Towards a Framework for Noctilucent Cloud Analysis
In this paper, we present a framework to study the spatial structure of noctilucent clouds formed by ice particles in the upper atmosphere at mid and high latitudes during summer. We studied noctilucent cloud activity in optical images taken from three different locations and under different atmosph...
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ftmdpi:oai:mdpi.com:/2072-4292/11/23/2743/ 2023-08-20T04:06:15+02:00 Towards a Framework for Noctilucent Cloud Analysis Puneet Sharma Peter Dalin Ingrid Mann 2019-11-22 application/pdf https://doi.org/10.3390/rs11232743 EN eng Multidisciplinary Digital Publishing Institute https://dx.doi.org/10.3390/rs11232743 https://creativecommons.org/licenses/by/4.0/ Remote Sensing; Volume 11; Issue 23; Pages: 2743 noctilucent clouds linear discriminant analysis convolutional neural networks Text 2019 ftmdpi https://doi.org/10.3390/rs11232743 2023-07-31T22:49:15Z In this paper, we present a framework to study the spatial structure of noctilucent clouds formed by ice particles in the upper atmosphere at mid and high latitudes during summer. We studied noctilucent cloud activity in optical images taken from three different locations and under different atmospheric conditions. In order to identify and distinguish noctilucent cloud activity from other objects in the scene, we employed linear discriminant analysis (LDA) with feature vectors ranging from simple metrics to higher-order local autocorrelation (HLAC), and histogram of oriented gradients (HOG). Finally, we propose a convolutional neural networks (CNN)-based method for the detection of noctilucent clouds. The results clearly indicate that the CNN-based approach outperforms the LDA-based methods used in this article. Furthermore, we outline suggestions for future research directions to establish a framework that can be used for synchronizing the optical observations from ground-based camera systems with echoes measured with radar systems like EISCAT in order to obtain independent additional information on the ice clouds. Text EISCAT MDPI Open Access Publishing Remote Sensing 11 23 2743 |
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Open Polar |
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MDPI Open Access Publishing |
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ftmdpi |
language |
English |
topic |
noctilucent clouds linear discriminant analysis convolutional neural networks |
spellingShingle |
noctilucent clouds linear discriminant analysis convolutional neural networks Puneet Sharma Peter Dalin Ingrid Mann Towards a Framework for Noctilucent Cloud Analysis |
topic_facet |
noctilucent clouds linear discriminant analysis convolutional neural networks |
description |
In this paper, we present a framework to study the spatial structure of noctilucent clouds formed by ice particles in the upper atmosphere at mid and high latitudes during summer. We studied noctilucent cloud activity in optical images taken from three different locations and under different atmospheric conditions. In order to identify and distinguish noctilucent cloud activity from other objects in the scene, we employed linear discriminant analysis (LDA) with feature vectors ranging from simple metrics to higher-order local autocorrelation (HLAC), and histogram of oriented gradients (HOG). Finally, we propose a convolutional neural networks (CNN)-based method for the detection of noctilucent clouds. The results clearly indicate that the CNN-based approach outperforms the LDA-based methods used in this article. Furthermore, we outline suggestions for future research directions to establish a framework that can be used for synchronizing the optical observations from ground-based camera systems with echoes measured with radar systems like EISCAT in order to obtain independent additional information on the ice clouds. |
format |
Text |
author |
Puneet Sharma Peter Dalin Ingrid Mann |
author_facet |
Puneet Sharma Peter Dalin Ingrid Mann |
author_sort |
Puneet Sharma |
title |
Towards a Framework for Noctilucent Cloud Analysis |
title_short |
Towards a Framework for Noctilucent Cloud Analysis |
title_full |
Towards a Framework for Noctilucent Cloud Analysis |
title_fullStr |
Towards a Framework for Noctilucent Cloud Analysis |
title_full_unstemmed |
Towards a Framework for Noctilucent Cloud Analysis |
title_sort |
towards a framework for noctilucent cloud analysis |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2019 |
url |
https://doi.org/10.3390/rs11232743 |
genre |
EISCAT |
genre_facet |
EISCAT |
op_source |
Remote Sensing; Volume 11; Issue 23; Pages: 2743 |
op_relation |
https://dx.doi.org/10.3390/rs11232743 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/rs11232743 |
container_title |
Remote Sensing |
container_volume |
11 |
container_issue |
23 |
container_start_page |
2743 |
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1774717224053899264 |