A cognitive map framework to support integrated environmental assessment

In this work we present the rational and design of a methodology to support Integrated Environmental Assessment using the DPSIR (Driving Forces–Pressures–State–Impact–Response) causal-effect framework and non-monotonic Fuzzy Cognitive Maps. The methodology is based on key pillars in environmental ma...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2016-03, Vol.77, p.81-94
Hauptverfasser: Mourhir, Asmaa, Rachidi, Tajjeeddine, Papageorgiou, Elpiniki I., Karim, Mohammed, Alaoui, Faycal Sossi
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Sprache:eng
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Zusammenfassung:In this work we present the rational and design of a methodology to support Integrated Environmental Assessment using the DPSIR (Driving Forces–Pressures–State–Impact–Response) causal-effect framework and non-monotonic Fuzzy Cognitive Maps. The methodology is based on key pillars in environmental management, namely connecting the socioeconomic and the natural environment dimensions into a policy oriented context; integration of stakeholders with inter-sectorial synergies and tradeoffs; handling of ambiguities and uncertainties intrinsic to environmental modeling and representation of complex non-linear cause-effect relationships in the form of Fuzzy Inference Systems, capable of adapting dynamically the influence between indicators. The methodology has the potential to support the development of informed policies and improves reliability through transparent, traceable and reproducible results. The illustrative example assesses the impact of air pollution abatement policies according to expert perceptions using proactive scenarios; the results revealed that, despite some positive changes, air protection activities are missing an overall strategic vision. •We developed an integrated environmental assessment model using non-monotonic FCMs.•DPSIR is used as a conceptual instrument to frame the selection of FCM concepts.•The model supports multi-disciplinary stakeholder participation.•The model is capable of handling uncertainties using Fuzzy Logic.•The model is used to perform simulations of air pollution control scenarios.
ISSN:1364-8152
DOI:10.1016/j.envsoft.2015.11.018