulting from the inventory and from the commonly imprecise, if not vague, criteria on the basis of his experience and his knowledge of the regional geological and historical and economic context. In this article, we propose mathematical tools for representing and processing this information in order to give flexibility to this step and manage the uncertainty inherent in the expert's information. The first tool, based on the weight of evidence theory, is for managing the uncertainty due to the heterogeneous spatial distribution of the data, whereas the second tool, based on the fuzzy set theory, is for managing the imprecision and incompleteness of available data, which hinder the definition of the class boundaries of the quantitative decision criteria. Based on an appropriate representation of the uncertainty sources (related to the input data and to the expert diagnostic), we then propose a methodology that integrates the uncertainty in the final output of the collapse susceptibility assessment and provides a confidence indicator useful within the decision-making process. The proposed methodology is applied to the Arras territory in the North of France, where abandoned chalk pits (dating back to the Roman ages) and war saps (i.e. covered trenches) located in the vicinity of the First World War front lines both raise difficulties for urban planning

show abstract

Predicting gold-rich epithermal and porphyry systems in the central Andes with a continental-scale metallogenic GIS

Cited by 50 publications

References 43 publications

Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping

Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping

Data-Driven Index Overlay and Boolean Logic Mineral Prospectivity Modeling in Greenfields Exploration

Managing expert-information uncertainties for assessing collapse susceptibility of abandoned underground structures

Contact Info

Product

Resources

About