Bike share programs were invented in the mid 1960’s and have come a long way from their relatively humble beginnings. Most modern programs require the swipe of a membership card and users are granted access to a valuable method of transportation that can assist in their commute (DeMaio, 2009). By integrating bicycles with existing public transportation networks, a single membership card can create a diverse network of transportation options that cohesively work together to improve mobility (DeMaio, 2009).
When determining optimal locations for Bike Share terminals many factors are evaluated. First, pre-existing bicycle infrastructure such as bike lanes are one of the most important factors that must be taken into consideration. Established bike paths ensure a higher level of safety and efficiency when travelling between terminals (Midgley, 2009). Secondly, access to public transportation terminals, such as bus stops, is ideal to keep travel times short and allow widespread accessibility within a community (Ricci, 2015). In addition, evaluation of other urban factors such as recreation centers, retail stores, population density, and office buildings need to be considered (Kabak, Erbas, Çetinkaya & Ozceylan, 2018). All factors listed above and then subsequently ranked against one another based on their relative importance in that city.
Geographic Information System (GIS) software plays a critical role in visualizing the multiple layers of geo-spatial data that exist within a given city (Kabak et al. 2018). GIS analysis allows users to constructively compare the many physical and spatially relevant variables that come together to influence which sites are optimal for a Bike Share terminal.
All cities have a different functionality and array of public data for speculation therefore, data must be chosen in order to tailor the strengths and weaknesses of that particular city. Typically, there is a cross-over of applicable factors in every city however, factors with high importance in one city may be irrelevant in another. Based on the relevant literature, only the most important criteria to the City of Guelph in particular was selected for further analysis. Intrinsic knowledge of the area is required in order to produce relevant results that have real-world implications.
Purpose of Research
The overall purpose of this research is to develop a GIS based model that incorporates demographic, spatial and geo-physical factors to identify optimal locations for bike-share terminals across the city of Guelph.
Objective 1: Define specific factors and variables that influence the locations of bike share terminals.
Objective 2: Develop a GIS-based MCE model using network analysis based on criteria identified in Objective 1.
Objective 3: Apply the GIS-based model to the City of Guelph to identify several optimal locations for bike terminals.
Objective 4: Evaluate the strengths and limitations of the model as it applies to the City of Guelph.