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Author: Maria Conceição da Proença

Affiliation: Department of Physics, Marine and Environmental Sciences Centre (MARE-ULisboa), Faculty of Sciences, University of Lisbon, Campo Grande, 1749-016 Lisboa, Portugal

Keyword(s): Wind Direction, Wind Shadows, Direction Ambiguity, SAR Images, Image Processing.

Abstract: The evaluation of the wind resource in large areas to study the viability of wind farms is ideally studied using synthetic aperture radar (SAR) images in which the direction of the wind can be mapped from its effects on the water surface. Methods in use usually assume a fixed direction from a measurement for the whole image or interpolate the direction of wind fields from numerical weather models, that can be non-coincident in time with the SAR snapshot and of much less spatial resolution. The problem remains in the directional ambiguity of 180 degrees. This work presents three indexes to identify and validate initial “anchor vectors” that could be used as an aid in the complex process of remove this ambiguity, using wind shadows in the water near the coastline. These indexes consider several hypotheses to provide for local variability such as physiographic accidents, the eccentricity of the shadows and the effect of bay-shaped areas, all quantified through image processing methods. Comparing the results with the reference wind field provided by ESA for the time of acquisition of the ENVISAT-ASAR image used we could conclude that this is a promising line of work. (More)

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Paper citation in several formats:
Proença, M. (2022). Removing Automatically the Ambiguity in Wind Direction Retrieved from SAR Images. In Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE; ISBN 978-989-758-563-0; ISSN 2795-4943, SciTePress, pages 93-100. DOI: 10.5220/0010934000003209

@conference{improve22,
author={Maria Concei\c{C}ão da Proen\c{C}a.},
title={Removing Automatically the Ambiguity in Wind Direction Retrieved from SAR Images},
booktitle={Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE},
year={2022},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010934000003209},
isbn={978-989-758-563-0},
issn={2795-4943},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - IMPROVE
TI - Removing Automatically the Ambiguity in Wind Direction Retrieved from SAR Images
SN - 978-989-758-563-0
IS - 2795-4943
AU - Proença, M.
PY - 2022
SP - 93
EP - 100
DO - 10.5220/0010934000003209
PB - SciTePress

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