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.