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Land use change assessment in coastal mangrove forests of Iran utilizing satellite imagery and CA–Markov algorithms to monitor and predict future change

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Abstract

Mangrove forest stores large organic carbon stocks in a setting that is highly vulnerable to climate change and direct anthropogenic influences. As such there is a need to elucidate the causes and consequences of land use change on these ecosystems that have high value in terms of ecosystem services. We examine the areal pattern of land types in a coastal region located in southern Iran over a period of 14 years to predict future loss and gain in land types to the year 2025. We applied a CA–Markov model to simulate and predict mangrove forest change. Landsat satellite images from 2000 to 2014 were used to analyze the land cover changes between soil, open water and mangroves. Major changes during this period were observed in soil and water which could be attributed to rising sea level. Furthermore, the mangrove area in the more seaward position was converted to open water due to sea-level rise. A cellular automata model was then used to predict the land cover changes that would occur by the year 2025. Results demonstrated that approximately 21 ha of mangrove area will be converted to open water, while mangroves are projected to expand by approximately 28 ha in landward direction. These changes need to be delineated to better inform precise mitigation and adaptation measures.

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Acknowledgements

This research was sponsored by Persian Gulf University (PGU) Department of Environment at Persian Gulf research Institute. The authors appreciate the University of South Florida and Tarbiat Modares University for accessing research data and field study also helping in evaluating this paper.

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Authors and Affiliations

  1. Environmental Science, Persian Gulf Research Institute, Persian Gulf University, P.O. Box 7516913817, Bushehr, Iran

    Hana Etemadi

  2. Environmental Science, University of South Florida, Tampa, FL, 33701, USA

    Joseph M. Smoak

  3. Remote Sensing and GIS Department, Tarbiat Modares University, Tehran, Iran

    Jalal Karami

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  1. Hana Etemadi
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Correspondence to Hana Etemadi.

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Etemadi, H., Smoak, J.M. & Karami, J. Land use change assessment in coastal mangrove forests of Iran utilizing satellite imagery and CA–Markov algorithms to monitor and predict future change. Environ Earth Sci 77, 208 (2018). https://doi.org/10.1007/s12665-018-7392-8

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