A collection of ESRI ArcGIS tools to perform GIS-based mineral (Nickel) prospectivity analysis using a knowledge-driven approach to combine different datasets in the study of Potential for intrusion-hosted Ni-Cu-PGE sulfide deposits in Australia: A continental-scale analysis of mineral system prospectivity.
###Metadata###
###Dependancies###
- ESRI ArcGIS 10.1 (ArcInfo Licence)
- ESRI ArcGIS Spatial Analysis Extension
- Python 2.7
###Configuration###
Download package, unzip and add GA_Nickel_Toolbox_2015.tbx to your ArcGIS toolbox
This study of Australia’s potential for tholeiitic intrusion-hosted Ni-Cu-PGE sulfide deposits utilises a mineral systems approach as the basis for a knowledge-driven GIS-based prospectivity analysis. The conceptual model for the formation of tholeiitic intrusion-hosted Ni-Cu-PGE sulfide deposits incorporates four mineral system components: (1) energy sources or drivers of the ore-forming system; (2) crustal and mantle lithospheric architecture; (3) sources of ore constituents (i.e., Ni, PGE, Cu, S in magmatic systems); and (4) gradients in ore depositional physico-chemical parameters. For each of the four system components 'theoretical’ conceptual criteria were developed which represent geological processes essential for the formation of a major ore deposit. These processes are represented by `mappable criteria’ which are themselves represented by individual geoscientific datasets. The GIS analysis of prospectivity uses a wide range of continental- to regional-scale geological, geophysical and geochemical datasets, each weighted with fuzzy logic values between 0 and 1 according to expert opinion. Summed values for each of the four mineral system components contributes a maximum of 25% of the final assessment of mineral potential, reflecting the need for all four mineral system components to have been present to form a major ore deposit.
Figure 1: Map showing the potential for tholeiitic intrusion-hosted Ni-Cu-PGE sulfide deposits in Australia. For further information refer to the publication listing below.
The following tools are available through the toolbox. Please refer to the publication listed below for detailed workflow and data processing descriptions.
#####1. Union input data + calculate sum or max Merges vector data into a single vector layer using the union process and takes either the sum or maximum of the input layers to form the new value.
#####2a. Polygon To Raster Polygon to raster tool to convert vector files to raster.
#####2b. Resample raster to source raster Alters the input raster dataset by changing the cell size and origin to match the snap raster using the nearest neighbour resampling algorithm.
#####3. Normalize Raster Creates normalized (0-1) raster for each input file.
#####4. Convert to Integer and create attribute table Converts raster to integer using the supplied multiplier and adds an attribute table to the output raster.
#####5. Populate I, A, C and W fields Populates the raster attribute table with Importance, Applicability and Confidence fields and values. Using these fields a total weight field is calculated.
#####6a. Weighted sum - use feature weight Executes a weighted sum calculation using the weight values stored in the attribute table of each input raster
#####6b. Weighted sum - use equal weight Executes a weighted sum calculation using an equal weight given to each input raster.
Dulfer, H., Skirrow, R.G., Champion, D.C., Highet, L.M., Czarnota, K & Coghlan, R.A., 2015. Potential for intrusion-hosted Ni-Cu-PGE sulfide deposits in Australia: A continental-scale analysis of mineral system prospectivity. Record 2016/001. Geoscience Australia, Canberra. http://dx.doi.org/10.11636/Record.2016.001