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

• Published in: Environmental earth sciences Vol. 77; no. 5; pp. 1 - 13
• Main Authors: Etemadi, Hana, Smoak, Joseph M., Karami, Jalal
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2018; Springer Nature B.V
• Subjects: Adaptation; Algorithms; Anthropogenic factors; Biogeosciences; Cellular automata; Climate change; Coastal zone; Computer simulation; Earth and Environmental Science; Earth Sciences; Ecosystem services; Ecosystems; Environmental Science and Engineering; Geochemistry; Geology; Human influences; Hydrology/Water Resources; Imagery; Land cover; Land use; Landsat; Landsat satellites; Mangrove swamps; Mangroves; Markov chains; Mitigation; Organic carbon; Original Article; Remote sensing; Satellite imagery; Satellites; Sea level; Sea level rise; Soil; Soil water; Spaceborne remote sensing; Stocks; Terrestrial Pollution; Iran; Markov chain; Mangrove forest; Cellular automata; Land change analysis; Sea-level rise
• ISSN: 1866-6280; 1866-6299
• DOI: 10.1007/s12665-018-7392-8

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.