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Coupling Agent-Based Modelling with Geographic Information Systems for Environmental Studies—A Review

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Abstract

With the increase of worldwide population, the environment has suffered intensely, where climate change issues are some of the top priorities for decision-makers worldwide. The extreme events recently witnessed have affected a countless number of people, with the loss of lives, properties and livelihood. Resourcing to technologies that facilitate decision-making is one of the viable options to correct our current path into the future. By using agent-based modelling coupled with geographical information systems, an effective platform can be created to design a bottom-up approach in policy creation and planning. This review paper analyses studies that have applied this methodology, yielding a vast range of results that were divided into nine different sustainable development categories: natural resources, social participation and trust, material welfare and economy, climate and energy, technology, biodiversity and landscape, mobility, safety and land development. The number of results shows that these studies are extremely relevant to the sustainable development topic. Although having manifested some limitations related to the transparency of the model design or validation issues, the application of agent-based modelling coupled with geographical information systems proved a competent tool for implementation in environmental and sustainability subjects.

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Acknowledgements

The first author has been supported by the Portuguese Foundation for Science and Technology (Fundação Portuguesa para a Ciência e Tecnologia—FCT), co-funded by FSE and national funds by MCTES, under the contract SFRH/BD/105590/2014. Thanks are also due for the financial support to CESAM (UID/AMB/50017/2019), to FCT/MCTES through national funds.

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Correspondence to Tanya Cristina Esteves .

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Esteves, T.C., Alves, F.L., Vaz, E. (2020). Coupling Agent-Based Modelling with Geographic Information Systems for Environmental Studies—A Review. In: Vaz, E. (eds) Regional Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-36479-3_12

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