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Wavelet Analysis for Wind Fields Estimation

Teleinformatics Engineering Department, Federal University of Ceará, Fortaleza, CE 60455-970, Brazil
Math and Visualization Groups, Lawrence Berkeley National Laboratory–LNBL, Berkeley, CA 94117, USA
Division of Engineering, Brown University, Providence, RI 02912, USA
Author to whom correspondence should be addressed.
Sensors 2010, 10(6), 5994-6016;
Received: 11 May 2010 / Revised: 30 May 2010 / Accepted: 5 June 2010 / Published: 14 June 2010
(This article belongs to the Special Issue Sensor Algorithms)
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 B3 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. View Full-Text
Keywords: SAR; wind direction; FFT; CMOD4; wind speed SAR; wind direction; FFT; CMOD4; wind speed
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MDPI and ACS Style

Leite, G.C.; Ushizima, D.M.; Medeiros, F.N.S.; De Lima, G.G. Wavelet Analysis for Wind Fields Estimation. Sensors 2010, 10, 5994-6016.

AMA Style

Leite GC, Ushizima DM, Medeiros FNS, De Lima GG. Wavelet Analysis for Wind Fields Estimation. Sensors. 2010; 10(6):5994-6016.

Chicago/Turabian Style

Leite, Gladeston C., Daniela M. Ushizima, Fátima N. S. Medeiros, and Gilson G. De Lima. 2010. "Wavelet Analysis for Wind Fields Estimation" Sensors 10, no. 6: 5994-6016.

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