Better urban planning can help save our rivers and the Chesapeake Bay—by reducing this region’s future impervious surfaces by 20%. Here’s why.
As many Washingtonians know, the Chesapeake Bay needs help. Dead zones and algae blooms appear every summer which destroy aquatic life in the Bay and threaten fishing, swimming, and economic health. A major contributor to this problem is rainwater runoff from paved roads, parking lots, and roofs. These are called “impermeable surfaces”. In contrast, permeable (or pervious) surface is one through which liquids are able to pass.
Grassy fields, woodlands and farmlands are excellent examples of this: rainwater or snowmelt soaks into the ground, pollutants in the water are filtered naturally, and excess water travels underground to streams and eventually (in the Washington region) the Chesapeake Bay.Rainfall that falls on impervious surfaces like paved roads, parking lots and roofs “runs off” unfiltered making its way to the Chesapeake Bay—along with nitrogen and sulfur oxides from vehicle emissions, motor oil, and road salt residue.
Figure 1 – Map of impermeability throughout the region with overlaid jurisdictional boundaries and Metrorail system for reference. Note the concentrations of highly-impermeable surfaces in central D.C., and at other activity centers like Dulles.
Screenshot of Metrorail rider income by station visualization. Click image for full interactive version.
The biggest overall difference between our work and that of the MIT group is higher household incomes at end-of-line stations on the eastern side of the region. These stations, while located in lower income areas, have large parking facilities that draw commuters from all over the region and beyond. Read more…
Learn about the travel patterns of Silver Line riders in rich, interactive detail with this new tool.
Click on the dashboard below to see where Silver Line rail riders are going, coming from, and by time of day and day type. This is simply a visualization of the October 2014 rail ridership data we recently posted. What patterns do you see? What jumps out at you?
I was invited to present a wide variety of data visualizations featured on the blog at a recent meeting of transportation techies.
I had the honor of being invited to present at the 2nd meeting of the Transportation Techies Meetup group, Metro Hack Night on January 2, 2014. I used this opportunity to illustrate some of the data visualizations I’ve developed using Metro data and talk a bit about the technology behind them.
On-Street Bike Parking in Buenos Aires. Photo by the author.
I spotted this cool on-street bike rack in the trendy Palermo neighborhood of Buenos Aires. It says “One car = ten bikes”. It’s a very cool, visual way of providing bicycle parking in a neighborhood with narrow sidewalks and heavy pedestrian activity that also educates the driving public on the efficiency of travel by bicycle and the need for on-street bike infrastructure.
Please try out our draft Greenhouse Gas Calculator, which asks for a starting and ending address, and then routes your trip via automobile and transit and displays the route and GHG emissions differences.* We are soft-launching this tool to crowd-source the quality assurance process and assess its usefulness.
What other features would you like to see? Did the tool accurately portray your travel choices? What is the difference in GHGs between driving and transit for your most frequent trip?
* Note on GHG calculations: the tool uses the Google Directions API to route your trip using both automobile and transit. The Google Directions API response includes each step of the journey, including mode and distance. We apply standard rates of GHG emissions per mile to the different modes used. As an added bonus, if your transit trip includes walking, we toss in an estimate of the calories you burned too!
A handful of end-of-line stations’ parking facilities are doing the lion’s share of extending the reach of Metro across the region, while parking at most other stations primarily serves nearby residents.
Parking at rail stations is traditionally thought to extend the geographic reach of transit in the region, by giving longer-distance commuters a way to access a rail station. Based on an analysis of Metro parking customers’ origins, a handful of large end-of-line Metro parking facilities perform this function, but most Metrorail parking facilities do not. Nine Metrorail stations are capturing 70 percent of all customers who drive from more than three miles to park-and-ride, while the 26 other Metro parking facilities primarily serve the surrounding neighborhoods.
Our map of parking customers’ origins showed how far Metro’s reach extends across the region. Now, this map shows the dominant station among Park & Ride customers, by half square-mile, for a typical weekday:
Map of dominant station of Park & Ride customers, highlighting each station’s “catchment area.”
Areas where there is no clear primary station are shaded gray: for example, the dividing line between Southern Ave. and Branch Ave. stations. The dominant station is shown, regardless of how many Park & Ride customers there are for a square. There is some noise in this data, but two “flavors” of parking emerge: Read more…
Metro planning staff have been working to showcase Metro data in new and unique ways. We recently posted a visualization in a calendar format that displayed 9 years of rail ridership in one graphic. We are currently working on animations of ridership data as well. Below is our first volley into that arena, a visualization of one day’s worth of station-level activity in 15-minute intervals.
Before hitting play, please note the following:
The video is available in high definition (720p), which is the recommended viewing resolution.
The dots are sized according to total station volume (entries plus exits) per 15-minute interval.
The color of the dot represents what percent of the volume is entries vs exits. Magenta dots are 100% exits, blue dots are 100% entries, and purple dots are 50/50, with other colors representing ratios between these three.
The visualization is of data from April 10, 2013, which hit the 4th highest ridership mark that day. A combination of cherry blossom peak bloom and two sporting events ratcheted ridership up to 871,000 for the day, compared to an average weekday ridership of around 750,000. Note the high level of activity at the Smithsonian station all day long, and big dots that grow and shrink as the sports games begin and then end near Gallery Place and Navy Yard-Ballpark stations.
What other unique activity can you spot in this animation? What other types of animations of Metrorail and Metrobus would be informative?