Integrated Aeromagnetic and Radiometric Data

Organize a centralized folder structure for aero-magnetic and radiometrics data, GIS projects, and related files, including shapefiles, maps, raster images, and shareable archives.

Locate mining sites and define the study area by converting coordinates to decimal degrees, creating GIS points, then exporting the area as shapefile and KML for ArcGIS and Google Earth.

Identify towns within your study area in QGIS, assign names, and save them as a towns shapefile. Export with WGS84 coordinates for use in ArcGIS.

Create a radiometric data project, import potassium, thorium, and uranium grids, project to UTM 32N, save to database, export geotiff, and verify study area on the grid in Google Earth.

Produce potassium, thorium, and uranium radiometric grids for the study area using grid and image utilities, labeled as k, th, and u. Reproject to xy coordinates for geographic alignment.

Create potassium, thorium, and uranium concentration maps in OS montage, export them to ArcGIS, and prepare them for styling and analysis in ArcGIS MSD.

Create a potassium-thorium ratio map from potassium and thorium data to delineate hydrothermal alteration zones, export a CSV, re-project grids, and visualize in ArcGIS.

Create a K–Th–U ternary map from radiometric data using RGB channels to reveal relative concentrations; identify potassic alteration zones and potential radio targets, then export as a GeoTIFF.

Identify anomalies in the potassium to rhodium ratio and ternary maps using QGIS, creating shapefile polygons to map hydrothermal alteration zones.

Edit and export a potassium K/Th ratio map in ArcGIS, adjusting grids, symbols, legends, and scale bars, then generate a ternary radiometric map with anomalies and mining sites for publication.

Reclassify the potassium-to-radiometric ratio map into three regions—high, medium, and low—and use ArcGIS to grid, rasterize, and resample to 30x30 cells, delineating high-mineral-potential areas.

Reclassify the potassium-thorium data into three ranges, save as a TIFF raster, and apply color symbology to produce a reclassified potassium-thorium ratio map for mineralization potential.

Create a new aero-magnetic project in OAS Montage, import grids with magmap and cet, reproject to longitude and latitude in utm 32n, and grade the z channel to tmi.

Learn to extract the study area tmi from sheet 104, convert to x and y coordinates, and produce a finished arcgis tmi map with a 200 m grid.

Realign magnetic anomalies by reducing total magnetic intensity to the equator with MAGMAP, then compare side-by-side RTE and TMI maps for analysis using date, declination, and inclination.

Create the analytical signal map for the study area by building a grid and exporting to ArcGIS. Highlight anomalous zones and mining sites using normal distribution shading.

Isolate anomalies in the AS grid using the analytical signal in QGIS, converting it to a raster, and digitizing polygon features to delineate magnetic anomalies.

Edit the analytical signal map created in OAS Montage in ArcGIS, adjusting grids, symbols, labels, and the legend, then export a high resolution image of the map.

Reclassify the analytical signal map for use in the weighted overlay via the analytical hierarchy process in ArcGIS.

Use spatial analysts tools in ArcGIS to reclassify the analytical signal into three ranges with breakpoints at 0.058 and 0.1254, then export a map layer with legend.

Create the EULA solution map for structural index one using EULA convolution to map linear features, refine depth and errors, and overlay analytical signal for validation.

Learn to create a lineament map and derive a lineament density map in ArcGIS, using detected lineaments, skeleton to vectors, and shapefile export.

Create a reclassified linear mean density map for the study area using spatial analyst tools, including resampling to 30 meters, three-class reclassification, and exporting for the analytical hierarchy process weighting.

Create a rose diagram for lineaments by splitting lines at vertices, calculating coordinates, exporting to dxf, importing to RockWorks with utm meters zone 32, generating a jpeg (legend optional).

Apply the analytical hierarchy process to derive weights from pairwise comparisons of analytical signal, lignin density, and potassium to urium, and then perform a weighted overlay in ArcGIS.

Load three rasters (potassium, thorium, and lignament density); ensure identical cell size, apply weights from the analytical signal, and export the weighted overlay as a mineral potential map.

This lecture shows how to produce a mineralization potential map by reclassifying data, applying a weighted overlay, and symbolizing high, moderate, and low potential zones from aero-magnetic and radiometric data.