Coupling fuzzy multiple attribute decision-making with analytic hierarchy process to evaluate urban ecological security: A case study of Guangzhou, China

Abstract

Urban ecosystem is plagued with complexities and uncertainties due to the interconnections among multiple subsystems, as well as human and environment interventions. In this study, a hybrid AHP-FMADM method through coupling fuzzy multiple attribute decision-making (FMADM) with analytic hierarchy process (AHP) is developed to evaluate urban ecological security (UES). AHP-FMADM has advantages in (i) reflecting interactive relationships among multiple attributes in UES, (ii) dealing with uncertainties expressed as imprecise linguistic terms and judgments, and (iii) achieving the ranking of alternatives based on pairwise comparison. Then, AHP-FMADM is applied to assessing the ecological security of Guangzhou from 2005 to 2015, where an urban ecological security evaluation indicator system is constructed based on the pressure–state–response conceptual model. A number of scenarios with different weight assignment modes are examined. Results indicate that the overall ecological security of the study city is gradually improved. Urban environment indicators contributes more to the ecological security level than social and economic indicators. However, although ecological security state and response level increase significantly, the ecological pressure has increased since 2012, which may result in a decline of ecological security. Compared to the traditional fuzzy synthetic analysis (FSA) approach with weighted sum operator, AHP-FMADM cannot only reduce the effect of the attributes with low importance and increase that with high importance, but also help decision makers determine alternative adaptation options and management schemes based on their preferences. These findings reveal that indicators with high importance degree need to be efficiently adjusted for decision makers to maintain ecological security, such as increase water reuse ratio and control the rapid growth of the population.