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Title: Aerosol Plume Detection Algorithm Based on Image Segmentation of Scanning Atmospheric Lidar Data

Journal Article · · Journal of Atmospheric and Oceanic Technology
 [1];  [2];  [2]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  2. National Center for Atmospheric Research, Boulder, CO (United States)
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An image-processing algorithm has been developed to identify aerosol plumes in scanning lidar backscatter data. The images in this case consist of lidar data in a polar coordinate system. Each full lidar scan is taken as a fixed image in time, and sequences of such scans are considered functions of time. The data are analyzed in both the original backscatter polar coordinate system and a lagged coordinate system. The lagged coordinate system is a scatterplot of two datasets, such as subregions taken from the same lidar scan (spatial delay), or two sequential scans in time (time delay). The lagged coordinate system processing allows for finding and classifying clusters of data. The classification step is important in determining which clusters are valid aerosol plumes and which are from artifacts such as noise, hard targets, or background fields. These cluster classification techniques have skill since both local and global properties are used. Furthermore, more information is available since both the original data and the lag data are used. Performance statistics are presented for a limited set of data processed by the algorithm, where results from the algorithm were compared to subjective truth data identified by a human.

Research Organization:
National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Sponsoring Organization:
National Center for Atmospheric Research (NCAR), Boulder, CO (United States)
Grant/Contract Number:
AC36-08GO28308
OSTI ID:
1247117
Report Number(s):
NREL/JA-6A20-64224
Journal Information:
Journal of Atmospheric and Oceanic Technology, Vol. 33, Issue 4; ISSN 0739-0572
Publisher:
American Meteorological SocietyCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 4 works
Citation information provided by
Web of Science

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Cited By (1)

Preliminary Studies on Atmospheric Monitoring by Employing a Portable Unmanned Mie-Scattering Scheimpflug Lidar System journal April 2019

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Related Subjects

97 MATHEMATICS AND COMPUTING
observational techniques and algorithms
algorithms
data processing
lidars/lidar observations
mathematical and statistical techniques
classification