20240818
18375400
1.0
FALSE
NWAosmEdgeUID_FC2023
002
https://www.arcgis.com/sharing/rest/content/items/3f8c564979a54757a3c85347f5cf2838/info/thumbnail/thumbnail1771563224721.png
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_UTM_Zone_15N
<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/3.3.0'><WKT>PROJCS["NAD_1983_UTM_Zone_15N",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-93.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26915]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>10000</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26915</WKID><LatestWKID>26915</LatestWKID></ProjectedCoordinateSystem>
20260218
13562700
20260218
13562700
<p style='text-align:center;'>This OSM edge feature layer was developed from a data-driven framework for estimating bicycle ridership across the entire<br />Northwest Arkansas trail network—over 13,000 paved trail segments—using Strava Metro crowdsourced<br />cycling data calibrated against 12 permanent EcoCounter sites. The goal was to give regional active transportation planners<br />segment-level ridership estimates where no counters exist, enabling more informed decisions about<br />trail investment, maintenance prioritization, and network expansion.</p><p style='text-align:center;'><span style='font-size:24px;'><strong>Ridership Modeling in Northwest Arkansas:</strong></span><br /><span style='font-size:24px;'><strong>A Counter-Calibrated, Strava-Informed Machine Learning</strong></span><br /><span style='font-size:24px;'><strong>Framework</strong></span></p><p style='text-align:center;'>Brian Culpepper, Katie Wyatt, Jack Cothren<br />Center for Advanced Spatial Technologies (CAST), University of Arkansas<br />rculpepp@uark.edu<br />February 24, 2026<br />Abstract<br />This study develops and compares multiple approaches for predicting Average Annual Daily<br />Bicycle (AADB) counts across the Northwest Arkansas trail network using Strava Metro crowdsourced<br />data. We evaluate pooled ratio, temporal stratification, trail-type stratification, regressionbased,<br />and combined approaches using Leave-One-Site-Out Cross-Validation (LOSOCV) at 12<br />counter sites (two outlier sites excluded from calibration). The analysis reveals substantial<br />site-level heterogeneity in the Strava-to-counter ratio, with activity features and infrastructure<br />characteristics serving as the strongest predictors of outcome similarity. Results inform the<br />development of a calibrated prediction model that expands AADB estimates to over 13,000<br />network edges, accessible in a dedicated ArcGIS Online (AGOL) site.</p>
CAST
NWA Mobility Modeling
AADB edgeUID output from Random Forest modeling of NW Arkansas; contains 13,163 unique features within two counties. Center for Advanced Spatial Technologies (CAST).
Esri ArcGIS 13.3.0.52636
NWAosmEdgeUID_FC2023
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
File Geodatabase Feature Class
dataset
EPSG
6.11(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
NWAosmEdgeUID_FC2023
Feature Class
0
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
edgeUID
edgeUID
Integer
4
0
0
F23_activity_type
Strava_activity_type
String
8000
0
0
F23_MEAN_fwd_avg_spd_MperS
yr2023_Avg_Fwd_speed_mtrspersec
Double
8
0
0
F23_MEAN_rvrse_avg_spd_MperS
yr2023_Avg_Rev_speed_mtrspersec
Double
8
0
0
F23_SUM_ride_count
yr2023_SUM_ride_count
Double
8
0
0
F23_SUM_ebike_ride_count
yr2023_SUM_ebike_ride_count
Double
8
0
0
F23_COUNT_stravaDATE
COUNT2023_stravaDATE
Integer
4
0
0
osm_id
osm_id
String
12
0
0
code
code
SmallInteger
2
0
0
fclass
fclass
String
28
0
0
name
name
String
100
0
0
jOSMid
jOSMid
Integer
4
0
0
edgeUID_1
edgeUID
Integer
4
0
0
aadb_RF
aadb_RF
Double
8
0
0
ci_lower_RF
ci_lower_RF
Double
8
0
0
ci_upper_RF
ci_upper_RF
Double
8
0
0
ci_width_RF
ci_width_RF
Double
8
0
0
aadb_Ratio
aadb_Ratio
Double
8
0
0
ci_lower_Ratio
ci_lower_Ratio
Double
8
0
0
ci_upper_Ratio
ci_upper_Ratio
Double
8
0
0
edge_class_static
edge_class_static
String
8000
0
0
confidence_static
confidence_static
Double
8
0
0
edge_class_converged
edge_class_converged
String
8000
0
0
confidence_converged
confidence_converged
Double
8
0
0
reliability
predicted_reliability
String
8000
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
20260218