Proposing Bike Stations for the Future 2016 Public Bike Share (PBS) Project:

My group project consisted of determining different bike stations, for the upcoming public bike share system (Vancouver 2016). We aimed to determine the best locations for these bike share stations based on a hierarchical ranking of relevant criteria. We will be classifying specific bike share station points based on levels of importance to public services. We took various factors into consideration which include, bikeways, roads, universities, community and shopping centres, tourist attractions, parks, and public transport (bus and skytrain routes). We took these factors, and clipped it onto the Vancouver Mask layer, where we began our analysis and adjusting our map in various to make our final product.

How did you organize your team (project management)?
Sourcing data: We will mainly be drawing upon DataBC, the G:Drive, and UofT Census data. In addition, we will consult Tourism Vancouver maps, Translink bus routes, and Vancouver’s open data catalogue.
Parsing and filtering data: Querying for specific land use, normalizing for population density, and clipping the project boundary to outline the city of Vancouver, including Downtown Vancouver.
Creating a hierarchy and applying values to the different types of criteria to determine bike share locations. i.e. – proximity to transit, tourist attractions, parks, etc.

• Manually input polygons to represent tourist attractions by vectoring on top of an aerial map of Vancouver
• Adding buffers to high density layers to represent walkable distance to bike share i.e. – transit, schools, parks
• Measuring spatial distance between layers and features to rationalize bike share station locations.

Manually inputting bike share locations based off value system
Establishing signage points: Final bike share station locations
Interact: Using our classification method to determine which areas require a bike share more than others. By recognizing potential errors or misrepresentations of the data, we will manually edit or input bike share locations based on subjective data. Finally, we will be establishing signage points.

What are some interesting things you learned as a result of the process? For example:

• Some facts about the project?
  • Most ideal locations for the bike share systems were found to be in Downtown Vancouver.
    Upon creating the final map, we discovered interesting hotspots in removed areas away from downtown.
    We prioritized placing most of the bike share locations precisely on the “most important” (red) areas, with higher population density.
    
• Some interesting GIS analysis techniques?
  • We created buffers that were 20m around all the layers, so we could map those specific regions, just so we were aware of the surroundings when when proposing the bike share stations. Because we were focusing solely on Metro Vancouver, all the data that was downloaded had to be clipped to that specific to the project area. Another GIS analysis technique that we used was manually adding in tourist and post-secondary locations. This is because DataBC or any other sources, did not provide us with the data we needed, so we manually plugged them in based on the top 10 found on the Internet. We used signage points to do this, where we would zoom in to the exact location, as it appeared on GoogleMaps.
• Some facts about teamwork / project management approaches and techniques?
  • For the final project, all of my group members including myself made an exceptional amount of effort equally. We all stuck to the times we would meet (outside of lab sessions), and conducted very productive meeting sessions. We uniformly divided up the parts of the project, and would check everyone’s work in order to eliminate redundancy in the report for instance. I was content with the group members, because all the members were fair, and excellent team work was exhibited throughout the course of the final project.
• Some issues or tips around data management on a team?
  • Splitting up the work load evenly amongst group members can be challenging, because when we faced problems with being redundant while writing the report. Sometimes it lead to the some groups members doing more than others, which is where other group members, should take it into account, and try to take on other parts of the project such as editing or submitting.
• Some issues around publicly available data and proprietary data?
  • We took the upcoming PBS system and decided to potentially make the bike share systems based on factors that we assumed would impact the area in which we are studying. DataBC and various other data sharing websites, did not provided all the information that strongly thought would influence where we would position the stations. Examples of these are tourist locations, and post secondary institutions in Vancouver, where we did not acquire the data files online, resulting in us manually adding them onto our maps, while we simultaneously corresponded to GoogleMaps. This was fairly time consuming, and challenging, because any small mistake we would make, had us going through the process all of over again.

Group’s Final Report
Final Project Flow Chart