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Integrating RS into Transportation Information Systems

This study explores the integration of Remote Sensing (RS) technology into Transportation Information Systems to enhance operational efficiencies and safety. Methodological research conducted by Val Noronha at the University of California, Santa Barbara, reveals how RS benefits the Department of Transportation (DOT) as a customer, facilitates data access for academics, and enables idea exchange across four universities. The research delves into needs analysis, sensor technology, education and outreach, image processing, and data management, emphasizing partnerships and user consultation. The study highlights RS applications in asset management, location referencing, Intelligent Transportation Systems (ITS), security, and infrastructure mapping. Lessons learned underscore the diverse approaches in RS centerline solutions and the importance of validating RS with GPS for manual or automated processes. Engaging with various standards and partnerships, this research emphasizes the promising role of RS in transportation systems. Stay updated at ncgia.org for more insights.

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Integrating RS into Transportation Information Systems

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  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

  8. 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

  9. 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

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

  11. 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

  12. The GPS Challenge

  13. GPS Results — lane resolution

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

  15. 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

  16. 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

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

  18. UNETRANS

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

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

  21. 3-D Airport Approach Planning

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

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

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

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

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

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

  28. Boston — Big Dig impacts

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

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