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Monitor Mangrove Forest Dynamics from Multi-temporal Landsat 8-OLI Images in the Southern Coast of Sancti Spíritus Province (Cuba)

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12955))

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Abstract

In the coastal tropics and subtropical regions, fragile ecosystems such as deltas, mangrove forests, and swamps are common, whose ecological stability strictly depends on the quality management of hydrological resources at the basin level. The National Hydrographic Basin Council in Cuba, protect the hydrographic basins, considered as the reference unit for the integrated management of water resources. Moreover, the council aims at preventing negative impacts on of these vital ecosystems for their key services to the overall social and economic wellbeing. As an example, the Zaza River basin in the of Province of Sancti Spiritus, the mangrove forest is suffering from significant decay, in particular on the southern coasts. A significant improvement of the water resources sustainable management in Cuba, is a more reliable and timely monitoring. Considering the extreme conditions and the limited accessibility of mangroves, remote sensing and others earth observations techniques represents a suitable tool for monitoring the mangrove forest in coastal areas. In our study, we used a set of 10 multispectral Landsat – 8 OLI images from November 2014 to December 2015.

By collecting campaigns on mangroves’ phenology, we have: 1) studied the relationships between phenology and spectral behavior of species; and, 2) set up a classification framework to assess the forests composition remotely, with special attention to mangroves. The methodology here implemented could be effectively applied in all coastal natural ecosystems of this island to improve the knowledge about the critical issues of these very fragile ecosystems.

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Author information

Authors and Affiliations

  1. Department of Agricultural, Food, and Environmental Sciences, Marche Polytechnic University, Ancona, Italy

    Ernesto Marcheggiani, Andrea Galli, Osmany Ceballo Melendres & MD Abdul Mueed Choudhury

  2. Division of Forest, Nature, and Landscape, Department of Earth and Environmental Sciences, KU Leuven, 3001, Leuven, Belgium

    Ernesto Marcheggiani, Ben Somers, Julio P. García-Lahera & Wanda De Keersmaecker

Authors
  1. Ernesto Marcheggiani
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  2. Andrea Galli
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  3. Osmany Ceballo Melendres
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  4. Ben Somers
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  5. Julio P. García-Lahera
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  6. Wanda De Keersmaecker
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  7. MD Abdul Mueed Choudhury
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Corresponding authors

Correspondence to Ernesto Marcheggiani or MD Abdul Mueed Choudhury .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A. C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Marcheggiani, E. et al. (2021). Monitor Mangrove Forest Dynamics from Multi-temporal Landsat 8-OLI Images in the Southern Coast of Sancti Spíritus Province (Cuba). In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12955. Springer, Cham. https://doi.org/10.1007/978-3-030-87007-2_13

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  • DOI: https://doi.org/10.1007/978-3-030-87007-2_13

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