Statewide Bicycle/Pedestrian Suitability Analysis

Statewide Bicycle/Pedestrian Suitability Analysis Eric DeVoe | Office of Traffic Engineering June 25, 2019 To prioritize reviewing projects for bicycle and pedestrian accommodations, this high-level analysis aggregates data on key characteristics across the entire state. For project selection or prioritization, this process captures an estimate for demand but not existing infrastructure. To avoid issues with updates to the LRS and ensure continuity across geographies, the entire state was divided into 522,263 equal sized hexagons. Each hexagon is approximately 104 acres; as a frame of reference, the Mall of America with attached parking is approximately 88 acres.

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Characteristics

Field Name Definition Source

BUSSTOP Within 500 feet of Bus Stop MnDOT, Met Transit

SCHOOL Within 1 mile of a K-12 School Dept. Education

URBAN Urban Downtowns Dept. Agriculture

FOOD_05MI Percent of Population > 0.5 miles from Supermarket USDA

FOOD_1MI Percent of Population > 1 mile from Supermarket USDA

FOOD_10MI Percent of Population > 10 miles from Supermarket USDA

FOOD_20MI Percent of Population > 20 miles from Supermarket USDA

EJ_MPCA MPCA Area of Environmental Concern < calculated >

EJ_185POV MPCA Area of Environmental Concern: Percent Below 185% Poverty ACS (D05, S1701)

EJ_POC MPCA Area of Environmental Concern: Percent People of Color* ACS (B03002)

REZ Indian Reservation MnDOT

BIKE_COMM Within 1 mile of Bike Friendly Community MnDOT

BIKE_FIRM Within 1 mile of Bike Friendly Business MnDOT

BIKE_UNIV Within 1 mile of Bike Friendly University MnDOT

BIKE_PRTY MnDOT Bike Plan Priorities MnDOT

TRAIL USBR-41, USBR-45, and DNR Trails MnDOT, DNR

DENS_LAND 2015 Population Density per 100 Acres (Land Only) ACS (S0101)

DENS_AREA 2015 Population Density per 100 Acres (Land + Water) ACS (S0101)

PCT_0517 Percent Population Age 5-17 ACS (S0101)

PCT_1864 Percent Population Age 18-64 ACS (S0101)

PCT_65UP Percent Population Age 65+ ACS (S0101)

PCT_DABLE Percent Population with Disability ACS (DP02)

PCT_NAI Percent Population Native American Indian ACS (DP05)

PCT_NCIT Percent of Population Non-citizen, Foreign Born ACS (DP02)

POV_ALL Percent in Poverty, Total Population ACS (DP03)

POV_0017 Percent in Poverty, Age 0-17 ACS (DP03)

POV_1864 Percent in Poverty, Age 18-64 ACS (DP03)

POV_65UP Percent in Poverty, Age 65+ ACS (DP03)

INC_MED Medium Income ACS (DP03)

INC_CAPITA Per Capita Income ACS (DP03)

UNEMPLOY Unemployment Rate ACS (DP03)

FIRM_EST Average Number of Employers, 2011-2015 CBP

FIRM_GROW Trend in Number of Employers, 2011-2015 CBP

PCT_VEH0 Percent of Workers with Access to 0 Vehicles ACS (S0801)

PCT_VEH1 Percent of Workers with Access to 1 Vehicle ACS (S0801)

PCT_VEH2UP Percent of Workers with Access to 2+ Vehicles ACS (S0801)

PCT_BIKE Percent of Workers, Commute by Bike ACS (S0801)

PCT_POOL Percent of Workers, Commute by Carpool ACS (S0801)

PCT_SVO Percent of Workers, Commute by Driving Alone ACS (S0801)

PCT_TRNST Percent of Workers, Commute by Public Transportation ACS (S0801)

PCT_WALK Percent of Workers, Commute by Walking ACS (S0801)

MIN_0014 Percent of Workers, Commuting 0-14 minutes ACS (S0801)




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Field Name Definition Source

MIN_60UP Percent of Workers, Commuting 60+ minutes ACS (S0801)

RD_MI Miles, All Roads MnDOT

TH_MI Miles, Trunk Highways MnDOT

CO_MI Miles, County Roads MnDOT

CI_MI Miles, City/Municipal Roads MnDOT

OT_MI Miles, Other Roads MnDOT

DSP_RISK Maximum (TH) Intersection Safety Risk Score for Non-motorists MnDOT

XINGS Number of Intersections (estimate) MnDOT

XING_DENS Intersection Density MnDOT

RD_ADT Calculated ADT, All Roads MnDOT

TH_ADT Calculated ADT, Trunk Highways MnDOT

CO_ADT Calculated ADT, County Roads MnDOT

CI_ADT Calculated ADT, City/Municipal Roads MnDOT

OT_ADT Calculated ADT, Other Roads MnDOT

DBP_SCORE District Bike Plan Priority Score, 07/20/2018 < Calculated >

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Scoring and Aggregating

District Bike Plan Priority Scoring, 07/20/18

DBP Score Total Miles Trunk Highway Miles Hexagons

0 836 0.6 % 81 0.6 % 12,192 2.3 %

1 to 20 32,226 22.0 % 2,947 20.6 % 126,912 24.3 %

21 to 40 96,055 65.6 % 9,285 64.9 % 361,926 69.3 %

41 to 60 15,030 10.3 % 1,709 12.0 % 20,363 3.9 %

61 to 80 2,279 1.6 % 264 1.8 % 843 0.2 %

81 to 93 84 0.1 % 12 0.1 % 27 0.0 %

DBP_SCORE = 100 ×1

14×∑ points

1 point Within 500 feet of bus stop BUSSTOP = YES

1 point Within an urban area URBAN in (RURAL DOWNTOWN, METRO,

METRO – GREATER MN)

1 point Percent of population less than 0.5 mile from supermarket > 25.0

FOOD_05MI < 75.0

1 point Percent of population below 185% of federal poverty line > 40.0

EJ_185POV > 40

1 point Contains a state bicycle trail TRAIL in (DNR, USBR41, USBR45)

1 point Population density > MN average DENS_LAND > 10.70

1 point Percent of population age 5-17 > MN average PCT_0517 > 17.1

1 point Percent of population age 65+ > MN average PCT_65UP > 14.3

1 point Percent of population with disability > MN average PCT_DABLE > 10.6

1 point Percent of population Native American > MN average OR within reservation boundary

PCT_NAI > 1.0 or REZ = YES

1 point Percent of population foreign born > MN average PCT_NCIT > 4.0

1 point Statistically significant growth in number of firms over previous five years

FIRM_GROW > 0.5

1 point Percent of workers with access to zero vehicles > MN average

PCT_VEH0 > 2.6

1 point Contains a high risk intersection for non-motorists identified in District Safety Plan

DSP_RISK > 3

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Suitabil ity of Pedestrian And Cyclist Environment (SPACE) Score , 04/26/18

SPACE Total Miles Trunk Highway Miles Hexagons

0 0 .0 % 0 .0 % 0 .0 %

1 to 15 578 .4 % 30 .2 % 16,898 3.2 %

16 to 30 13,735 9.4 % 1,259 8.8 % 59,901 11.5 %

31 to 45 66,508 45.4 % 5,946 41.6 % 237,177 45.4 %

46 to 60 57,029 38.9 % 5,972 41.8 % 196,612 37.6 %

61 to 75 8,110 5.5 % 1,024 7.2 % 11,499 2.2 %

76 to 90 549 .4 % 67 .5 % 176 .0 %

91 + 0 .0 % 0 .0 % 0 .0 %

SPACE_SCORE = 100 ×1

19×∑ points


1 point Within 1 mile of a K-12 school SCHOOL = YES




FOOD_05MI < 75.0

1 point Defined as an “area of concern” by MPCA environmental justice

EJ_MPCA = YES





1 point Percent of population Native American > MN average

PCT_NAI > 1.0


1 point Within an urban area, percent of total population in poverty > 25.0

URBAN ≠ RURAL and POV_ALL > 25.0

1 point Unemployment rate > MN average UNEMPLOY > 4.9

1 point Percent of workers with access to zero vehicles > 0.0

PCT_VEH0 > 0.0

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1 point Percent of workers commuting by bicycle > 0.0 PCT_BIKE > 0.0

1 point Percent of workers commuting by transit > 0.0 PCT_TRNST > 0.0

1 point Percent of workers commuting by walking > 0.0 PCT_WALK > 0.0

1 point Percent of workers with a commute less than 15 minutes > MN average

MIN_0014 > 31.3


DSP_RISK > 4

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Field Definitions Values of the input datasets are assumed to be uniformly distributed across the representative geographies; by using the smallest available area, this assumption is not inappropriate for such high-level analysis. Input spatial datasets are clipped to the boundaries of the containing hexagons. The calculated lengths or areas are used as weighting to aggregate to each hexagon.

PCT_TOT =∑(PCT𝑖 × AREA𝑖)

𝑛

𝑖=1

/∑(AREA𝑖)

𝑛

𝑖=1

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Bike Friendly Communities

Bike MN conducts applications for Bike Friendly Community (BFC) status twice annually. Results from 2018 Round One will be announced in May; applications open in August for 2018 Round Two. A community remains with BFC status for four years. Honorable mentions are given for one year; however these are not included in the analysis here.

Employer Growth

Growth was estimated for each ZIP code from the original County Business Patterns dataset. The percent growth in employers from the prior year estimate was calculated for 2011, 2012, 2013, 2014 and 2015. A trend was estimated using a linear regression on these five points; statistical significance reported at α = 0.05 for a one-sided t-test. While County Business Pattern data is not recommended as a time series, the FIRM_GROW field attempts to capture general trends of growing or shrinking, large or small.

- 1.0 Statistically significant reduction in employers

- 0.5 Portions have statistically significant reductions in employers

0.0 Trend in number of employers is not statistically significant

+ 0.5 Portions have statistically significant growth in employers

+1.0 Statistically significant growth in employers

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Environmental Justice with MPCA

Minnesota Pollution Control Agency considers areas of concern for environmental justice at the Census Tract level rather than ZTCA. Three factors are used in defining an environmental justice concern:

At least 40% of people reported income less than 185% of federal poverty level

At least 50% of people identify as people of color*

Tribal area Census data is derived from ACS 5-year estimates (e.g. DP05, S1701). More information on MPCA environmental justice work can be found at www.pca.state.mn.us/ej. To maintain consistency, the field EJ_MPCA of the hexagon characteristics is computed at the ZTCA level. “People of color” are defined as all individuals not identified as “Not Hispanic or Latino: - White Alone”.

Food Deserts

Characteristics of the USDA Food Access Research Atlas Data are located based on the census tracts at a 1:500,000 mile resolution. Three definitions are reported for low access tracts by the researchers; “Low Access Tract at 1 mile for Urban Areas and 10 miles for Rural Areas” is recommended for use with this dataset.

Intersections

The XINGS field is based on a working dataset being developed by MnDOT Office of Traffic, Safety & Technology (OTST) and MnGEO to contain all at grade intersections in Minnesota. XING: number of intersections, rounded

0 to 5 round up to nearest 1

6 to 10 round up to nearest 2

10 + round up to nearest 5

XING_DENS: number of intersections divided by total roadway miles, rounded after calculation

.00 to 2.50 round up to nearest 0.05

2.51 to 5.00 round up to nearest 0.25

5.01 to 10.00 round up to nearest 0.5

10.01 to 50.00 round up to nearest 1



500.01 + round up to nearest 100

XING_DENS = ∑(Intersection𝑖)

𝑖

/RD_MILES

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Non-citizen, Foreign Born

Calculated as percent of Foreign Born population that is Non-citizen as a percent of Total Population where Foreign/Native Born known.

Volume (ADT)

Calculated volume is based on the Traffic Volume layer. It is further separated by system type for Trunk Highways, CSAHs/CRs, MSAS/City Streets, and all others. The miles may not reflect the centerline miles in a hexagon but is useful in estimating AADT (e.g. divided highways).

RD_ADT = ∑(ADT𝑖 × LENGTH𝑖)

𝑛

𝑖=1

/∑(LENGTH𝑖)

𝑛

𝑖=1

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Data Sources and Technical Details

Data Screening Criteria

A basic set of criteria was applied to screen potential data sources:

1. Spatial 2. Can be applied consistently across state 3. As localized as possible, i.e. smallest possible areas

Some valuable datasets (e.g. Open Street Map, Regional Parks, or Land Use) were not included due to regional limitations or inconsistent reporting.

ZTCA Codes and ZIP Codes

Zip Code Tabulation Areas (ZTCAs) are general polygon representations of ZIP Code service areas developed and maintained by the U.S. Census Bureau. For this analysis, ZTCAs within Minnesota and surrounding U.S. states are applied to each hexagon. ZIP Codes identify individual post office or delivery stations for addresses as maintained by the U.S. Postal Service; ZIP codes are not spatial features but a collection of delivery routes. In most instances the ZCTA code is the same as the ZIP code for an area.

Data Sources Internal to MnDOT

“AADT.” TGP11g. SDW_FRZ_INCDT.TRAFFIC_VOLUME_AADT.

“All Bus Stop.” TGP11g. ADA_SIDEWALK_ADMIN.BusStop.

“Bike Routes.” TGP11g. SDW_FRZ_TRANS.BIKE_ROUTES.

“CHIP.” ArcGIS Portal. http://services.arcgis.com/qWbGMYB49y8mLbRt/arcgis/rest/services/ CHIP_SD/FeatureServer

“District Safety Plan Intersections.” TGP11g. SDW_FRZ_DTHSP.INTERSECTIONS. (Maximum Risk 7 Stars)

“Metro Intersection Bike/Ped Risk Assessment.” August 2017. Kaitlin Spomer. MnDOT, Office of Traffic, Safety & Technology. (Maximum Risk 5 Stars)

“Motor Vehicle Crash Data, 2013-2015.” WHS111g. CRASH_ADMIN schema.

“Motor Vehicle Crash Data, 2016-2017.” TGP11g. CRASH_DPS_TEMP schema.

“Preliminary OTST Intersections.” March 2018. ArcGIS Portal.

“Tribal Governments.” TGP11g. SDW_FRZ_GOVNT.TRIBAL_GOVERNMENTS.

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“USBR 41 – North Star Route.” May 2017. Liz Walton. MnDOT, Office of Transit and Active Transportation.

“USBR 45 – Mississippi River Trail.” March 2015. Liz Walton. MnDOT, Office of Transit and Active Transportation.

Data Sources External to MnDOT

Bicycle Alliance of Minnesota. “Bike Friendly Businesses.” April 2018. www.bikemn.org/ collaboration/bicycle-friendly-programs/bicycle-friendly-business

Bicycle Alliance of Minnesota. “Bike Friendly Communities.” April 2018. www.bikemn.org/ collaboration/bicycle-friendly-programs/bicycle-friendly-community

Bicycle Alliance of Minnesota. “Bike Friendly Universities.” April 2018. www.bikemn.org/ collaboration/bicycle-friendly-programs/bicycle-friendly-university

Department of Agriculture. “Urban Areas, Minnesota.” March 12, 2016. Distributed by MnGEO. ftp://ftp.gisdata.mn.gov/pub/gdrs/data/pub/us_mn_state_mda/base_urban_areas/ metadata/metadata.html

Department of Education. “School Program Locations, Minnesota, SY2017-2018.” November 7, 2017. Distributed by MnGEO. ftp://ftp.gisdata.mn.gov/pub/gdrs/data/pub/ us_mn_state_mde/struc_school_program_locs/metadata/metadata.html

Department of Natural Resources. Division of Parks and Trails. “State Trails of Minnesota.” March 14, 2018. Distributed by MnGEO. ftp://ftp.gisdata.mn.gov/pub/gdrs/data/pub/ us_mn_state_dnr/trans_state_trails_minnesota/metadata/metadata.html

Metropolitan Council – Metro Transit. “Transit Stops.” March 3, 2018. Distributed by MnGEO. ftp://ftp.gisdata.mn.gov/pub/gdrs/data/pub/us_mn_state_metc/trans_transit_stops/ metadata/metadata.html

U.S. Census Bureau. “CB1500CZ11 – ZIP Code Business Statistics: Total for Zip Code.” 2015 County Business Patterns. https://www.census.gov/programs-surveys/cbp/data.html

U.S. Census Bureau. “DP02 – Total Civilian Noninstitutionalized Disability Status by ZCTA” 2012-2016 American Community Survey, 5-Year Estimates. https://factfinder.census.gov/ bkmk/table/1.0/en/ACS/16_5YR/DP02

U.S. Census Bureau. “DP03 – Selected Economic Characteristics by ZCTA” 2012-2016 American Community Survey, 5-Year Estimates. https://factfinder.census.gov/bkmk/table/1.0/ en/ACS/16_5YR/DP03

U.S. Census Bureau. “DP05 – Race by ZCTA” 2012-2016 American Community Survey, 5-Year Estimates. https://factfinder.census.gov/bkmk/table/1.0/en/ACS/16_5YR/DP05

U.S. Census Bureau. “S0101 – Age and Sex by ZCTA.” 2012-2016 American Community Survey, 5-Year Estimates. Population by ZCTA5. https://factfinder.census.gov/bkmk/table/1.0/ en/ACS/16_5YR/S0101

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U.S. Census Bureau. “S0801 – Commuting Characteristics by Sex by ZCTA.” 2012-2016 American Community Survey, 5-Year Estimates. https://factfinder.census.gov/bkmk/table/1.0/ en/ACS/16_5YR/S0801

U.S. Census Bureau. “S1701 – Poverty Status in the Past 12 Months by ZCTA.” 2012-2016 American Community Survey, 5-Year Estimates. https://factfinder.census.gov/bkmk/ table/1.0/en/ACS/16_5YR/S1701

U.S. Department of Agriculture. Economic Research Service. “Food Access Research Atlas by Census Tract.” 05/18/2017 update. https://www.ers.usda.gov/data-products/food-access-research-atlas/download-the-data

SPACE Scoring

April 26, 2018


1 point Within 1 mile of a K-12 school SCHOOL = YES




FOOD_05MI < 75.0

1 point Defined as an “area of concern” by MPCA environmental justice

EJ_MPCA = YES





1 point Percent of population Native American > MN average

PCT_NAI > 1.0


1 point Within an urban area, percent of total population in poverty > 25.0

URBAN ≠ RURAL and POV_ALL > 25.0

1 point Unemployment rate > MN average UNEMPLOY > 4.9

1 point Percent of workers with access to zero vehicles > 0.0

PCT_VEH0 > 0.0

1 point Percent of workers commuting by bicycle > 0.0 PCT_BIKE > 0.0

1 point Percent of workers commuting by transit > 0.0 PCT_TRNST > 0.0

1 point Percent of workers commuting by walking > 0.0 PCT_WALK > 0.0

1 point Percent of workers with a commute less than 15 minutes > MN average

MIN_0014 > 31.3


DSP_RISK > 4

SPACE Score = 100 ×1

19× ∑ POINTS

Score Total Miles Trunk Highway Miles Hexagons

0 0 .0 % 0 .0 % 0 .0 %

1 to 15 578 .4 % 30 .2 % 16,898 3.2 %

16 to 30 13,735 9.4 % 1,259 8.8 % 59,901 11.5 %

31 to 45 66,508 45.4 % 5,946 41.6 % 237,177 45.4 %

46 to 60 57,029 38.9 % 5,972 41.8 % 196,612 37.6 %

61 to 75 8,110 5.5 % 1,024 7.2 % 11,499 2.2 %

76 to 90 549 .4 % 67 .5 % 176 .0 %

91 + 0 .0 % 0 .0 % 0 .0 %

How to Score a Project using SPACE Hexagons 07/19/2018 A. Prepare Your Location Data Ensure the projection is NAD 1983 UTM Zone 15N. We will be using geometry calculations so it is important that the projection matches the half-mile hexagon shapefile. If the projection needs to be changed, use the “Project” tool under ArcToolbox > Data Management Tools > Projections and Transformations > Project.

Ensure your projects have a unique identifier for each project. If one is not available, you can create one ad hoc using the FID.

B. Use Identity on Segments Add the MN_HalfMile_Hexagons shapefile. Use the “Identity” tool under ArcToolbox > Analysis Tools > Overlay > Identity.

C. Create Lengths for Aggregating Open attribute table. Add a [double] field for the length of roadway within each hexagon. Calculate Geometry for the field using a small length (e.g. meters or feet). Using the smallest units helps avoid very small distances being lost when the decimals are rounded.

D. Join Scoring Characteristics The field “hexid” is unique to each hexagon. Using this key you can link the characteristics/scoring table back to the Identity Shapefile. E. Create Length-weighted Field Add a [double] field for the length-weighted score. Calculate by multiplying score and segment length.

F. Aggregate to Original Projects Using the “Dissolve” tool under ArcToolbox > Data Management Tools > Generalization > Dissolve. Set the “Dissolve _Field(s)” to be your unique ID per project; set the “Statistics Field(s)” to be both the scoreLEN and HEXLEN as a sum. Leave the “Create multipart features (optional)” checked—this changes the way the project is mapped but makes the math work out correctly.

G. Calculate a Final Project Score Open the Attributes Table for the final dissolved projects. Add a [double] field for the final score. Calculate by dividing the length-weighted score by the total length. By using the ROUND function, you can eliminate insignificant differences in scores. The syntax is as follows:

ROUND( [number] , [number of decimal places] )

Statewide Bicycle/Pedestrian Suitability Analysis

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