Understanding magma plumbing systems hinges upon an intricate comprehension of crystal populations concerning size, chemistry, and origin. We introduce an innovative, yet elegantly simple approach—the ‘number–length of crystals (N-LoC) multifractal model’—to classify crystal sizes, unveiling compelling insights into their distribution dynamics. This model, a departure from conventional crystal size distribution (CSD) diagrams, reveals multifractal patterns indicative of distinct class sizes within igneous rock crystals. By synthesizing multiple samples from experimental studies, natural occurrences, and numerical models, we validate this method’s efficacy. Our bi-logarithmic N-LoC diagrams for cooling-driven crystallized samples transcend the confines of traditional CSD plots, identifying variable thresholds linked to cooling rates and quenching temperatures. These thresholds hint at pulsative nucleation and size-dependent growth events, offering glimpses into crystallization regimes and post-growth modifications like coalescence and coarsening. Examining multifractal log–log plots across time-series samples unravels crystallization histories during cooling or decompression. Notably, microlites within volcano conduits delineate thresholds influenced by decompression rate and style, mirroring nucleation and growth dynamics observed in experimental studies. Our fractal methodology, presenting a more direct approach with fewer assumptions than the classic CSD method, stands poised as a potent alternative or complementary tool. We delve into its potential, facilitating comparisons between eruptive styles in volcanoes while deliberating on inherent limitations. This work not only advances crystal size analysis methodologies but also holds promise for inferring nuanced volcanic processes and offers a streamlined avenue for crystal size evaluation in igneous rocks.
The irregular and sporadic occurrence of chromite pods in podiform chromite deposits (PCD), especially in mountainous terranes with rough topography, necessitates finding innovative methods for reconnaissance and prospecting. This research combines several remote sensing methods to discriminate the highly serpentinized peridotites hosting chromite pods from the other barren ultramafic and mafic cumulates. The case study is the area of the Sabzevar Ophiolite (NE Iran), which hosts several known chromite and other mineral deposits. The integration of satellite images [e.g., Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite sensor, Landsat series, and Sentinel-2] coupled with change detection, band rationing, and target detection algorithms [including the Spectral Angle Mapper (SAM)] were used to distinguish potential lithological units hosting chromites. Results have been verified by an initial on-field checking and compared with the high-resolution (GSD ~6 cm) orthomosaic images obtained by the processing of photographs taken from an Unmanned Aerial Vehicle (UAV) at a promising area of 35 km2. The combination of visual interpretation and supervised classification by machine learning methods [Support Vector Machine (SVM)] yielded the production of a geological map, in which the lithological units and structures are outlined, including the crust-mantle transition zone units, mafic cumulates, crosscutting dykes, and mantle sequences. The validation of the results was performed through a second phase, made up of field mapping, sampling, chemical analysis, and microscopic studies, leading to the discovery of new chromite occurrences and mineralized zones. All ultramafic units were classified into four groups based on the degree of serpentinization, represented by the intensity of their average spectral reflectance. Based on their presumed protolith, the highly serpentinized ultramafics and serpentinites were classified into two main categories (dunite or harzburgite). The serpentinite with probable dunitic protolith, discriminated for a peculiar Fe-rich Ni-bearing lateritic crust, is more productive for chromite prospecting. This is particularly true at the contact with mafic dykes, akin to some worldwide chromite deposits. The results of our work highlight the potential of multi-scale satellite and UAV-based remote sensing to find footprints of some chromite mineral deposits.
Understanding magma plumbing systems hinges upon an intricate comprehension of crystal populations concerning size, chemistry, and origin. We introduce an innovative, yet elegantly simple, approach—the 'number-length of crystals (N-LoC) multifractal model'—to classify crystal sizes, unveiling compelling insights into their distribution dynamics. This model, a departure from conventional crystal size distribution (CSD) diagrams, reveals multifractal patterns indicative of distinct class sizes within igneous rock crystals. By synthesizing multiple samples from experimental studies, natural occurrences, and numerical models, we validate this method's efficacy. Our bi-logarithmic N-LoC diagrams for cooling-driven crystallized samples transcend the confines of traditional CSD plots, identifying variable thresholds linked to cooling rates and quenching temperatures. These thresholds hint at pulsative nucleation and size-dependent growth events, offering glimpses into crystallization regimes and post-growth modifications like coalescence and coarsening. Examining multifractal log-log plots across time-series samples unravels crystallization histories during cooling or decompression. Notably, microlites within volcano conduits delineate thresholds influenced by decompression rate and style, mirroring nucleation and growth dynamics observed in experimental studies. Our fractal methodology, presenting a more direct approach with fewer assumptions than the classic CSD method, stands poised as a potent alternative or complementary tool. We delve into its potential, facilitating comparisons between eruptive styles in volcanoes while deliberating on inherent limitations. This work not only advances crystal size analysis methodologies but also holds promise for inferring nuanced volcanic processes and offers a streamlined avenue for crystal size evaluation in igneous rocks.
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