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DOI: 10.14569/IJACSA.2023.0140380
PDF

Polarimetric SAR Characterization of Mangrove Forest Environment in the United Arab Emirates (UAE)

Author 1: Soumaya Fatnassi
Author 2: Mohamed Yahia
Author 3: Tarig Ali
Author 4: Maruf Mortula

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 14 Issue 3, 2023.

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Abstract: This Mangrove forests in the United Arab Emirates (UAE) provide valuable ecosystem services such as coastal erosion protection, water purification and refuge for a wide variety of plants and animals. Therefore, the first step toward understanding the mangrove forests is the monitoring of this important ecological system. This paper proposes an original study to characterize the mangrove forest environment in the UAE by using polarimetric synthetic aperture radar (PolSAR) remote sensing. Free access C-band dual- PolSAR Sentinel 1 data have been exploited. The elements as of the covariance matrix as well as the entropy/alpha decomposition parameters have been studied. Results show that the VH intensity, the coherence between VV and VH polarimetric channels, the entropy and alpha angle provide the most pronounced signatures that discern mangrove forests. Thus, these parameters could be exploited to improve the accuracy of the remote sensing monitoring and mapping techniques of mangrove forests in the UAE.

Keywords: Mangrove forests; dual-PolSAR; sentinel 1; United Arab Emirates; entropy/alpha decomposition

Soumaya Fatnassi, Mohamed Yahia, Tarig Ali and Maruf Mortula, “Polarimetric SAR Characterization of Mangrove Forest Environment in the United Arab Emirates (UAE)” International Journal of Advanced Computer Science and Applications(IJACSA), 14(3), 2023. http://dx.doi.org/10.14569/IJACSA.2023.0140380

@article{Fatnassi2023,
title = {Polarimetric SAR Characterization of Mangrove Forest Environment in the United Arab Emirates (UAE)},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140380},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140380},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {3},
author = {Soumaya Fatnassi and Mohamed Yahia and Tarig Ali and Maruf Mortula}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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