Comparison of Fuzzy AHP and AHP in Multicriteria Inventory Classification While Planning Green Infrastructure for Resilient Stream Ecosystems
As climate change-induced weather variability increases, various green infrastructure plans, such as stream ecosystems, have been studied to overcome ecological and environmental problems arising from extreme weather events; however, our understanding of them and their resilience to extreme weather...
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Veröffentlicht in: | Sustainability 2020-11, Vol.12 (21), p.9035 |
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Sprache: | eng |
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Zusammenfassung: | As climate change-induced weather variability increases, various green infrastructure plans, such as stream ecosystems, have been studied to overcome ecological and environmental problems arising from extreme weather events; however, our understanding of them and their resilience to extreme weather events is considerably limited. This study proposes a multicriteria inventory classification while planning green infrastructure for resilient stream ecosystems under extreme weather events. Literature reviews, expert surveys, and reliability/validity analyses were used to enlist indicators for this classification. The analytic hierarchy process (AHP) and fuzzy analytic hierarchy process (fuzzy AHP) were used to compute the weights and ranks of indicators for identifying critical indices while planning green infrastructure. The AHP and fuzzy AHP analysis suggested that meteorological phenomena and disasters, hydraulic characteristic of streams, land use/geographic characteristics, and experience/damage restoration were important factors. High weights were attributed to aquatic ecology, potentially vulnerable areas, population, topography, and heat waves. The weights and ranks attributed by AHP and fuzzy AHP varied slightly, but the indicator groups with high and low weights were the same; hence, primary indicators to be considered while planning green infrastructure for resilient stream ecosystems could be suggested. These results could be used as a preliminary analysis in establishing countermeasures against climate change or in distributing budgets for green infrastructure plans. |
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ISSN: | 2071-1050 2071-1050 |
DOI: | 10.3390/su12219035 |