MAPPS, the national association of firms in the surveying, spatial data and geographic information systems field, recognized Michael Baker’s Dallas Fort Worth International Airport Asset Data Collection project as the Surveying and Field Data Collection and Overall Project Award winner.
Michael Baker team performed asset data collection at the Dallas Fort Worth International Airport, the second largest U.S. airport by land mass and third busiest in the world. With more than 3 million unique visitors each month and approximately 1,850 flights daily, there is very little downtime to perform data collection around the bustling terminals and active runway surfaces.
The request we received included condition assessment of the Central Terminal Area roadway network on five terminals and 120 lane miles of roadway, using mobile LiDAR, a mapping solution that incorporates advanced mobile laser scanning sensors, cameras, and position and navigation to collect survey-quality data quickly and accurately; Laser Crack Measurement Systems (LCMS), a single-pass, 3D sensor for pavement inspections that uses laser-line projectors, high-speed cameras and advanced optics; and PCI visual inspections of two 13,401 foot long runways, 17C/35C and 17R/35L.
A second contract extension involved expanding the scope of PCI, mobile LiDAR and LCMS to the entire airfield to include the majority of the taxiways, high-speed exits and the hold pads. This extension also included a subsurface condition investigation that was conducted on runway 17C/35C, utilizing ground penetrating radar (GPR), a nondestructive imaging method that uses radar pulses to image below the pavement surface, and soil testing of the runway subgrade.
Our innovative one-vehicle solution collected data along all roadways comprising DFW’s landside area, and 95 percent of all airfield surfaces including: runways, taxiways, airfield roads and aprons. In total, they collected data on more than 1,300 linear miles on DFW grounds – sometimes requiring around-the-clock collection and multiple crews to maintain schedule without impacting airfield operations.
The collection system included sensors that blanket a 235-meter-wide collection swath with up to 1.2 million laser shots per second – each to survey-grade accuracy. The system also includes four five-megapixel digital cameras and a 360° spherical camera for capture of high-resolution digital images suitable for attributing features and QA validations. While nighttime operations limited the use of cameras on airfield surfaces and some terminal areas, minimal re-collections during daylight hours along a single path provided an effective means of gathering photography and minimally impacting operations.
Using the newly acquired mobile LiDAR, ground-based photography, traditional surveying, static scanning and legacy GIS data, Michael Baker’s LiDAR technicians performed feature extraction and populated the GIS database with required features and attributes. The landside features included: road pavement markings, symbols and text, road signs, guardrails, attenuators, curbing, edge of pavement, edge of shoulder, curb inlets and catch basins. Each feature contained attributes defined by the data model.