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1.
Vesa Nykänen 《Natural Resources Research》2008,17(1):29-48
Among the more popular spatial modeling techniques, artificial neural networks (ANN) are tools that can deal with non-linear
relationships, can classify unknown data into categories by using known examples for training, and can deal with uncertainty;
characteristics that provide new possibilities for data exploration. Radial basis functional link nets (RBFLN), a form of
ANN, are applied to generate a series of prospectivity maps for orogenic gold deposits within the Paleoproterozoic Central
Lapland Greenstone Belt, Northern Fennoscandian Shield, Finland, which is considered highly prospective yet clearly under
explored. The supervised RBFLN performs better than previously applied statistical weights-of-evidence or conceptual fuzzy
logic methods, and equal to logistic regression method, when applied to the same geophysical and geochemical data layers that
are proxies for conceptual geological controls. By weighting the training feature vectors in terms of the size of the gold
deposits, the classification of the neural network results provides an improved prediction of the distribution of the more
important deposits/occurrences. Thus, ANN, more specifically RBFLN, potentially provide a better tool to other methodologies
in the development of prospectivity maps for mineral deposits, hence aiding conceptual exploration. 相似文献
2.
Harris J. R. Wilkinson L. Heather K. Fumerton S. Bernier M. A. Ayer J. Dahn R. 《Natural Resources Research》2001,10(2):91-124
A Geographic Information System (GIS) is used to prepare and process digital geoscience data in a variety of ways for producing gold prospectivity maps of the Swayze greenstone belt, Ontario, Canada. Data used to produce these maps include geologic, geochemical, geophysical, and remotely sensed (Landsat). A number of modeling methods are used and are grouped into data-driven (weights of evidence, logistic regression) and knowledge-driven (index and Boolean overlay) methods. The weights of evidence (WofE) technique compares the spatial association of known gold prospects with various indicators (evidence maps) of gold mineralization, to derive a set of weights used to produce the final gold prospectivity map. Logistic regression derives statistical information from evidence maps over each known gold prospect and the coefficients derived from regression analysis are used to weight each evidence map. The gold prospectivity map produced from the index overlay process uses a weighting scheme that is derived from input by the geologist, whereas the Boolean method uses equally weighted binary evidence maps.The resultant gold prospectivity maps are somewhat different in this study as the data comprising the evidence maps were processed purposely differently for each modeling method. Several areas of high gold potential, some of which are coincident with known gold prospects, are evident on the gold prospectivity maps produced using all modeling methods. The majority of these occur in mafic rocks within high strain zones, which is typical of many Archean greenstone belts. 相似文献
3.
Posterior probabilities of occurrence for Zn-Pb Mississippi Valley Type (MVT) mineralization were calculated based on evidence
maps derived from regional geology, Landsat-TM, RADARSAT-1, a digital elevation model and aeromagnetic data sets in the Borden
Basin of northern Baffin Island, Canada. The vector representation of geological contacts and fault traces were refined according
to their characteristics identified in Landsat-TM, RADARSAT-1, DEM, slope, aspect, and shaded relief data layers. Within the
study area, there is an association between the occurrence of MVT mineralization and proximity to the contact of platformal
carbonates and shale units of the adjacent geological formation. A spatial association also tends to exist between mineralization
and proximity to E-W and NW-SE trending faults. The relationships of known MVT occurrences with the geological features were
investigated by spatial statistical techniques to generate evidence maps. Supervised classification and filtering were applied
to Landsat-TM data to divide the Society Cliffs Formation into major stratigraphic subunits. Because iron oxides have been
observed at some of the MVT occurrences within the Borden Basin, Landsat-TM data band ratio (3/1) was calculated to highlight
the potential presence of iron-oxides as another evidence map. Processed Landsat-TM data and other derived geological evidence
maps provided useful indicators for identifying areas of potential MVT mineralization.
Weights of evidence and logistic regression were used independently to integrate and generate posterior probability maps showing
areas of potential mineralization based on all derived evidence maps. Results indicate that in spite of the lack of important
data sets such as stream or lake sediment geochemistry, Landsat-TM data and regional geological data can be useful for MVT
mineral-potential mapping. 相似文献