Transit users and STB readers use – and like to use – route maps. Routes are tangible, and are how we think when we actually use transit. This post uses some geographic analysis – focused on population and walking access – to show more of the big picture.
In April Metro recommended several phases of service cuts, for a total of about 16% of current service hours, corresponding to the estimated shortfall revenue following the defeat of county Proposition 1. It estimated loss of existing riders (10.8M rides – about 10%). This is indeed a key metric but I’ve not found quantitative answers to another seemingly basic question: what effect would the full set of recommended Metro cuts have on residents’ access to service (measured by 1/4-mile walking distance to service stops)?
So I’ve built some tools marrying Metro service details with a geographic information system (GIS). Here’s a sample map showing areas of 15-minute frequency service during commute hours, after the cuts (green) overlaid on current (orange). Compare this to route-oriented maps from Metro and Oran Viriyincy’s remarkable before-and-after route frequency map.
Translating this information to population impact for Seattle (county-wide to come soon):
|Service hours cut||Loss of served population|
|30-minute freq.||15-minute freq.|
On these results, Metro’s planning, following the Service Guidelines, looks to be quite effective, including restructures that increase the population that can be served with limited revenue.
What’s next? This is a start and there are many ways we can extend this information:
- Evaluate possible outcomes from the County Council’s decision to defer the final 200,000 hours in cuts (those after February 2015).
- Evaluate the impact to low-income population
- Results for the complete Metro service area (not just Seattle)
Other ideas in the hopper:
- Additional service measures: bus crowding and trip duration
- Evaluate service separately to key destinations: Downtown, UW, Bellevue Transit Center, etc.
- Include further demographics: employment, land-use indicators, and others.
Please comment to suggest further improvements! More maps are below.
The first 2 maps show all the areas within ¼ mile of bus stops that currently have at least every 30 minutes – with and without the stops. Then the area served is calculated from the orange region, and the population served is calculated from population densities (right map) using 2010 census data.
|Area with 30-minute peak-hour frequency – with and without stops shown||Population density|
The maps below show service today, and after all recommended cuts to meet 16% reduction of service hours:
|Key: Green – after cuts – overlaid on Orange – current|
|30-minute frequency||15-minute frequency|
- Current service details, stop locations, routes, and schedule are largely derived from Metro’s published General Transit Feed System data
- Post-cut service details are outlined in some detail here. Many of the restructures amount to splicing together parts of existing routes, so I could project the likely stops on restructured routes accordingly. This left a small amount of “new” routing, which was estimated manually using existing stop locations.
- Service analysis is around stops. The schedule at each stop is constructed from the service details (above), including the frequency of service at different periods of the day. Routes can be analyzed for availability, frequency, and (scheduled) trip duration of service to downtown, the UW, and other areas. These analyses use a handful of small programs. No doubt similar analysis is done for tools such as Walkscore’s transit analysis.
- Map development is done with Q(uantum)GIS, an open-source graphical information system compatible with ArcGIS (the industry standard). Information from the Service Analysis (above) is provided as a table keyed to bus-stops. For a particular stop, the area served by that stop is then assumed to be a ¼-mile radius circle. Population analysis is based on 2010 census block data. Further demographic analysis can be done as additional GIS-oriented data are incorporated.
As no doubt clear already, this is NOT a professionally developed nor commercial project (by contrast with Walkscore or OneBusAway, for example) – my aim is to conceive and demonstrate measures for policy decisions. If you are aware of similar or overlapping tools and analysis, please share – I and other readers would likely find value!