Airborne LiDAR reflective linear feature extraction for strip adjustment and horizontal accuracy determination.

Details

• Creators:
  Toth, Charles ; Grejner-Brzezinska, Dorota A.
• Corporate Creators:
  Ohio State University. Research Foundation
• Corporate Contributors:
  Ohio. Dept. of Transportation
• Subject/TRT Terms:
  • Laser radar
  • Traffic flow
  • Remote sensing
  • Traffic flow--Ohio--Remote sensing
  • Motor vehicles--Ohio--Remote sensing
  • Optical radar--Ohio
• Publication/ Report Number:
  FHWA/OH-2008/15
• Resource Type:
  Tech Report
• Geographical Coverage:
  Ohio
• Corporate Publisher:
  Ohio State University
• Abstract:
  ODOT's Office of Aerial Engineering (OAE) has been using an Opetch 30/70 ALTM airborne LiDAR system for about four years. The introduction of LiDAR technology was a major development towards improving the mapping operations. The overall experiences are excellent as evidenced by numerous projects where highly accurate surface data were produced in an unprecedentedly short time. As is typically with new technology, OAE has identified areas for improvements in terms of achieving better accuracy and increasing data processing efficiency. In particular, the horizontal accuracy of the LiDAR product required further attention. The objectives of this research were to (1) introduce ground control to LiDAR by using road pavement makings that can be precisely surveyed by ODOT's system; (2) preform a strip adjustment for seamless integration of strips into the final product; (3) improve the horizontal accuracy in order to better characterize the final product; and (4) improve accuracy (both horizontal and vertical) to use ground control that is less labor-intense, requires no or limited surveying and imposes less restrictions in normal field operations.
• Format:
  PDF
• Funding:
  134316
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/18475/dot_18475_DS1.pdf
• File Type:
  [PDF - 4.55 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha256:f251e28af277c22b4b721b1ff31bbce2e341f6315ce2c59b31083da5368c5729