uncertainty in geological mapping - lachlan grose (monash uni.)
DESCRIPTION
This presentation was delivered at the June 10 (2014) 3D Interest Group Meeting at the Centre for Exploration Targeting, UWA.TRANSCRIPT
School of Geosciences
Investigating uncertainty in geological maps using geological variability and geodiversity
Lachlan Grose, Laurent Ailleres, Gautier Laurent and Peter Betts
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What are geological maps? how do we create them?
• A topological representation of geological interactions eg. Lithological boundaries, structures.
• Essentially a 2D model
• Human interpolation between outcrops guided by knowledge and experience
• Interpolation is similar to how implicit 3D models are built
• Studies looking into uncertainty in 3D models have used implicit scheme, we used 40 students
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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This study
Geological variability as a proxy for geological uncertainty
40 geological maps of the Eldee Structure, Broken Hill
Locate and quantifying geological variability between maps
Identify how maps vary geologically and geometrically due to variability
Classifies geological maps into “species” using the concept of biodiversity
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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Three types of uncertainty (Mann, 1993)
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
a.Error, bias and imprecision
b.Inherent randomness
c.Imprecise knowledge
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A sample map of the Eldee structure
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
Metasediments
– Clast-Bearing-Biotite-Gneiss (CBBG)– Interbedded Pelite and psamopelitic schist
(IPP) Large intrusive
– Pegmatite Smaller intrusive
– Felsic gneiss– Amphibolite
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Visualising variability Stratigraphic variability (Lindsay et al. 2012)
– Maximal when most common lithology is least well known– Assesses the quality of the average map
Information entropy (Shannon, 1958; Wellmann et al., 2012)
– Determines amount of information missing from a system– Maximal when all lithologies are equally likely to occur
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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Stratigraphic variability (P)
All maps2011 2012+ =
Stratigraphic variability
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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All maps2011 2012+ =
Confidence map 70% cutoff
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
CBBG IPP PEG
FELS AMPH
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Entropy (H)
All maps2011 2012+ =
Information entropy
Information entropy (H)
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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Probability
Felsic gneiss
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
All maps2011 2012+ =
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Probability
Amphibolite
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
All maps2011 2012+ =
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Lawrence, 2008; Lindsay et al., 2013
Comparing maps using geodiversity• Biodiversity allows for;
• Diversity of species described by a number of metrics• Trends in dataset to be identified
• Geodiversity
• Built on the concept of biodiversity• Geometrical and geological metrics can be used to
analyse the diversity of a set of geological maps/models• Trends between maps can be found highlighting different
“species” of maps/models
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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Analysing geodiversity• Principal Component Analysis (PCA)
• Used by Lindsay et al. 2013• Identifies linear trends in the dataset• A common dimension reduction technique• However many of the geodiversity metrics don’t follow
standard distributions - which can introduce error!• May bias towards modal map (modal geodiversity values)
• Self Organising Maps (SOMs) (Kohonen, 1982)
• Fits a deformable mesh to the dataset capturing more details about the distribution of the original dataset
• Also provides dimension reduction• Can be used to categorise groups of similar maps
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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Sml Med Lge Legs Feathers
Hair Hooves
Mane
Run Swim Hunt Fly
dove 1 0 0 2 1 0 0 0 0 0 0 1
hen 1 0 0 2 1 0 0 0 0 0 0 0
duck 1 0 0 2 1 0 0 0 0 1 0 0
goose 1 0 0 2 1 0 0 0 0 1 0 1
owl 1 0 0 2 1 0 0 0 0 0 1 1
hawk 1 0 0 2 1 0 0 0 0 0 1 1
eagle 0 1 0 2 1 0 0 0 0 0 1 1
fox 0 1 0 4 0 1 0 0 0 0 1 0
dog 0 1 0 4 0 1 0 0 1 0 1 0
wolf 0 1 0 4 0 1 0 1 1 0 1 0
cat 1 0 0 4 0 1 0 0 0 0 1 0
tiger 0 0 1 4 0 1 0 0 1 0 1 0
lion 0 0 1 4 0 1 0 1 1 0 1 0
horse 0 0 1 4 0 1 1 1 1 0 0 0
zebra 0 0 1 4 0 1 1 1 1 0 0 0
cow 0 0 1 4 0 1 1 0 0 0 0 0
A quick example of SOMs
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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SOMs component maps
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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Animal groups
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
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Geodiversity metrics
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
Aspect ratio
Geological Complexity
Contact relationships
Surface area and number of regionsOrientation
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SOMs geodiversity results
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
Number of regions PEGMATITE
Number of regions FELSIC GNEISS
Contact between INTERBEDDED AND
FELSIC GNEISS
Maximum surface area PEGMATITE
Number of regions INTERBEDDED
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Map “species”
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
Species 1 Species 2 Species 3
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Probability
The modal map
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
All maps2011 2012+ =
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Conclusion
6th Febuary 2014Geological uncertainty in geological maps using variability and geodiversity
Variability observed between students interpretation of the geometry of lithological domains
The felsic gneiss and amphibolite were rarely mapped consistently in the one location
◦ We identified three distinct clusters highlight different mapping styles; lumpers, blobbers and the outliers!
◦ Self Organising Maps should be considered for further geodiversity analysis