lecture 10 - mapping uncertainty

7/24/2019 Lecture 10 - Mapping Uncertainty

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EO 309 Intro. to Spatial Analysis:apping Uncertainty

pring 2010

GEO 309 Intro. to Spatial Analysis: Visualizing Uncertainty

GEO 309 Spring 2010

Mapping Uncertainty


In 1970, Johnny Cash (the Man in Black) asked:

What is Truth?


According to Hunter and Goodchild

(1993), when inaccuracy is known

objectively, it can be expressed as

error; when it is not known, the term

uncertainty applies.

Uncertainty about uncertainty


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Gershons taxonomy of imperfect knowledge (1998)


Pangs definitions for uncertainty

Errorcan be defined as the discrepancy between agiven value and its true value

Inaccuracyis the difference between the given valueand its modeled or simulated value

Validityencompasses both the accuracy of the datathemselves and the procedures applied to the data.

Data qualityis an even more general term thatincludes data validityand data lineage.

From Visualizing Uncertainty in Geo-spatial Data by A. Pang, 2001

How do we map what were not sure of?


Three Sources of Uncertainty

1. The raw data

itself2. The way these

data are

processed

3. Visualization

approach

Pang et al., 1997


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Three Sources of Uncertainty

For every map we look at, we need to askourselves what we can know for certain.

If we cant be sure about something, why not?Which of the 3 sources of uncertainty is the

cause? Is it more than one?

1. Questionable data

2. Questionable processing

3. Questionable visualization

??


Categories for assessing data quality



1. Lineage

2. PositionalAccuracy

3. Attribute

Accuracy

4. Completeness

5. Logical

Consistency

http://mcmcweb.er.usgs.gov/sdts/SDTS_standard_oct91/part1.html#p122


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Historical metadatadescribing the

development of the

data, e.g., digitized or

scanned, scale and

projection


1. Lineage

2. Positional

Accuracy

3. Attribute

Accuracy

4. Logical

Consistency

5. Completeness



Locational accuracy of

geographic features,

both horizontal and

vertical


1. Lineage

2. Positional

Accuracy

3. Attribute

Accuracy

4. Logical

Consistency

5. Completeness



Are the attributesassociated with this

location correct?

For example,

address, land use

classification,

temperature, etc.


1. Lineage


3. Attribute

Accuracy

4. Logical

Consistency

5. Completeness


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1. Lineage

2. Positional

Accuracy

3. Attribute

Accuracy

4. Logical

Consistency

5. Completeness


Topological integrity of the spatial

data, including:1. Do lines intersect only where intended?

2. Are any lines entered twice?3. Are all areas completely described?4. Are there any overshoots or undershoots?

5. Are any polygons too small, or any linestoo close, or polygon slivers?




1. Lineage

2. Positional

Accuracy

3. Attribute

Accuracy

4. Logical

Consistency

5. Completeness

Completeness has two components:spatial completeness and attribute

completeness. For example, it can refer

to how representative the sample of

objects is compared to all objects in the

universe, or whether standard

definitions are being used.



1. Lineage


3. Attribute

Accuracy

4. Logical

Consistency

5. Completeness

Most important in the

visualization of spatial data


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Depicting uncertainty

Visual variables

Intrinsic (already part of the display)

Extrinsic (objects added to the display)


Depicting uncertainty

Spatial uncertainty isencoded as gaps in

contour lines. The moreuncertain, the larger thegaps. The contour lines

themselves are for someother variable such astemperature, humidity, etc.

A. Pang, Visualizing Uncertainty in Geo-spatial Data, 2001


Depicting uncertainty (cont.)

Clarity (MacEachren)

Crispness, Resolution & Transparency


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Judith Tyner, Principles of Map Design, 2010





Fuzzy Britain, and Truth in Maps,Ben Terrett, 2008

(Of course,anything can

be taken to

extremes .)





High

Resolution

LowResolution
http://strangemaps.wordpress.com/2008/11/11/328-fuzzy-britain-and-truth-in-maps/http://strangemaps.wordpress.com/2008/11/11/328-fuzzy-britain-and-truth-in-maps/http://strangemaps.wordpress.com/2008/11/11/328-fuzzy-britain-and-truth-in-maps/http://strangemaps.wordpress.com/2008/11/11/328-fuzzy-britain-and-truth-in-maps/http://strangemaps.wordpress.com/2008/11/11/328-fuzzy-britain-and-truth-in-maps/


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Other approaches (Edwards & Nelson)

Legend




Reliability

Diagram


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Focus




Value


Intentional uncertainty

http://gis.chicagopolice.org/CLEARMap/startPage.htm#

Block is shown, but

not the address


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Intentional uncertainty (cont.)What ISNT this maptelling us?

What dont we

know?

What cant we besure of?

Why not?

http://map.measureofamerica.org/maps.aspx

The HIPAA Privacy

Rule protects the

privacy of individuallyidentifiable health

information (1996)

Govt.-mandated

uncertainty???


Unintentional uncertainty

Density maps, often used in

mapping crime hot spots,

may create the impression ofcriminal activity (or its

likelihood) where there is no

empirical evidence for it.

Aldo Miranda, RTI International

Mapping of crime hot-spots in

Salvadoran municipalities highlight

patterns of local crime and violence,

like this map showing robbery

incidents (orange dots) in and around

public housing (black triangles)

Questionable processQuestionable visualization


Unintentional uncertainty

Density maps, often used in

mapping crime hot spots,

may create the impression ofcriminal activity (or its

likelihood) where there is no

empirical evidence for it.

http://jamescousins.com/2009/03/london-shootings-heat-map/

Heat (intensity) map compiled from

100 shooting related incidents in and

around London, March, 2009

Questionable processQuestionable visualization


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Remember

For every map we look at, we need to askourselves what we can know for certain.

If we cant be sure about something, why not?

1. Questionable data

2. Questionable processing

3. Questionable visualization

??


Decision Making with Uncertainty

The research seems to take for granted that

visual depictions of uncertainty are useful fordecision making.-Fabien Girardin

But, does letting the map reader knowwhat is uncertain and to what degree it is

uncertain really help in making

productive decisions based on the data?

F. Girardin, 2006, http://liftlab.com/think/fabien/



Behavioral economists Tversky and Kahneman (1974) note a

conflict: some experts are dependent on statistical analyses

to incorporate uncertainty into their decision, but lay users

tend to ignore or misinterpret statistical probabilities and

instead rely on less accurate heuristics when makingdecisions.

That is, most people ignore or misinterpret

the explicit display of uncertainty and dont

end up using that information in their

decision-making processes



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Girardin poses two interesting questions:

1. Will providing information about data uncertainty in

an explicit visual way help a lay or expert mapreader make different decisions?

2. IF they do make different decisions, will provision of

information about data uncertainty lead to better,more correct, decisions or simply cause analysts to

discount the unreliable information?


Definitely worth thinking more about



Cliburn et al. (2002) address the idea of makingdecisions based on uncertain data with the help of

uncertainty representations. They list the depictionof uncertainty as a drawback, because policy makers

(the users for their study) typically want issuespresented without ambiguity. One participant in

their study suggested that a depiction of un-certainty could be used to discredit the modelsrather than having the intended effect of signalingunbiased results.



Additional (uncertain) resources

Visualizing Uncertainty in Geo-spatial Data by A. Pang,University of California, Santa Cruz

http://www.spatial.maine.edu/~worboys/SIE565/papers/pang%20viz%20uncert.pdf

UC Santa Cruz Laboratory for Visualization and Graphics:

http://slvg.soe.ucsc.edu/index.html

Gershon, N. D. 1998. Visualization of an imperfect world.

Computer Graphics and Applications (IEEE) 18(4): 43-5.

F. Girardin, http://liftlab.com/think/fabien/

And, just for fun

Judgment under Uncertainty: Heuristics and Biases. A. Tversky;D. Kahneman, 1974

http://www.hss.caltech.edu/~camerer/Ec101/JudgementUncer

tainty.pdf
http://www.spatial.maine.edu/~worboys/SIE565/papers/pang%20viz%20uncert.pdfhttp://www.spatial.maine.edu/~worboys/SIE565/papers/pang%20viz%20uncert.pdfhttp://slvg.soe.ucsc.edu/index.htmlhttp://ieeexplore.ieee.org/iel4/38/15110/00689662.pdfhttp://liftlab.com/think/fabien/http://liftlab.com/think/fabien/http://ieeexplore.ieee.org/iel4/38/15110/00689662.pdfhttp://slvg.soe.ucsc.edu/index.htmlhttp://www.spatial.maine.edu/~worboys/SIE565/papers/pang%20viz%20uncert.pdfhttp://www.spatial.maine.edu/~worboys/SIE565/papers/pang%20viz%20uncert.pdf

lecture 10 - mapping uncertainty

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