Proximity to transit, especially high-quality, frequent, high-capacity rail, increases property values, attracts development and provides mobility choices. Property values are higher near Metro’s high-quality, high-frequency, high-capacity services, and deliver an incremental increase in total tax revenue to the Compact jurisdictions.
- Property taxes on land around Metrorail stations generate $3.1 billion annually in revenues to the jurisdictions.
- Of these revenues, $224 million is extra value that would not exist without Metro. This amount is equivalent to providing the following public services.
PlanItMetro saw great interest in our last full data download of O/D data last year. We thought we’d provide an update with data from October of 2012. This enhanced data download contains the following files:
- Full O/D trip data MS Access, including service type (weekday, Saturday, Sunday Special), travel period (AM Peak, mid-day, etc.), entry hour, Origin Station, Destination Station, rider class (full fare or discounted), media type (SmarTrip vs paper farecard), fare instrument type (stored value vs benefits vs pass), average travel time and average number of trips.
- Subset of O/D trip data “No Details” CSV, includes all trips like the first file above but doesn’t include details on rider class, media type or fare instrument
Download either of these data files and let us know what you find!
Sample Bluetooth Sensor
Metro, in conjunction with Traffax, Inc., recently hosted a Bluetooth traffic monitoring test at Fort Totten station. Bluetooth technology has been used for years now, for monitoring vehicular traffic. Specifically, it has been used to provide travel time and origin-destination data, mostly in vehicular settings. Some pedestrian monitoring has been tested as well.
For Metro’s recent pilot, Bluetooth traffic monitoring was used to study pedestrian movements within a multi-level environment. The hope was that the Bluetooth data captured could tell stories about pedestrian flow within the station (including vertical movement), the train dwell times, train volumes, and the transfer rate between the Yellow/Green and Red lines. The latter is an area that WMATA is most interested in, since it is difficult to predict how people will ride Metro when given options. In this case, do people prefer transferring between Red and Yellow/Green at Fort Totten or at Gallery Place? This kind of data would make it easier for WMATA’s planning staff to better serve its customers by understanding true crowding levels on trains at peak load points.
It was estimated that 1 in 20 passengers’ movements would be captured in the pilot. The Bluetooth data sensors were placed in backpacks that Traffax employees were wearing. This initial data collection test will be used primarily to develop appropriate methods for analyzing such data, and to see what potential the data has for WMATA.
Please note that no personally identifiable information can be captured by detecting Bluetooth signals, which is the electronic equivalent of viewing license plates. Read more about privacy and Bluetooth on the Traffax website.
Stay tuned for more info!
Metro planning staff understand that a picture is worth at least a thousand words, and often more. (And that a video is worth 1000 * 30 words per second.) As such, we are always looking to increase our ability to create compelling graphs, charts and video simulations.
Sample image of the Metrorail Ridership Visualization. Click the image to open the viz in a new window.
Metro planning staff adapted this code to create a visualization of Metrorail ridership data from 2004 to the present. (Link opens in new window.) Here’s how it works:
- Each year is a horizontal stripe, sectioned off into months that go across. Both years and months are labeled.
- The days within each month are transposed, so start at the left and read down, then move right. In the sample image, the leftmost column of January 2004 is the first week, with Thursday January 1 being the darkest red square. A graphical example is also displayed in the legend at the top of the visualization.
- Each day is colored according to the ridership on that day, with darkest red being the smallest range (0 to 99,999) and the darkest green being the highest range (greater than 1,000,000).
- If you move your mouse pointer over any individual day, a small “tool tip” appears showing the date and the ridership for that day, rounded to the nearest 1,000.