using sound to represent positional accuracy of address locations nick bearman and andrew lovett phd...

Using Sound to Represent Positional Accuracy of

Address LocationsNick Bearman and Andrew Lovett

PhDSchool of Environmental Science

University of East Anglia

[email protected]; [email protected]

IntroductionPositional

Accuracy & AL2

Why Sound? Methods Results Next Steps

Positional Accuracy of Address Locations

• Geo-coding is ‘address’ → ‘location’

• Two main uses

• Spatial analysis & Routing

• Why is it important?

• Address Layer 2 is used for geo-coding• not all addresses have correct locations

• assuming all entries are correct can impact the analysis or routing

Merrifield CottageTR16 5DA


Accuracy & AL2


OS MasterMap ® Address Layer 211B Clarendon Road

NorwichNR2 2PN


Accuracy & AL2


Value Description

Surveyed Within the building that the address refers to.

Approximate Usually within 50m.

Postcode Unit Mean Mean position calculated from correctly located points within the postcode unit (e.g. NR4 6AA is a postcode unit).

Estimate Usually within 100m.

Postcode Sector Mean Mean position calculated from correctly located points within the postcode sector (e.g. NR4 6__ is a postcode sector).

Positional Accuracy - which some users ignore

Why?

• it's not relevant• users don't think it's relevant (when it is)• users can't access the information within the data• users can't display the information• the information isn't available

• Vision can be saturated• Alternatives to Vision

• Vision can be used more effectively – but there are limits

• Sound is the next most powerful sense (haptic/touch)• Little Previous Research

• These were pilot studies, custom coded. Need to move these to a generic, easily usable environment (GIS)

• No user testing & no existing research frameworks• Piano Notes

• Easy to understand – clear order (implicit assumption?)• CEG Triad, preferred option• Possibly could have chosen any sound though

Why Sound?

http://kbark.wordpress.com/2006/12/17/where-am-i/ (18/03/2009)

Finnish Town

http://www.politics.co.uk/news/policing-and-crime/new-police-crime-maps-confusing--$1272816.htm (18/03/2009)

London Crime

Fisher (1994)

Fisher (1994) Uncertainty of Classification

MacVeigh & Jacobson (2007)

MacVeigh & Jacobson (2007) Harbour, Sea and Land


Accuracy & AL2


Value

Surveyed

Approximate

Postcode Unit Mean

Estimate

Postcode Sector Mean

Methods• Created extension to ArcGIS

• Written in Visual Basic

• Prototype – tested and improved

• Users asked to choose proportion• 25%, 50% or 75% (stratified random method)

• Four methods

• Demo


Accuracy & AL2


• Proportion – (p < 0.005)

– Logical, but no evidence of this in GI literature

• Presentation Method– (p < 0.05)

– As expected

ResultsProportion Mean Score

75% 0.88

25% 0.74

50% 0.62

Presentation Method Mean Score

Visual Sonic Same 0.86

Visual 0.82

Sonic 0.67

Visual Sonic Different 0.65

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+-

+

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Accuracy & AL2


• Logistic Regression• Also Knowledge of the Data appeared to have an impact

– but when this was added into the logistic regression, it wasn’t significant.

• Discussion Sessions• Greater differences between sounds• Colour blind users

Results

Factors added to Model -2 Log Likelihood Cox & Snell R2

Proportion 182.01 0.043

Presentation Method 169.579 0.105

Knowledge of the Data 167.319 0.116


Accuracy & AL2


Next Steps• Summary

• Sound can work

• Significant Factors• Proportion of Data and Presentation Method

• Knowledge of Data

• Improvements• Task & Sounds

• Next case study• UKCP09

• web interface

• more focus on prior knowledge of data set

• VR Visualisations of Future Landscapes


Accuracy & AL2


using sound to represent positional accuracy of address locations nick bearman and andrew lovett phd...

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