How Aerial and Satellite Remote Sensing Assist Transportation Planning and Mitigate Risks Stan Morain Amelia Budge Earth Data Analysis Center University of New Mexico Applications of Remote Sensing Technologies for Transportation Data Collection Jacksonville, FL December 1-2, 2004 National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters

Discussion Topics Multispectral and Temporal Concepts Terrain –Corridor Planning –Failures –Deformations Roads –Updates & Maintenance –Safety & Incident Management –Hazardous Materials Transport Airports National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters

Increasing Complexity Local Inventory Single Source Data Simple Identification Manual Analysis Photographs Analog Recording Cameras Balloons Global Surveys Multiple Source Data Complex Problem Solving Machine Assisted Analysis Image & Non-image Data Digital Recording Electronic Sensor Systems Satellites National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Concepts

Wavelength, µm R Each pixel has an associated, continuous spectrum that can be used to identify the surface materials. Images taken simultaneously (e.g., in 200 or more spectral bands) inherently registered The Imaging Spectrometry Concept National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Concepts

Mapping Monitoring Modeling Other Image Data Legal Economic Social Public Health Topography Sediment Hydrology Utilities Natural Resources Measurement ProblemInformation Decision Action Database Manipulation & Analysis Decision Making Process National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Concepts

T+n T+1 T Measurement T N+1 TNTN T+1 T -M Modeling Information analysis for management decision making Measurement, Mapping, Modeling, and Management T+n T+1 T Mapping Management requires constant refreshment of information obtained from measurement, mapping, and modeling. Time provides the means for making static data and information more dynamic. Outputs are more easily visualized in time and space when temporal and spectral attributes are fused. Time Data analysis and processing National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Concepts

Gulf Coast Assessment The Gulf Coast includes dense urban areas intermixed with designated natural areas, which influence or constrain development within the area. National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Terrain: Corridor Planning Slide courtesy of NCRST-E

Preliminary Alternate Routes Alt A- 1 Alt B-1 Alt D-1 Alt D-2 Alt D-1 / D-2 Alt B-1 Alt A- 1 Alt C- 1 Alt C-1 D-1 Slide courtesy of NCRST-E National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Terrain: Corridor Planning

LIDAR and Hyperspectral Data Collection Slide courtesy of NCRST-E National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Terrain: Corridor Planning

What Worked Well?.....a Summary Coordinated Data Collection Key Data and Products: i.e., LiDAR, DEMs, Hydrological, Hyperspectral Data Fusion 3-D Landscape Views Identifying Wetlands Detailed Land Cover Analysis Partnering With Industry National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Data Fusion Wetlands Land Cover Analysis Terrain: Corridor Planning

Very near-term prime-time technology. Successfully demonstrated in multiple states. Promises to help bring meaningful streamlining to various NEPA processes. Helps preserve the intent of NEPA to consider all alternatives. Needs to be pilot deployed and applications taken to production mode to allow delivery of finished information products rather than raw data. Application Summary National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Slide courtesy of NCRST-E Terrain: Corridor Planning

Assessing Transportation Lifeline Hazards A variable shaped neighborhood (function of hazard type, surroundings and time) is passed along a lifeline to assign a hazard value to each point or segment. National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Terrain: Failures

General Strategy for Assessing Risk For Land Failures A B C D National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Terrain: Failures

Visualization of Results Terrain: Failures National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters

Las Vegas Interferogram ERS-2 data (the background image) are fused with ERS- 1 data taken three years earlier to create an interferogram. National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters From Professional Surveyor, Oct Terrain: Deformations

InSAR-derived displacement map of the Salt Lake Valley. The change in color scale indicates more subtle movements. The road network is shown in black with fault traces in white. Terrain: Deformations National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters

Ikonos 1m IRS-C 5m DOQQ.33m data Updating Roads Using Imagery National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Roads: Updates & Maintenance

Total image evaluation time to total road mileage updated (min/km) Percent of Total Road Mileage Updated Speed and Output National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Roads: Updates & Maintenance Ikonos IRS-C DOQQ

Some tools in the rural road toolkit help managers (1)pinpoint areas of highest risk for flooding and washouts (2)dispatch maintenance crews efficiently to the most critical spots Road Safety & Maintenance Tools National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Roads: Safety & Incident Management

White dots show crash locations, black line is the road centerline along Route 17. Highway Safety Using Multi-Criteria Evaluation National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Roads: Safety & Incident Management

Bridge Doctor / Bridge Hunter Bridge Hunter and Bridge Doctor algorithms locate bridges of interest and diagnose their structural integrity Damage detection algorithms using high- resolution satellite imagery, offers timely coverage These tools have been validated by the UDOT in Salt Lake City Courtesy ImageCat Inc. National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Roads: Safety & Incident Management

Route, Risk, & Vulnerability Assessment Reduce losses and disruptions arising from hazardous materials transport by improving route, risk, and vulnerability assessments. Deploy an operational, geospatial system that provides enhanced route assessment, risk evaluation, and emergency response capabilities for hazmat transport. National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Roads: Hazardous Materials Transport

Current Process and Proposed Deployment Solution National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Existing Approach TRAGIS & NHMRR Proposed Deployment Route Assessment & Monitoring Baseline Data Acquisition Hazmat Route Selection Windshield survey Emergency Response Integrate NCRST-H GIT & resources Spreadsheet format Online visualization & quantitative risk analysis DECISION SUPPORT SYSTEM High Moderate Low School 10 Extended Functionality Evacuation planning Re-routing N/A  Roads: Hazardous Materials Transport

Expected Outcomes Enhanced route assessment methods Migration from spreadsheet to map format in the cab Increased number of route assessment attributes Insertion of risk and vulnerability data in assessment database Migration from road alignment buffer to include sensitive features off-road Online deployment of tools and resources National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Roads: Hazardous Materials Transport

200ft 98 ° 200ft 98° Runway Primary Surface Primary Surface Centerline of Runway 1000ft ft (7nm) ft Specification of NIMA (NGA), 2001 Airport Obstruction Analysis Top View National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Airports

Airfield Facilities & Management SBMA Photo SBMA w/2.5m post-spacing DEM from aerial photos SBMA aerial photo w/1m LiDAR DEM post spacings Courtesy, I.K. Curtis; Airborne-1; and, BAE Systems National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Airports

Glide Path Visualization National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Airports

Obstruction Identification Yellow = Terrain obstructs Red = Point obstructs Orange = OIS Santa Barbara Municipal Airport National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters Airports

Contact Information National Consortium for Remote Sensing in Transportation Security, Safety, Hazards, and Disasters NCRST-H Stan Morain, PI Amelia Budge