Comparison of three hybrid models to simulate land use changes: a case study in Qeshm Island, Iran Ali Kourosh Niya & Jinliang Huang & Ali Kazemzadeh-Zow & Hazhir Karimi & Hamidreza Keshtkar & Babak Naimi Received: 29 December 2019 /Accepted: 2 April 2020 # Springer Nature Switzerland AG 2020 Abstract Land use change simulation is an important issue for its role in predicting future trends and provid- ing implications for sustainable land management. Hybrid models have become a recognized strategy to inform decision-makers, but further attempts are needed to warrant the reliability of their projected results. In view of this, three hybrid models, including the cellular automata-Markov chain-artificial neural network, cellu- lar automata-Markov chain-logistic regression, and Markov chain-artificial neural network, were applied to simulate land use change on the largest island in Iran, Qeshm Island. The Figure of Merit (FOM) was used to measure the modeling accuracy of the simula- tions, with the FOMs for the three models 6.7, 5.1, and 4.5, respectively. Consequently, the cellular automata- Markov chain-artificial neural network most precisely simulates land use change on Qeshm Island and is, thus, used to simulate land use change until 2026. The simu- lation shows that the incremental trend of the built-up class will continue in the coming years. Meanwhile, the areas of valuable ecosystems, such as mangroves, tend to decrease. Despite the protection plans for mangroves, these areas require more attention and conservation planning. This study demonstrates a referential example to select the proper land use models for informing planning and management in similar coastal zones. Keywords Land use/cover change . Hybrid models . Qeshm Island . Persian Gulf Introduction Land use/cover change (LUCC) simulation can help obtain a better understanding and more realistic predic- tion of future developments (Olmedo et al. 2015; Newman et al. 2016) and create better plans for solving environmental problems. Models used to predict LUCC are considered useful tools for environmental and geo- science research (Varga et al. 2019; Mustafa 2020). LUCC maps are applicable to environmental decisions and support planning for sustainable development Environ Monit Assess (2020) 192:302 https://doi.org/10.1007/s10661-020-08274-6 A. Kourosh Niya : J. Huang (*) Coastal & Ocean Management Institute, Xiamen University, Xiamen 361102 Fujian, China e-mail: jlhuang@xmu.edu.cn A. Kazemzadeh-Zow Department of RS and GIS, Faculty of Geography, University of Tehran, Tehran, Iran H. Karimi Department of Environmental Science, University of Zakho, Zakho, Kurdistan Region, Iraq H. Keshtkar Department of Arid and Mountainous Regions Reclamation, Faculty of Natural Resources, University of Tehran, Karaj, Iran B. Naimi Department of Geosciences and Geography, University of Helsinki, Helsinki 00014, Finland