Remote Sensing Analysis of Mineralized Alteration in the Ramand Area (Qazvin Province)
Bibliographic record
Abstract
Introduction The Ramand area, southwest of Buin- Zahra, about 60 kilometers from Qazvin, lies in the igneous belt of the Urmieh-Dokhtar region, the main structural zone of north-central Iran. Rhyodacite and rhyolite lava flows are the principal host rocks of mineralization and alteration of the area, most of which occurs in faulted and brecciated zones alongmaj or northwest-trending fault systems (such as Kour-Cheshmeh, Hassan Abad and their branches). Clay minerals determined from satellite images indicated principally argillic hydrothermal alteration before laboratory mineralogical analysis. According to instrumental analyses, mineralized alteration with greater amounts of argillic halos and lesser amounts of sericitic-propylitic minerals contains quartz veinlets in the vertical and lateral sections. Initially, alteration in the Ramand area was revealed in ETM images by using the SPCA technique of Crosta and Moore, 1990 (Selective Principle Component Analysis). Compared with other techniques, SPCA results have reliable spectral signatures for identifying argillic minerals and Fe-oxides as the main mineralogical association in hydrothermal environments. Subsequently, multispectral images (ASTER) were analyzed using band ratios.The results indicated silicification alteration along the faulted regions in the Ramand area. Later, areas of silicification alteration were prospected for precious and base metal mineralization.Sampling results suggested that the altered areas have some potential for epithermal mineralization, according to instrumental analyses and micrographic evidence. Materials and methods 1- Collecting satellite images, geological evidence and related documents 2- Image processing to reveal and identify the mineralized alteration. 3- Sampling of the mineralized zones indicated by the remote sensing. 4- Thin- and polished section microscopic studies. 5- X-ray diffraction analysis (XRD) (19 samples), inductively coupled plasma mass spectrometry analysis(ICP- MS)for determining the major and trace elements (4 samples) and 4 samples were analyzed for the gold content by using atomic absorption (AA). Discussion and results Most of the hydrothermal alteration in the Ramand region was mapped by processing the ETM and ASTER satellite images. The Crosta and Moore (1990) technique indicated the facies of alteration, and increased the correlation between altered and mineralized regions. Evaluating the potential for ore-grade mineralization requires mapping the location and probable zonal location of the quartz veins indicated by band ratios in the ASTER image (Kruse et al., 1993; Honarmand et al., 2012). Our studies showed that volcanic rocks in the Ramand area are intensively altered by hydrothermal processes. The micrographic results confirmed that argillic and silicification alteration occurred within calcitized-oxidized masses. The study has shown that the mineralized region significantly contains quartz veinlets usually surrounded by argillic halos and Fe-oxides as two components of the alteration. In conclusion, our remotely sensed prognostic mapindicates a strongly altered epithermal system along faulted structures and breccia zonesclearly apparent at the surface (Akbari, et al., 2012).The altered zones probably extend at depth with probable zones enriched in gold and base metals. Considering the zonalpatterns indicated by image processing, besides the ore genesis peculiarities of the epithermal systems (micrographic results), this article introduces reliable data indicating the nature of mineralization in the Ramand area based on analysis of satellite images and mineralogical and chemical analyses of samples which encourage detailed exploration for discovery of orebodies in a deeper prospect. References Akbari, A., Mehrnia, S.R. and Moghadasi, J., 2012. Using GIS for Investigating on Barite Mineralization Potentials in Qazvin 1/100000 Sheet. 6th National Geological Conference, Payame Noor University of Kerman, Kerman, Iran (in Persian with English abstract). Crosta, A.P. and Moore, J.McM., 1990. Enhancement of Landsat thematic mapper imagery for residual soil mapping in SW Minais Gerais State, Brazil: a prospecting case history in Greenstone belt terrain. 7th Thematic Conference on Remote Sensing for Exploration Geology, University ofCalgary, Calgary Canada. Honarmand, M., Ranjbar, H. and Shahabpour, J., 2012.Application of principal component analysis and spectral angle mapper in the mapping of hydrothermal alteration in the Jebal–Barez Area, Southeastern Iran. Resource Geology, 62(2): 119–139. Kruse, F.A., Lefkoff A.B., Boardman, J.W., Heidebrecht, K.B., Shapiro, A.T., Barloon, P.J. and Goetz. A.F.H., 1993. The spectral image processing system interactive visualization and analysis of imaging spectrometer data. Remote Sensing of Environment, Elsevier, 44(2-3): 145-163.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".