Integrating RS into Transportation Information Systems

1. Integrating RS into Transportation Information Systems Val Noronha University of California, Santa Barbara

2. Why this engineering stuff? • Methodological research • DOT as customer: GI-science brings operational efficiencies • Academics (social scientists) as end-users: facilitates DOT data, e.g. access, safety • Hands across the sea: idea exchange

3. Environment Infrastructure Flows Hazards     4 universities 4 TAPs Background U.S. DOT — NASA Partnership Transportation Legislation “TEA-21”

4. NCRST Philosophy • Rapid evolution of research into commercial products, practice • User consultation and outreach • Partnerships: industry, international

5. Needs analysis Sensor technology Education & outreach Image processing tech Analysis/process model Data models, communication Research Production Line Problem Sensor Decision/solution Image processing Data integration Data management

6. NCRST—Infrastructure • Asset management (esp. location referencing) • ITS • Corridor/facility location • Security

7. C E N T E R L I N E M A P P I N G

9. TIGER USGS 1:24K Design CAD GDT Navtech State, local State, local DOT Mapquest ITS Engineering CVO/Logistics Centerline databases — families RS RS RS Producers Users

10. Early Thinking • RS is not a monolithic solution; many types of imagery  many approaches • No centerline solution is the “right” answer for all needs; each addresses a niche • scale • rural vs urban • Initial plan: validate RS with GPS

11. Material classification Edge detection Imagery Resources AVIRIS Spectral resolution Landsat TM IKONOS Soft copy photogrammetry Spatial resolution

13. Lessons Learnt • There are many approaches • No RS centerline solution is the answer to all our needs; each addresses a niche • Manual process with some automation, or largely automated process with some user intervention

14. The GPS Challenge

15. GPS Results — lane resolution

16. GPS for Hwy Ops Hi end  Lo end compatibility

18. Centerlines from RS — conclusion • RS not a fully automated solution … yet • Augments other methods (e.g. GPS) effectively, esp. visual verification • Good for small areas: 1:5K soft-copy photogrammetry • Good for large areas, 1:50K to 1:100K … global databases, sustainable policy, etc • Research is promising, worth pursuing

19. TIGER USGS 1:24K Design CAD GDT Navtech State, local State, local DOT Mapquest ITS Engineering CVO/Logistics Centerline databases — families RS RS RS Producers Users

20. Data exchange support • UNETRANS — with ESRI • NSDI Road Identification Standard • NCHRP 20-27(3) — led by UW • Inter-state partnerships

21. UNETRANS

22. A I R P O R T P L A N N I N G

23. Airport Planning • FAA priorities • 3-D Airport Layout Planning • 3-D Airport Approach Planning • LIDAR projects • St Petersburg, FL • Plant City, FL

24. 3-D Airport Approach Planning

27. New Projects • Security of infrastructure • Corridor alignment • Pavement condition (hyperspectral) • LIDAR and photogrammetry

28. OrbImage — Imagery Access Virginia — widening Rte 1 from Woodrow Wilson bridge to Dale City

29. Tetra Tech — multi-modal transfers Land use classification — methodology test

30. Tetra Tech — multi-modal transfers Counting containers — methodology development

31. Tetra Tech — multi-modal transfers Washington Blvd corridor ...

32. Tetra Tech — multi-modal transfers … objects in 15 cm imagery

33. Boston — Big Dig impacts

34. Keep in touch! www.ncgia.org • CSISS • VITAL • NCRST