Abstract
Coasts worldwide are facing enormous challenges relating to extreme water levels, inundation and coastal erosion. These challenges need to be addressed with consideration given to the need for infrastructure such as for ports and other socio-economic developments, especially for coastal tourism. Choosing the optimal decision support tools (DSTs) for coastal vulnerability and resilience assessment is a major challenge for decision-makers and coastal planners. The robustness and flexibility of coastal decision-making can be improved by using effective DSTs, particularly for the management of coastal hazards. This study provides an overview of the construction and use of decision support systems (DSSs) as combinations of DSTs, such as the commonly used multi-criteria decision analysis (MCDA) methods and an artificial neural network (ANN), integrated with a geographical information system (GIS). The experience of many researchers is that the combination of MCDA techniques based on fuzzy logic, analytical hierarchy process (AHP) and weighted linear combination (WLC), with GIS, and possibly also incorporating ANN, provides decision-makers with a comprehensive tool for efficiently calculating decision support indices (DSIs). Hybrid tools are becoming more popular and relevant among experts due to their multiple functionalities that facilitate decision-making. An integration of DSTs in a DSS and further development of DSIs provides a path for the integration of quantitative and qualitative parameters into the decision-making process, and providing materials to be used in consultation processes. An integrated DSS is more likely to produce high-quality results for decision-makers, handle the uncertainty of analysis, and extend the long-term applicability of tools employed by coastal managers.
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