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Scenario modeling to predict changes in land use/cover using Land Change Modeler and InVEST model: a case study of Karaj Metropolis, Iran

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Abstract

Models for land cover/land use simulation are appropriate and important tools for decision-makers, helping them build future plausible landscape scenarios. Due to the fact that the simulation results of different models may be different, it is sometimes difficult for users to choose a suitable model. Therefore, in this study, an integrated approach is used, combining the data obtained from remote sensing and GIS with Land Change Modeler (LCM) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models to simulate and predict land cover/land use changes for 2028 in Karaj metropolis (Northern Iran as a poor region—in terms of data—which is under intense and rapid urbanization. In this sense, three land cover/land use maps related to the study area were primarily generated using satellite image data for the period 2006, 2011, and 2017. They were used as a basis to define two scenarios: business-as-usual (BAU) scenario and participatory plausible scenario (PPS) for 2028. Afterwards, the necessary input data used in running of both models were prepared and, then, the outputs of the models were interpreted and compared. According to the results, while human-made coverage and low-density grasslands increased by about 74% and 12%, respectively, it was from 2006 to 2017 that agricultural lands, gardens, and high-density grasslands decreased by 42%, 34%, and 7%, respectively. According to the business-as-usual scenario, which was projected using the LCM model, the increase in human-made cover will continue by about 29% by 2028, and the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will experience decrease by about 20%, 3%, 11%, and 9%, respectively. The participatory plausible scenario for 2028, which was defined using the InVEST model, confirmed the same results, but having different quantities. Accordingly, while human-made cover will increase by about 73%, the reduction rate of agricultural lands, gardens, and low-dense and dense grasslands will decrease by about 41%, 10%, 16%, and 1%, respectively. The output quantities of InVEST scenario model seem to be closer to reality with less uncertainty, because this model estimates the quantity of demand for land and its suitability for different uses, based on the views of different stakeholders, and considers landscape development future policies and plans. In contrast, the LCM model is based solely on trend extrapolation from the past to current time and changes in the landscape structure.

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Availability of data and materials

The datasets used or analyzed during the current study are available from the corresponding author on reasonable request.

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Acknowledgements

The authors of this article would like to thank the Research Center for Environment and Sustainable Development (RCESD), Department of Environmental Sciences, Malayer University, and the Department of Geodesy and Cadaster, Vilnius Gediminas Technical University, for their supports.

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Authors and Affiliations

  1. Research Center for Environment and Sustainable Development (RCESD), Department of Environment, Tehran, Islamic Republic of Iran

    Ardavan Zarandian

  2. Evaluation and Land Use Planning, Faculty of Natural Resources, Malayer University, Malayer, Iran

    Fatemeh Mohammadyari

  3. Department of Environmental Sciences, Malayer University, Malayer, Iran

    Mir Mehrdad Mirsanjari

  4. Department of Geodesy and Cadaster, Vilnius Gediminas Technical University, Sauletekio Av. 11, 10223, Vilnius, Lithuania

    Jurate Suziedelyte Visockiene

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A.Z. and F.M.: conception and design, data collection, methodology, modeling and mapping, validation, and writing and preparation of original draft; A.Z.: formal analysis and resources; M.M.M. and J.S.V.: methodology, validation, and writing and preparation of original draft. All authors read and approved the final manuscript.

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Zarandian, A., Mohammadyari, F., Mirsanjari, M.M. et al. Scenario modeling to predict changes in land use/cover using Land Change Modeler and InVEST model: a case study of Karaj Metropolis, Iran. Environ Monit Assess 195, 273 (2023). https://doi.org/10.1007/s10661-022-10740-2

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