A methodology for cloud masking uncalibrated lidar signals
Most lidar processing algorithms, such as those included in EARLINET’s Single Calculus Chain, can be applied only to cloud-free atmospheric scenes. In this paper, we present a methodology for masking clouds in uncalibrated lidar signals. First, we construct a reference dataset based on manual inspec...
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Published in | EPJ Web of Conferences Vol. 176; p. 5048 |
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Main Authors | , , , , |
Format | Journal Article Conference Proceeding |
Language | English |
Published |
Les Ulis
EDP Sciences
01.01.2018
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Subjects | |
Online Access | Get full text |
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Summary: | Most lidar processing algorithms, such as those included in EARLINET’s Single Calculus Chain, can be applied only to cloud-free atmospheric scenes. In this paper, we present a methodology for masking clouds in uncalibrated lidar signals. First, we construct a reference dataset based on manual inspection and then train a classifier to separate clouds and cloud-free regions. Here we present details of this approach together with an example cloud masks from an EARLINET station. |
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ISSN: | 2100-014X 2101-6275 2100-014X |
DOI: | 10.1051/epjconf/201817605048 |