Building a Transportation Database WMATA Rail Station Mapping Project 3/18/2014

2  The Washington Metropolitan Area Transit Authority (WMATA, a.k.a. Metro) serves a 1500 sq. mile area that includes:  5 Virginia Cities and Counties  Arlington County  Alexandria  Fairfax County  Fairfax City  Fall Church  2 Counties in Maryland:  Montgomery County  Prince George’s County  Washington, D.C.  Metro serves a population of approximately 3.5 million with 91 Rail Stations. Metro Background

3 What exactly are we capturing for WMATA?  Station Interior  Station Exterior  Parking Garage  Space object relationships  Standard codes and names  Location Hierarchy Rail Station Data Model

4  Our Primary Objective was to capture spatial features for each rail station in the form of a geodatabase.  Step 1: Review source data provided by WMATA. i.e. CAD drawings, emergency maps, and as-built files.  Step 2: Field verification of station features as compared to existing data resources.  Step 3: Geo-reference source data to be used for digitization.  Step 4: Digitize and attribute spatial features defined by WMATA custom Schema  Step 5: Quality Control check each station database to ensure all feature classes that apply have been captured and attributed. Project Scope

5  What JMT Started with  WMATA maintains a library of as-built engineering drawings and for all rail stations. This data is in various formats.  As-built PDF documents  As-built TIFF images  Station Design Documents in the form of AutoCAD Drawing files  Emergency Maps in the form of PDF Documents for reference  Each set of documents where reviewed to determine its relevance, accuracy, ability to be georeferenced for digitization. Step 1 – Review Source Data

6 Source Data As-built PDF’s and CAD print outs used for geo-referencing

7  Station features to be captured in the geodatabase where field verified by a member of the JMT team.  Any information not found in the source data was to be recorded on the field visit to the station. Step 2: Field Verification

8  Once the data from the field and the relevant source drawings where collected the data was geo-referenced to a custom coordinate system created and used by WMATA’s GIS department. Step 3: Geo-reference Source Data

9 RAIL STATION INTERIOR – Mezzanine – MezzanineZones Kiosk FareGateArea FareCardVendingMachineArea PaidArea OpenAccessArea Step 4: Digitize & Attribute Indoor Features – Rooms – RoomDoor – Passageway – Platform – PlatformEndGate – ElevatorBank – EscalatorBank – SafetyWalk – ServiceRoomFloor – Stairways – Trackbed

10 RAIL STATION EXTERIOR – StationEntrance – Pavilion – Busbay – PassengerWaiting Area – KissRide – PedestrianBridge – PedestrianWalkway – SideWalk – ParkingLot – EntranceGate – Landscape – Lawn – Roadbed – OutstationStructure – OffsiteFacility Step 4: Digitize & Attribute Outdoor Features PARKING GARAGE – GarageRamp – ParkingGarage – ParkingGarageLevel

11  The geodatabases were then reviewed internally by JMT and turned over to WMATA as each station was completed.  After WMATA received each station various GIS tools where used to verify spatial accuracy  WMATA also created a matrix spread sheet used to help check each individual feature class and its attributes. Step 5 – QA/QC

12  Station Maps for Customers  Departmental asset tracking, and equipment location within the organization.  Maintenance and Facility management:  Tracking maintenance issues  Inventory of facilities  Space utilization  Emergency preparedness and response:  Define Emergency Evacuation Plan  Incident and crime location tracking What are the Benefits?

13 Data created in 2D

14  Emergency Exits and Rescue Areas  Rail Station Asset Mapping: e.g., camera, detection device, emergency equipment, etc.  3-D Access Paths and 3-D Rail Station Mapping  3-D Routing  Rail Station Evacuation Modeling The Future of this Dataset

15  “Rubber sheeting” tiff images often threw off what little amount of scale was retained in the scanning of the original as-built drawings.  Solution: Scratch lines using bearing and distances already on the as-builts where drawn in order to get proper scale of station features being digitized.  Features not previously defined in scope or data schema where discovered during source data review or field visit.  Solution: Domain values for feature class attributes where constantly being updated, on occasion new feature classes where added to schema.  As each portion of the station was being digitized it quickly became cumbersome to keep track of different levels within the stations as many where directly above and below each other.  Solution: Within the schema a series of attributes where created that allowed us to isolate the portion of the station being digitized with a simple definition query.  As station data began filtering in to the client different departments within the organization realized the usefulness of the geodatabase being created and began requesting additional assets or features to be captured.  Solution: Requests where filtered by the WMATA Project manager and a decision was made on whether it was within the scope of the statement of work or beyond it and set aside for future consideration. Lessons Learned

16 Thank You! Additional Resources Washington Metropolitan Area Transit Authority:

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