Integrating fuzzy logic, optimization, and GIS for ecological impact assessments.
Appraisal of ecological impacts has been problematic because of the behavior of ecological system and the responses of these systems to human intervention are far from fully understood. While it has been relatively easy to itemize the potential ecological impacts, it has been difficult to arrive at accurate predictions of how these impacts affect populations, communities, or ecosystems. Furthermore, the spatial heterogeneity of ecological systems has been overlooked because its examination is practically impossible through matrix techniques, the most commonly used impact assessment approach. Besides, the public has become increasingly aware of the importance of the EIA in decision-making and thus the interpretation of impact significance is complicated further by the different value judgments of stakeholders. Moreover, impact assessments are carried out with a minimum of data, high uncertainty, and poor conceptual understanding. Hence, the evaluation of ecological impacts entails the integration of subjective and often conflicting judgments from a variety of experts and stakeholders. The purpose of this paper is to present an environmental impact assessment approach based on the integration fuzzy logic, geographical information systems and optimization techniques. This approach enables environmental analysts to deal with the intrinsic imprecision and ambiguity associated with the judgments of experts and stakeholders, the description of ecological systems, and the prediction of ecological impacts. The application of this approach is illustrated through an example, which shows how consensus about impact mitigation can be attained within a conflict resolution framework.
Bojórquez-Tapia
Luis A
LA
School of Renewable Natural Resources, Biological Science East, Room 207, University of Arizona, Tucson, AZ 85721 USA.
Juárez
Lourdes
L
Cruz-Bello
Gustavo
G
D003657:Decision Making; D004463:Ecology; D017753:Ecosystem; D004777:Environment; D004784:Environmental Monitoring / Q000379:methods*; D005544:Forecasting; D017143:Fuzzy Logic; D005843:Geography; D007256:Information Systems; D011050:Policy Making; D012680:Sensitivity and Specificity