20230927
06043200
1.0
FALSE
Server=DOTICSQLT31; Service=sde:sqlserver:DOTICSQLT31;APPLICATIONINTENT=READWRITE;MULTISUBNETFAILOVER=YES; Database=TIMS; User=TIMS; Version=dbo.DEFAULT
ArcSDE Connection
TIMS.WGIS_WALKBIKEOHIO_DEMAND
002
-9442153.682500
-8963301.634100
4636574.818000
5210110.140500
1
Projected
GCS_WGS_1984
Linear Unit: Meter (1.000000)
WGS_1984_Web_Mercator_Auxiliary_Sphere
<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'><WKT>PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem>
UpdateSchema "CIMDATA=<CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.2.0'><WorkspaceConnectionString>ENCRYPTED_PASSWORD_UTF8=00022e682b696d5451497961445563494e6b664f7a4b2f4958484c767432362b6f53495a7a41524e63473832476c513d2a00;ENCRYPTED_PASSWORD=00022e68627a793245554e6943656f4a70755954423861753143356f30535537656d486a6959473876704f596831493d2a00;SERVER=DOTICSQLT31;INSTANCE="sde:sqlserver:DOTICSQLT31;APPLICATIONINTENT=READWRITE;MULTISUBNETFAILOVER=YES";DBCLIENT=sqlserver;DB_CONNECTION_PROPERTIES="DOTICSQLT31;APPLICATIONINTENT=READWRITE;MULTISUBNETFAILOVER=YES";DATABASE=TIMS;USER=TIMS;VERSION=dbo.DEFAULT;AUTHENTICATION_MODE=DBMS</WorkspaceConnectionString><WorkspaceFactory>SDE</WorkspaceFactory><Dataset>TIMS.WGIS_WALKBIKEOHIO_DEMAND</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><EnableEditorTracking><creator_field>created_user</creator_field><creation_date_field>created_date</creation_date_field><last_editor_field>last_edited_user</last_editor_field><last_edit_date_field>last_edited_date</last_edit_date_field><add_fields>TRUE</add_fields><record_dates_in>UTC</record_dates_in></EnableEditorTracking></workflow></operationSequence>
20240503
12041800
20250814
12150500
625000
5000
FGDC
Microsoft Windows 10 Version 10.0 (Build 19045) ; Esri ArcGIS 13.2.0.49743
Active Transportation Demand
Active Transportation Demand
1
-84.820310
-80.518709
42.327140
38.403430
Active transportation planning aims to provide communities safe and convenient access to home, work, school, recreation, and transit via walking and biking. This dataset contains composite scores for active transportation demand and need. Scores are derived from quantifying factors that generate bicycle and pedestrian movement, and can be used to inform and prioritize. Factors considered in demand analysis include: employment density, retail employment density, population density, park density, presence of existing active transportation, presence of colleges/universities, and poverty levels. Scores are applied at the geographic level of census block group. Date created: April 2020. For more information, visit: transportation.ohio.gov/wps/portal/gov/odot/programs/walkbikeohio
AT_WalkBikeOhio_Demand
MapServer
ODOT Office of Statewide Planning & Research
Enterprise Geodatabase Feature Class
dataset
EPSG
6.18.3(9.3.1.2)
9472
Simple
FALSE
9472
TRUE
FALSE
TIMS.WGIS_WALKBIKEOHIO_DEMAND
Feature Class
9472
STATEFP
STATEFP
String
2
0
0
State FIPS Code
COUNTYFP
COUNTYFP
String
3
0
0
County FIPS code
TRACTCE
TRACTCE
String
6
0
0
Census Tract
BLKGRPCE
BLKGRPCE
String
1
0
0
Census block group number
NAMELSAD
NAMELSAD
String
13
0
0
Translated legal/statistical area description and the block group number
MTFCC
MTFCC
String
5
0
0
MAF/TIGER feature class code
FUNCSTAT
FUNCSTAT
String
1
0
0
Functional Status
ALAND
ALAND
Double
8
38
8
Land area
AWATER
AWATER
Double
8
38
8
Water area
INTPTLAT
INTPTLAT
String
11
0
0
Latitude of the internal point
INTPTLON
INTPTLON
String
12
0
0
Longitude of the internal point
GEOID2
GEOID2
Double
8
38
8
POP_DENSITY
POP_DENSITY
Double
8
38
8
Density of population the given zone.
EMPLOYMENT_DENSITY
EMPLOYMENT_DENSITY
Double
8
38
8
Density of emloyers in the given zone.
RETAIL_DENSITY
RETAIL_DENSITY
Double
8
38
8
Density of retail employment in the given zone.
COMMUTE_BIKE_WALK
COMMUTE_BIKE_WALK
Integer
4
10
0
Average combined commute times for biking and walking.
POVERTY_AT_BELOW_200
POVERTY_AT_BELOW_200
Integer
4
10
0
Population at or below 200% of the poverty line.
TOTAL_NUMBER_OF_COLLEGES
TOTAL_NUMBER_OF_COLLEGES
Integer
4
10
0
Number of colleges and or universities.
PARK_DENSITY
PARK_DENSITY
String
255
0
0
Density of park area, expressed in acreage per zone.
RACE
RACE
Integer
4
10
0
Population considered to be part of a minority group.
YOUTH
YOUTH
Integer
4
10
0
Population under the age of 18.
POVERTY
POVERTY
Integer
4
10
0
Population considered to be in poverty.
EDUCATION
EDUCATION
Integer
4
10
0
Population without a high school diploma.
LIMITED_ENGLISH_PROFICIENCY
LIMITED_ENGLISH_PROFICIENCY
Integer
4
10
0
Population with limited english proficiency.
SENIOR
SENIOR
Integer
4
10
0
Population over 64 years old.
MOTOR_VEHICLE_ACCESS
MOTOR_VEHICLE_ACCESS
Integer
4
10
0
Population with access to a motor vehicle.
POPULATION_SCORE
POPULATION_SCORE
Integer
4
10
0
Score for poulation density indicator. Score is broken into quantile of 1-5 and 0 for no score.
EMPLOYMENT_SCORE
EMPLOYMENT_SCORE
Integer
4
10
0
Score for employment density indicator. Score is broken into quantile of 1-5 and 0 for no score.
RETAIL_SCORE
RETAIL_SCORE
Integer
4
10
0
Score for retail employment density indicator. Score is broken into quantile of 1-5 and 0 for no score.
POVERTY_SCORE
POVERTY_SCORE
Integer
4
10
0
Score for poverty indicator. Score is broken into quantile of 1-5 and 0 for no score.
COLLEGE_SCORE
COLLEGE_SCORE
Integer
4
10
0
Score for college/university indicator. Score is broken into quantile of 1-5 and 0 for no score.
COMMUTE_BIKE_SCORE
COMMUTE_BIKE_SCORE
Integer
4
10
0
Score for commute walk indicator. Score is broken into quantile of 1-5 and 0 for no score.
COMMUTE_WALK_SCORE
COMMUTE_WALK_SCORE
Integer
4
10
0
Score for commute walk indicator. Score is broken into quantile of 1-5 and 0 for no score.
COMM_BIKEPED_SCORE_Q_NODIVIDE
COMM_BIKEPED_SCORE_Q_NODIVIDE
Integer
4
10
0
RACE_SCORE
RACE_SCORE
Double
8
38
8
Score for minority population indicator. Score is broken into quantile of 1-5 and 0 for no score.
YOUTH_SCORE
YOUTH_SCORE
Double
8
38
8
Score for youth poulation indicator. Score is broken into quantile of 1-5 and 0 for no score.
EDUCATION_SCORE
EDUCATION_SCORE
Double
8
38
8
Score for the population without a high school diploma indicator. Score is broken into quantile of 1-5 and 0 for no score.
LIMITED_ENGLISH_PROFICIENCY_SCO
LIMITED_ENGLISH_PROFICIENCY_SCORE
Double
8
38
8
SENIOR_SCORE
SENIOR_SCORE
Double
8
38
8
Score of adults over the age of 64 indicator. Score is broken into quantile of 1-5 and 0 for no score.
MOTOR_VEHICLE_ACCESS_SCORE
MOTOR_VEHICLE_ACCESS_SCORE
Double
8
38
8
Score of access to a motor vehicle indicator. Score is broken into quantile of 1-5 and 0 for no score.
DEMAND_COMPOSITE_SCORE
DEMAND_COMPOSITE_SCORE
Integer
4
10
0
Composite score of all demand scores.
NEED_COMPOSITE_SCORE
NEED_COMPOSITE_SCORE
Double
8
38
8
Composite of all need scores.
DEMAND_MAPPING
DEMAND_MAPPING
Integer
4
10
0
Score used for mapping the demand for walking and biking.
NEED_MAPPING
NEED_MAPPING
Integer
4
10
0
Score used for mapping the need for walking and biking.
DEMAND_NEED_MAPPING
DEMAND_NEED_MAPPING
String
255
0
0
Composit score used for mapping the demand and need for walking and biking.
PARK_SCORE
PARK_SCORE
Integer
4
10
0
Score for park density indicator. Score is broken into quantile of 1-5 and 0 for no score.
20250814
ODOT Office of Transportation & Economic Development
https://www.transportation.ohio.gov/programs/walkbikeohio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==