Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/27469

Title: High resolution geochemical mapping in the Mociços mine (Ossa-Morena Zone, Portugal). Contributes from machine learning methods
Authors: NOGUEIRA, Pedro
VICENTE, Sandro
MAIA, Miguel
ROSEIRO, José
MATOS, João X.
Editors: NOGUEIRA, Pedro
MOREIRA, Noel
ROSEIRO, José
MAIA, Miguel
Keywords: Zona de Ossa-Morena
Geoquímica
Mociços
Cobre
Portable X-Ray Fluorescense
Issue Date: 2019
Publisher: Universidade de Évora
Citation: NOGUEIRA, P., VICENTE, S., MAIA, M., ROSEIRO, J., MATOS, J.X. (2019). High resolution geochemical mapping in the Mociços mine (Ossa-Morena Zone, Portugal). Contributes from machine learning methods. Congresso Ibérico de Geoquímica & XX Semana da Geoquímica, Évora, 251-254.
Abstract: The Mociços mine was exploited for copper in the early twentieth century. A recent soil geochemistry campaign with portable X-ray fluorescence equipment permited to map the surroundings of this ancient mine with high resolution. The analysis of the results using machine learning methods, namely, principal component analysis, hierarchical and k-mean clustering, and the mapping of the observations, allows a better understanding of the geochemical behavior of the elements. The principal component analysis and the k-means method have comparable results and allow to define the zone of mineralization and the outcropping of a dyke of acid rocks. The hierarchical agglomeration method allows to group the mineralized zones with the mine waste sites. Using the spatial mapping of the clusters it was possible to identify the regions marked by the geochemical behaviour of copper and zinc as well as to find relationships between the mineralized vein and outcropping acid rocks in the region.
URI: http://hdl.handle.net/10174/27469
Type: article
Appears in Collections:GEO - Artigos em Livros de Actas/Proceedings

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