• Home
  • Browse
    • Current Issue
    • By Issue
    • By Author
    • By Subject
    • Author Index
    • Keyword Index
  • Journal Info
    • About Journal
    • Aims and Scope
    • Editorial Board
    • Publication Ethics
    • Indexing and Abstracting
    • Peer Review Process
  • Guide for Authors
  • Submit Manuscript
  • Contact Us
 
  • Login
  • Register
Home Articles List Article Information
  • Save Records
  • |
  • Printable Version
  • |
  • Recommend
  • |
  • How to cite Export to
    RIS EndNote BibTeX APA MLA Harvard Vancouver
  • |
  • Share Share
    CiteULike Mendeley Facebook Google LinkedIn Twitter
Egyptian Journal of Aquatic Biology and Fisheries
arrow Articles in Press
arrow Current Issue
Journal Archive
Volume Volume 29 (2025)
Volume Volume 28 (2024)
Volume Volume 27 (2023)
Volume Volume 26 (2022)
Volume Volume 25 (2021)
Volume Volume 24 (2020)
Volume Volume 23 (2019)
Issue 5 (Special Issue)
Issue Issue 4
Issue Issue 3
Issue Issue 2
Issue Issue 1
Volume Volume 22 (2018)
Volume Volume 21 (2017)
Volume Volume 20 (2016)
Volume Volume 19 (2015)
Volume Volume 18 (2014)
Volume Volume 17 (2013)
Volume Volume 16 (2012)
Volume Volume 15 (2011)
Volume Volume 14 (2010)
Volume Volume 13 (2009)
Volume Volume 12 (2008)
Volume Volume 11 (2007)
Volume Volume 10 (2006)
Volume Volume 9 (2005)
Volume Volume 8 (2004)
Volume Volume 7 (2003)
Volume Volume 6 (2002)
Volume Volume 5 (2001)
Volume Volume 4 (2000)
Volume Volume 3 (1999)
Volume Volume 2 (1998)
Volume Volume 1 (1997)
A. Basheer, M., B. El Kafrawy, S., A. Mekawy, A. (2019). Identification of mangrove plant using hyperspectral remote sensing data along the Red Sea, Egypt. Egyptian Journal of Aquatic Biology and Fisheries, 23(1), 27-36. doi: 10.21608/ejabf.2019.25932
Manar A. Basheer; Sameh B. El Kafrawy; Amal A. Mekawy. "Identification of mangrove plant using hyperspectral remote sensing data along the Red Sea, Egypt". Egyptian Journal of Aquatic Biology and Fisheries, 23, 1, 2019, 27-36. doi: 10.21608/ejabf.2019.25932
A. Basheer, M., B. El Kafrawy, S., A. Mekawy, A. (2019). 'Identification of mangrove plant using hyperspectral remote sensing data along the Red Sea, Egypt', Egyptian Journal of Aquatic Biology and Fisheries, 23(1), pp. 27-36. doi: 10.21608/ejabf.2019.25932
A. Basheer, M., B. El Kafrawy, S., A. Mekawy, A. Identification of mangrove plant using hyperspectral remote sensing data along the Red Sea, Egypt. Egyptian Journal of Aquatic Biology and Fisheries, 2019; 23(1): 27-36. doi: 10.21608/ejabf.2019.25932

Identification of mangrove plant using hyperspectral remote sensing data along the Red Sea, Egypt

Article 3, Volume 23, Issue 1, January 2019, Page 27-36  XML PDF (583.34 K)
Document Type: Original Article
DOI: 10.21608/ejabf.2019.25932
View on SCiNiTO View on SCiNiTO
Authors
Manar A. Basheer; Sameh B. El Kafrawy; Amal A. Mekawy
Abstract
The mangrove ecosystem is one of the most productive habitats that support many marine species and its adaptation to adverse environmental conditions, increase the demand to map, manage and monitor this ecosystem. The presence of hyperspectral remote sensing techniques can potentially improve the ability to measure the spectral signature of mangrove to differentiate mangrove from the other vegetation and to get detailed information about this ecosystem. This study has been carried out for mapping, monitoring and managing the Red Sea mangrove ecosystems through measuring their spectral properties using advanced hyperspectral remote sensing techniques. The spectral signature data were measured using Analytical Spectral Devices (ASD) Fieldspec spectroradiometer on November 2016 then the data were tested using statistical measures namely One-way Analysis of Variance (ANOVA) along with Tukey’s HSD test. The hyperspectral signatures of A. marina mangrove at the different sites showed that mangroves recorded a high reflectance at the visible and NIR region of the spectrum than the other regions and there are similarities at certain wavelengths and some differences at other wavelengths used for differentiation between mangroves in various environments. ANOVA and Tukey’s HSD test results showed that NIR region is the best region for the differentiation of mangrove from the other vegetation.
Keywords
Mangrove; Avicennia marina; Hyper-spectral signature; Remote Sensing; Red Sea
Statistics
Article View: 948
PDF Download: 1,430
Home | Glossary | News | Aims and Scope | Sitemap
Top Top

Journal Management System. Designed by NotionWave.