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Predict bicycle ridership after correcting bias in crowdsourced bicycling data from Strava using LASSO & Poisson Regression.

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Avipsa1/Strava_Bias_Correction

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Strava_Bias_Correction

The code in this repository is used to predict bicycle ridership after correcting bias in crowdsourced bicycling data from Strava using LASSO & Poisson Regression.The study area is Maricopa County, Arizona. The predictions are based on bicycle counts from 2016 provided by the Maricopa Association of Governments. We predict overall annual average daily bicyclist count for the city of Tempe & categorize the streets into 5 classes as shown in the map below.

Bias-corrected AADB Prediciton map for the city of Tempe in 2016

Please cite the following paper if you use the code.:

Roy, Avipsa; Nelson, Trisalyn A.; Fotheringham, A. S.; Winters, Meghan. 2019. "Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All Bicyclists." Urban Sci. 3, no. 2: 62. (https://doi.org/10.3390/urbansci3020062)

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Predict bicycle ridership after correcting bias in crowdsourced bicycling data from Strava using LASSO & Poisson Regression.

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