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Wavelet Analysis for Wind Fields Estimation

Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing und...

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Detalles Bibliográficos
Autores principales: Leite, Gladeston C., Ushizima, Daniela M., Medeiros, Fátima N. S., de Lima, Gilson G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3247744/
https://www.ncbi.nlm.nih.gov/pubmed/22219699
http://dx.doi.org/10.3390/s100605994
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author Leite, Gladeston C.
Ushizima, Daniela M.
Medeiros, Fátima N. S.
de Lima, Gilson G.
author_facet Leite, Gladeston C.
Ushizima, Daniela M.
Medeiros, Fátima N. S.
de Lima, Gilson G.
author_sort Leite, Gladeston C.
collection PubMed
description Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(−1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms.
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spelling pubmed-32477442012-01-04 Wavelet Analysis for Wind Fields Estimation Leite, Gladeston C. Ushizima, Daniela M. Medeiros, Fátima N. S. de Lima, Gilson G. Sensors (Basel) Article Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(−1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms. Molecular Diversity Preservation International (MDPI) 2010-06-14 /pmc/articles/PMC3247744/ /pubmed/22219699 http://dx.doi.org/10.3390/s100605994 Text en © 2010 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Leite, Gladeston C.
Ushizima, Daniela M.
Medeiros, Fátima N. S.
de Lima, Gilson G.
Wavelet Analysis for Wind Fields Estimation
title Wavelet Analysis for Wind Fields Estimation
title_full Wavelet Analysis for Wind Fields Estimation
title_fullStr Wavelet Analysis for Wind Fields Estimation
title_full_unstemmed Wavelet Analysis for Wind Fields Estimation
title_short Wavelet Analysis for Wind Fields Estimation
title_sort wavelet analysis for wind fields estimation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3247744/
https://www.ncbi.nlm.nih.gov/pubmed/22219699
http://dx.doi.org/10.3390/s100605994
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