Natural barriers facing female cyclists and how to overcome them: a cross national examination of bikesharing schemes

Data and software for examining the role of natural barriers in over 200 million trips from bikesharing data from 10 cities. The data is integrated with weather data, gradient data, and sunrise/sunset data and examined by gender (male / female self-reported) to check for significant differences between gender using Generalized Additive Models (GAMs).