I González-Álvarez1,2, T Albrecht3, J Klump1, S Pernreiter4, K Heilbronn5, T Ibrahimi1
1CSIRO, Mineral Resources, Discovery Program, Perth, Australia; 2University of Western Australia, Centre for Exploration Targeting, Perth, Australia; 3Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, Australia; 4Institute of Geology, University of Innsbruck, Innsbruck, Austria; 5Geosciences, College of Science and Engineering, James Cook University, Townsville, Australia
Landscapes contain essential information related to the geochemical footprint of ore deposits at depth. Variable surface topographical features can be grouped to define and classify unique landscape domains. Climatic conditions, tectonic activity, geological features, biological activity, and sedimentary dynamics are fundamentally linked to landscape variability. Consequently, the study of landscapes can reveal the link between surface features and geological processes at depth. Ore deposits and mineral systems can have dispersed or enhanced geochemical footprints, depending on how the landscape evolved. Geochemical dispersion halos penetrating through cover can be detected by selecting suitable landscape regimes and appropriate sampling media. Cataloguing landscape variability and understanding their evolution at a regional scale can be challenging. The primary difficulty is associated with the selection of the geographic extension of surficial features. In the past, landscape variability mapping relied on field observations along transects. However, a constraint on this approach lies in the uncertainty related to the extrapolation of field observations, especially when attempting to extrapolate them to regional scales. Such extrapolation can be unreliable due to the complexity and variability of landforms, the paucity of data availability, and the difficulty in defining quantitative criteria that discriminate diverse landscape types. Modern data analytics technology and advanced satellite data provide access to large data sets that can assist in characterizing landscape features and their distribution at regional scales. The ability to accurately map landscape variability domains may reveal a vector that links the geochemistry and geology at depth with the architecture of the cover. Such an approach will result in more efficient means to detect and constrain geochemical footprints and dispersion processes at large scales.
Ignacio is currently Principal Geochemist at CSIRO in Perth. Ignacio worked in Industry in Europe and Australia, and in Academia.
At present, Ignacio’s leading research is focussed on various aspects of landscape evolution and sedimentary systems, weathering processes, chemical element mobility in the continents, and mineral exploration.