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Proceedings Paper

Improving the detection of wind fields from LIDAR aerosol backscatter using feature extraction
Author(s): Brady R. Bickel; Eric R. Rotthoff; Gage S. Walters; Timothy J. Kane; Shane D. Mayor
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Paper Abstract

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.

Paper Details

Date Published: 20 April 2016
PDF: 6 pages
Proc. SPIE 9845, Optical Pattern Recognition XXVII, 98450A (20 April 2016); doi: 10.1117/12.2223932
Show Author Affiliations
Brady R. Bickel, The Pennsylvania State Univ. (United States)
Eric R. Rotthoff, The Pennsylvania State Univ. (United States)
Gage S. Walters, The Pennsylvania State Univ. (United States)
Timothy J. Kane, The Pennsylvania State Univ. (United States)
Shane D. Mayor, California State Univ., Chico (United States)

Published in SPIE Proceedings Vol. 9845:
Optical Pattern Recognition XXVII
David Casasent; Mohammad S. Alam, Editor(s)

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