Improving the detection of wind fields from LIDAR aerosol backscatter using feature extraction

Brady R. Bickel, Eric R. Rotthoff, Gage S. Walters, Timothy Joseph Kane, Shane D. Mayor

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The tracking of winds and atmospheric features has many applications, from predicting and analyzing weather patterns in the upper and lower atmosphere to monitoring air movement from pig and chicken farms. Doppler LIDAR systems exist to quantify the underlying wind speeds, but cost of these systems can sometimes be relatively high, and processing limitations exist. The alternative is using an incoherent LIDAR system to analyze aerosol backscatter. Improving the detection and analysis of wind information from aerosol backscatter LIDAR systems will allow for the adoption of these relatively low cost instruments in environments where the size, complexity, and cost of other options are prohibitive. Using data from a simple aerosol backscatter LIDAR system, we attempt to extend the processing capabilities by calculating wind vectors through image correlation techniques to improve the detection of wind features.

Original languageEnglish (US)
Title of host publicationOptical Pattern Recognition XXVII
EditorsDavid Casasent, Mohammad S. Alam
ISBN (Electronic)9781510600867
StatePublished - 2016
EventOptical Pattern Recognition XXVII - Baltimore, United States
Duration: Apr 20 2016Apr 21 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X


OtherOptical Pattern Recognition XXVII
Country/TerritoryUnited States

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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