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Creating a Walkability Surface for Maricopa County

Parul Singh and Madison DavisASU MAS-GIS students

Co-Authors: Marc Adams, Jane Hurley, Lu Hao

Funding Source #: R01CA198915

Presentation Objective

To share the the steps taken and tools used to create a geographic surface of walkability for Maricopa County

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Overview• Background on Walkability and WalkIT Arizona Study• Four Components of the Walkability Index:

o Net Residential Densityo Intersection Densityo Transit Densityo Land Use Mix (Entropy)

• Results and Significance

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Why is Walkability important?

U.S. Department of Health and Human Services. September 2015

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Vice Admiral Vivek Hallegere Murthy, Surgeon General of the United States

WalkIT Arizona Study

“to test the effectiveness of interventions using physical activity trackers, goal setting,

motivational text messages, monetary incentives and health education to promote physical activity

behaviors...”

“in high and low walkable communities”

Principal Investigator Marc Adams, PhD, MPH

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International Physical Activity and Environment Network (IPEN) Study

IPEN GIS templates guided decisions to quantify built environment attributes for physical activity

Templates include +100 pages of definitions, recommendations

www.ipenproject.org

Adams, Frank et al., 2015 Int’l J of Health Geographics

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Software• ESRI ArcGIS for Desktop v. 10.3

• Microsoft Excel

• SPSS

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Calculating Walkability• 4 components, each is a surface

• First find raw scores for each component

• Walkability Index = [ (z-score of net residential density)+ 2*(z-score of intersection

density)+ (z-score of transit density)+ (z-score of land use mix)]

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Maricopa County

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Focus Area

Phoenix Urban Core

North Scottsdale Suburban

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Urban Core Suburban

Comparison

Same scale (resolution)11

Preliminary Steps

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Preliminary Steps• Data Acquisition

o Maricopa County Assessor's Officeo Maricopa Association of Governments (MAG)o Valley Metroo U.S. Census Bureau

• Prep for use in context o Projection: NAD 1983 HARN StatePlane Arizona Central FIPS 0202 (Meters)

• PUCs Reclassification (2251 down to 5)o Main categories:

residential retail office entertainment civic 13

PUCs Reclassification ● Residential

○ single & multiple family,mobile home, dormitory○ exclude: hotels, motels, timeshared property

● Retail○ retail stores, shopping malls, banking, gas stations, food-related○ exclude: auto dealerships, “big box” mega stores ( >=300,000 sqf.)

● Office○ administration, nonprofit institutions, medical services○ exclude: warehouses, manufacturing offices, factories,

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PUCs Reclassification● Entertainment

○ bars, night clubs, theaters, museums

● Civic/ institutional○ educational, religious, health, governmental, police, military facilities

● Multi-use codes (mixed-use)○ Store & Office/Apartment○ Office & Residence

■ double/ triple counted

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Unit of Analysis• Census Block Groups

o Aligns with population estimate in IPEN templates• 100 Meter buffer

o Captures walkability/built environment features on edges

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Block Group Buffer

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Original Boundary

Walkability Components

1:Residential Density

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Net Residential Density• Ratio of residential housing units: residential land area in the buffer

o Residential= permanent, majority of the year, not easily moved housing/dwelling units

o Includes single and multi family use

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Net Residential Density• High Density = many units in area• Low Density = units spread out

20Imagery: Google, Map Data, Digital Globe, 2016

Net Residential Density

• Layer of all residential parcelso ~1.3 million parcels

• Includes Land Area and Housing Unitcount fields

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• Assign parcels to buffered block groups

Net Residential Density

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Net Residential Density

= Count Area

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Net Residential DensityUrban Core Suburban

24Lowest Highest

Walkability Components2:Intersection Density

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Intersection Density• Ratio of intersections : land area• Intersection: 3 or more walkable road segments intersect

• High Density = Many walkable intersections• Low Density = Few walkable intersections

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Intersection DensityRoads Included:

1. Neighborhood Streets

2. Byway - single lane of traffic in each direction

3. Pedestrian Trail

4. Pedestrian Passageway

5. Rural Road

6. City Streets

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Roads Excluded:

1. Interstate highway

2. Ramps

3. Unpaved Roads

4. Limited Access Highways

5. Freeways

6. Expressway

Pseudo Nodes

Dangling Nodes

Nodes not included

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Intersection Density

True Nodes

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Intersection Density

Intersection Density

• Assign Regular nodes to the Block group

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Intersection DensityIntersection Density = Count/ Area

31Summarize on Block group buffer Field

Intersection DensityUrban Core Suburban

32Lowest Highest

Walkability Components3:Transit Density

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Transit Density

• Ratio of transit stops: land area• Transit stops include bus and light rail• Considered how many buses stop at each ‘physical’ stop

• High Transit Density = many transit stops• Low Transit Density = few transit stops

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Transit Density● Bus Stops

● Light-Rail stops

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Transit Density

Summarize on Block group buffer Field

Transit density = Count/Area

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Transit DensityUrban Core Suburban

37Lowest Highest

Walkability Components

4: Land Use Mix

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Land Use Mix• Calculation of entropy of land use types in block group buffer

• Raw Score always between 0 and 1o 0 indicates only one land use present o 1 indicates a perfectly even distribution of all land uses across the block

group buffer

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Land Use Mix• Repeat merge and summarize processes described to get the sum of land or

floor area in each block group

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LandUseMix.gdbParcelArea_OfficeParcelArea_RetailParcelArea_CivicParcelArea_EntertainmentLivableArea_Residential

Land Use Mix

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Land Use MixUrban Core Suburban

42Lowest Highest

Walkability Index

Walkability Index = [ (z-score of net residential density) + (z-score of intersection density) + (z-score of transit density) + (z-score of retail floor area ratio) + (z-score of land use mix)]

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Z- Score Net Residential DensityIntersection DensityTransit Density Land Use Mix

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Lowest Highest

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Z- Score Net Residential DensityIntersection DensityTransit Density Land Use Mix

Lowest Highest

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Z- Score Net Residential DensityIntersection DensityTransit Density Land Use Mix

Lowest Highest

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Z- Score Net Residential DensityIntersection DensityTransit Density Land Use Mix

Lowest Highest

Walkability Surface…Combine all of the components...

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WalkabilitySurface

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Lowest Highest

Net Residential DensityIntersection DensityTransit Density Land Use Mix

WalkabilityUrban Core Suburban

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Crime-risk

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Lowest Highest

Walkability-Crime analysis

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Advantages of using GIS

• Analysis on Macroscale• Use existing data • Map Creation• Patterns are clearly observed• Help to select neighborhoods to test the effectiveness of the physical activity

intervention

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Conclusion• Able to target recruiting efforts to high and low walkable areas

• Gather participants for the WalkIT Arizona Research Study

Next Steps ● Virtual truth to make sure the surface makes sense

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Thank you!

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ContactsParul Singh Madison Davispsingh26@asu.edu mbdavis6@asu.edu

Marc Adams, PhD, MPHmarc.adams@asu.edu

MAS-GIS 2015-1656

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Data Versions:Maricopa County Block Groups, 2010 U.S. Census

Parcels, Maricopa County Assessor’s Office, 2015

Light Rail and Transit Stops, Valley Metro, 2015

Roads, U.S. Census TIGER/Line, 2015

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