DATA

 

This document briefly describes the data sets and data sources available in the MPM online tool. Further information is available in links given where available.

The content of the MPM Online Tool is similar to GTK Mineral Deposits and Exploration web service (http://gtkdata.gtk.fi/mdae/index.html). In addition, a dataset appropriate for creating mineral prospectivity models is provided (Table 1).

 

Table 1. Three types of data are available for modelling and visualization in the MPM online tool.

Data type

Purpose in the MPM tool

Link

Modelling input data by GTK

Inputs into the prospectivity models

Described below

Background data by GTK

Visualisation

Same as in http://gtkdata.gtk.fi/mdae/index.html

Background data from other sources

Visualisation

Same as in http://gtkdata.gtk.fi/mdae/index.html

 

The available input data for mineral prospectivity modelling are spatial geological, geophysical and geochemical data provided by the GTK and derivatives calculated from a chosen set of features. All dataset dedicated for modelling are in raster format. Known mineral deposits for model validation are given in point vector format. These created modelling input dataset specific to MPM Online Tool are under the GTK Basic license (http://tupa.gtk.fi/paikkatieto/lisenssi/gtk_basic_licence_1.pdf).

 

Shape files

This group of files includes a vector polygon file of Northern Finland and vector point files of mineral deposits derived from GTK's "Mineral deposits of Finland" data base (data layer Mineral Deposits). The full metadata of the Mineral deposits of Finland can be viewed at http://tupa.gtk.fi/paikkatieto/meta/mineral_deposits.html (in Finnish). Four mineral deposit-type layers are extracted from the mineral deposits data according to their genetic type. These are Orogenic Au, IOCG (Iron oxide-copper-gold), Magmatic PGE and Magmatic Ni-Cu layers. These were generated to be used as validation points of the fuzzy modelling results in the MPM Online Tool. For each of the different data sets a Fuzzy Membership Value column was added. Fuzzy Membership values were estimated based on each deposits metal content and/or economical potential. Data layer names and explanations are given in Table 2.

Table 2. Mineral deposit data layers available to be used for ROC validation in the MPM Online Tool.

Layer name

Explanation

IOCG

Iron oxide-copper-gold deposits and occurrences

Magmatic PGE

Magmatic PGE deposits and occurences

Magmatic Ni-Cu

Magmatic Ni-Cu deposits and occurrences

Orogenic Au

Orogenic gold deposits and occurrences

Geophysical data

The geophysical data consist of GTK's low-altitude aerogeophysical data acquired during 1972−2007. The parameters for original data were: flight altitude 30−40 m, the nominal flight line spacing 200 m and sample distance along the survey line 6−50 m (Airo 2005). The dataset has been recalculated for 500 m by 500 m cell size grids. The geophysical parameters measured are the Earth's magnetic field, the electromagnetic field and natural gamma radiation. Magnetic measurements determine the Earth's magnetic field strength (magnetic flux), obtaining the total magnetic intensity of the Earth's magnetic field as a parameter. Airborne electromagnetic measurements give information about the electrical properties of the ground. Measured components are real (in-phase) and imaginary (quadrature) components. Also apparent resistivity is calculated using a half space model. The MPM Online Tool data set includes total magnetic field, apparent resistivity, quadrature (em-imaginary) and in-phase (em-real) components (Table 2). Some errorneous negative values appear in the aerogeophysal dataset. However, in fuzzy logic negative values cannot be handled. Thus a small constant number was added to the values to shift the data distribution to include only positive values (Recalc, see Table 3). Metadata of the original data layers can be viewed here http://tupa.gtk.fi/paikkatieto/meta/lentogeofysikaaliset_matalalentokartat_20k.html (in Finnish).

Table 3. The geophysical layers available for fuzzy modelling in the MPM Online Tool.

Layer name

Explanation

Recalc magnetic

total magnetic field

Recalc apparent resistivity

apparent resistivity

Recalc EM quadrature

quadrature (em-imaginary)

Recalc EM real

in-phase (em-real)

 

Geochemical data

Regional till geochemistry describes the distribution of 25 elements in basal till.  The sampled material was chemically unchanged C-horizon till preferably under the water table. The average sampling depth was approximately 1.5-2 m. Sampling was done during years 1983-1991. The sampling density was one sample per 4 km2. The whole country was covered by the till sampling and the total amount of samples is 82062. The samples were collected as composite of 3-5 subsamples. The coordinates of each sample are calculated based on coordinates of these subsamples. Part of the subsamples are originally from targeting till geochemical sampling.  From dried samples the < 0.06 mm fraction was sieved for analysis. From hot aqua regia assay abundances of 25 elements were determined. The primary aim of the geochemical mapping program was to produce data for mineral exploration (Salminen 1995). Metadata can be viewed at http://tupa.gtk.fi/paikkatieto/meta/regional_till_geochemistry.html (in Finnish).

Raster layers were interpolated from these for 15 elements using inverse distance method with variable search radius and number of points 12. The geochemical rasters are named "Till gc" followed by respective element abbreviation (Table 4).

Table 4. Available till geochemical raster layers as inputs for fuzzy modelling in the MPM Online Tool. See Salminen 1995 for further details of the data quality.

Layer name

Element

Notes

Till gc Au

Au

Poor field precision

Till gc Ba

Ba

 

Till gc Ca

Ca

 

Till gc Co

Co

 

Till gc Cr

Cr

 

Till gc Cu

Cu

 

Till gc Fe

Fe

 

Till gc K

K

 

Till gc La

La

 

Till gc Mn

Mn

 

Till gc Ni

Ni

 

Till gc P

P

 

Till gc Te

Te

Poor field precision

Till gc Th

Th

Intermediate laboratory precision

Till gc V

V

 

 

Derivatives

The data set included derivative maps calculated from geological and geophysical data (Table 5). The geological data is extracted from GTK's digital bedrock map of Finland (Bedrock of Finland - DigiKP) which is a unified bedrock map dataset covering the whole Finland. It has been compiled by generalising the scale-free bedrock map feature dataset. The dataset consists of a lithological/stratigraphic geological unit polygon layer and linear layers, in which faults, diverse overprinting lines and dykes are represented. The metadata of the DigiKP (i.e. Bedrock of Finland 1:200000) can be viewed at http://tupa.gtk.fi/paikkatieto/meta/bedrock_of_finland_200k.html (in Finnish). The structures, domain boundaries, black shales and domain boundaries were selected from the DigiKP and their density and distance was calculated.

The gravity worms represent maximas of spatial gravity gradients at different upward continuation levels. The processing technique, multiscale edge detection, was first presented by Hornby et al. (1999) and later discussed by Archibald et al. (1999) and Holden et al. (2000). The the density of the worms and distance to the worms was calculated. The regional Bouguer data (1 observation per 25 km2) was used in the processing. The Bouguer anomaly map is the regional gravity data provided by the Finnish Geodetic Institute and the Geological Survey of Finland. Metadata of the original data can be found at http://tupa.gtk.fi/paikkatieto/meta/bouguer_anomaly_map_of_finland.html (in Finnish).

 

Table 5. Structural and lithological derivatives available for modelling in the MPM Online tool.

Layer name

Explanation

Density of structures

Density of structural lines

 

Distance to domain boundaries

Euclidean distance to domain boundaries

 

Distance to structures

Euclidean distance to structures

 

Distance to black shales

Euclidean distance to black shales

 

Density of lithological contacts

Density of lithological contact lines

 

Distance to worms

Euclidean distance to gravity worms

 

Density of worms

Density of gravity worm lines

 

 

References and links

Airo M.-L. (ed.) 2005. Aerogeophysics in Finland 1972-2004: Methods, System Characteristics and Applications. Geological Survey of Finland Special Paper 39. 197 p. 8 app.

Archibald, N., P. Gow, and F. Boschetti, 1999, Multiscale edge analysis of potential field data. Exploration Geophysics, 30, 38-44.

Bedrock of Finland - DigiKP. Digital map database [Electronic resource]. Geological survey of Finland [referred 15.6. 2016]. http://tupa.gtk.fi/paikkatieto/meta/bedrock_of_finland_200k.html

GTK Regional till database: http://hakku.gtk.fi/en/locations/search

Holden, D., N. Archibald, F. Boschetti, and M. Jessell, 2000, Inferring geological structures using wavelet-based multiscale edge analysis and forward models. Exploration Geophysics, 31, 617-621.

Hornby, P., F. Boschetti, and F. G. Horowitz, 1999, Analysis of potential field data in the wavelet domain. Geophysical Journal International, 137, 175-196.

METSO - GTK Mineral deposit database of Finland [Electronic resource]. Geological survey of Finland [referred 15.6. 2016] http://hakku.gtk.fi/en/locations/search?action=search&controller=locations&locale=fi&location_id=62

Salminen R. (ed.) 1995. Alueellinen geokemiallinen kartoitus Suomessa vuosina 1982-1994. Summary: Regional Geochemical Mapping in Finland in 1982-1994. Geological Survey of Finland Raport of Investigation 130. 47 p. 24 app. (In Finnish, summary in English). Electronic publication. Available at http://tupa.gtk.fi/julkaisu/tutkimusraportti/tr_130.pdf.