A heterogeneous approach for environmental impact significance assessment based on fuzzy linguistic models

Classical methods for Environmental Impact Significance Assessment are not efficient on handle heterogeneous information and they obtain numerical outputs of low interpretability. In this contribution we propose a novel heterogeneous approach for EISA based on fuzzy linguistic models. It provides a flexible evaluation framework in which experts can supply their preferences using different domains and applies an aggregation process based on 2-tuples linguistic computational model to obtain interpretable significance values.