A new approach of deriving indicators and comprehensive measure for ecological environmental quality assessment

The key indicators' identifications and assessments of ecological environmental quality (EEQ) are very important for management policies and strategy. In this paper, founding upon the facts that the key indicators of EEQ from the experts' selections are hidden in and improved by the constantly additions of new publications, a new approach of deriving indicators and comprehensive measure for ecological environmental quality assessment (EEQA) is developed from dynamic co-word network. We elaborate the new approach and the modeling construction roadmap: the key indicators of EEQ emerge from the dynamic co-word network; basing on clustering and K-core analysis of the co-word network domains, four levels of indicators for EEQA are deduced; based on the similarity or relatedness between the indicators in the co-word network, nodal degrees are introduced to calculate indicators' weights and derive a comprehensive measure for EEQ, finally forming a rigorous co-word network model of EEQA. This model is applied to some typical cases of EEQA (a town, a city and two specific cases from Chongqing and Beijing) and the reasonable assessment results are obtained. The results are compared with other models to show the features of the model. The co-word network model for EEQA is a potential and universal function derived from traditional co-word methods of bibliometrics. Beyond the EEQA, the assessment of many other complex phenomena can be similarly conducted in terms of the given technical roadmap.