AY1516 T2 Team WalkThere Methodology
Contents
Methodology
Part 1: Identify Commuter Patterns
This analysis aims to identify commuter patterns of each demographic groups - students, adults and elderly - as each group has differing interests and preferences in the places to frequent at. These patterns are recognized by areas with high volumes of people commuting by bus using the ez-link data. We aim to identify any commonalities where people travel for short distances, with only a few bus stops, within journeys, as well as recognize what are the common places of interests that the various demographic groups frequent at and at what periods of the week.
Our data for this analysis consists of the following:
1.Ez-link transactions
With the support from LARC, we were able to obtain ez-link transactions data from 20 to 26 January 2014. We have selected just a week of data in January 2014 because the travelling patterns for each week in a month are similar and there are neither no public holidays nor school holidays in the selected week for analysis. However, regardless of scaling down the data into just a week’s period, there are still millions of transactions presented. As such, analysis of the data will be further scaled down to grouping the transactions based on demographic profiles, followed by aggregating the timings of transactions to every 15 minutes given that the timings presented come in seconds.
2.Points of interests
Given that the places that each demographic groups frequent at varies due to differing interests and preferences, to include points of interests (POI) in this analysis will be helpful to understand which places attract various groups of people at various periods of the week. With that, our team conclude that POI should be places that serve the primary needs of the people. As such, POI include:
• MRT stations
• Schools (primary, secondary, pre-tertiary and tertiary education)
• Shopping malls
• Sports complex
• Parks
• Childcare
• Community centers
• Shapefiles for the identified POI can be retrieved from data.gov.sg, Openstreetmap, Onemap and LTA Data Mall
Part 2: Identify Gaps in Infrastructure
After conducting the analysis in part 1, various POIs for the various age groups are identified. Certain places will attract a particular age group more and this leads us to question whether these places serve that particular age group well enough?
The second part of analysis involves identifying gaps in the infrastructure within Tampines planning area. Why are people commuting by bus instead of walking? Will safety be compromised if people choose to walk? Or are there roads hindering the connectivity between the point of start with the destination? Thus, the second part of this analysis aims to highlight areas where the time taken to travel by bus is longer than walking and recommend improvements to the current infrastructure to encourage people to walk.
Our data for this analysis consists of the following:
1. Mapping Out Pedestrian Network
We will map out the pedestrian network around the various POIs identified. This data allows us to understand whether pedestrians can arrive at their destinations via walking. This data is available to us on OSM. Furthermore, we will also make use of raster analysis where we will draw a 5m x 5x square over residential buildings. The combination of raster layer and pedestrian network from OSM will allow us to find out the shortest walking path from the origin to the destination.
Besides using raster analysis, we will also make use of other geospatial tools such as pgrouting to allow us to map out the shortest walking path. We will then compare the various walking distance to the distance travelled by the bus and find out the difference. An average walking speed for the different age groups will also be used to find out the time taken if one choose to walk. We will then compare the time taken if one choose to walk to the time taken if one travel by bus.
Work Scope
Literature Study
To understand previous studies on walkability in Singapore and in other countries, and the types of infrastructures that can be introduced so as to be able to make recommendations to improve the connectivity between residential estates and points of interest.
Software Learning
Learn how to use the QGis software, both on the laptop as well as on the mobile phone (to aid data collection)
Data Collection
Ez-link data will be provided by LARC while points of interests data sets are publicly available on Openstreetmap, Data.gov.sg, LTA data mall and Onemap. Pedestrian network will be manually mapped out through conducting site visits and with the integration of road network.
Data Exploration
Ez-link data of one week will be segmented into 3 sections for analysis: student, adult and elderly. Each team members has to identify trends and patterns for each profile groups with the use of analytics tools such as JMP and QGIS.
Geospatial Analysis
Using QGIS, for the following:
• Commuters behaviours throughout the entire one week.
• Map out paths that residents may take from their houses to identified points of interest
• Understand the coverage of street lamps to analyse the safety of walking paths at night. Through measuring the radius of coverage and the height of the lamp post, we can understand how the distribution of the lamp post should be placed.
