Remote Sensing of Multimodal Transportation Systems

Hyperspectral remote sensing is an emerging field with many potential applications in the observation, management, and maintenance of the global transportation infrastructure. This report describes the development of an affordable framework to capture hyperspectral images and models to classify the images. The framework and models enable new approaches to plan, analyze, and assess the performance of multimodal transportation systems. Every hyperspectral image frame contains information in wavelengths that extend well beyond those that humans are capable of seeing or perceiving. The rapid size and cost reduction of both unmanned aircraft systems and hyperspectral image sensors enable easy scaling of the framework. Scaling is achieved simply by conducting multiple parallel missions to achieve broad area coverage at affordable prices. The authors showcase the general utility of the framework to enhance models used for roadway congestion forecasting, railway condition monitoring, and pipeline risk management. The authors offer additional insights by demonstrating a specific utility of the framework and models for the rapid detection of hazardous spills. Practitioners who utilize the framework and models to implement hyperspectral remote sensing platforms will benefit from greater situational awareness to make informed decisions in transportation systems development, operations, and maintenance.

• Record URL:
  https://www.ugpti.org/resources/reports/details.php?id=853
• 
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/31486
• Record URL:
  https://rosap.ntl.bts.gov/view/dot/31487
• Supplemental Notes:
  • This document was sponsored by the U.S. Department of Transportation, University Transportation Centers Program.
• Corporate Authors:

  Upper Great Plains Transportation Institute

  North Dakota State University
  1320 Albrecht Boulevard
  Fargo, ND  United States  581052

  Mountain-Plains Consortium

  North Dakota State University
  Fargo, ND  United States  58108

  Research and Innovative Technology Administration

  University Transportation Centers Program
  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Authors:
  • Bridgelall, Raj
  • Rafert, James B
  • Tolliver, Denver D
• Publication Date: 2016-9

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; References; Tables;
• Pagination: 51p

Subject/Index Terms

• TRT Terms: Condition surveys; Detection and identification systems; Drones; Multimodal transportation; Remote sensing; Risk management; Spills (Pollution)
• Subject Areas: Data and Information Technology; Transportation (General); Vehicles and Equipment;

Filing Info

• Accession Number: 01614940
• Record Type: Publication
• Report/Paper Numbers: MPC 16-313
• Contract Numbers: Project 460
• Files: UTC, NTL, TRIS, RITA, ATRI, USDOT
• Created Date: Oct 25 2016 2:05PM