On the Influence of Land Use and Weather in a Station-based Bike Sharing System

Abstract

This paper investigates the impact of weather conditions and land use on the station-based bike sharing system StadtRAD in Hamburg, Germany. Using k-means clustering, the study identifies five distinct station clusters, revealing different daily usage patterns. Results indicate that land use and proximity to transit stations significantly influence station clustering. Weather impact analysis reveals a decrease in bike demand during precipitation and increased demand on warmer days. The impact of weather is higher at stations associated with recreational areas and on weekends. Overall, the study provides valuable insights into the interplay between weather, land use, and bike sharing patterns, consistent with existing literature.