Globally, the challenges facing cities regarding urban decay, insufficient urban function, and fragmented urban development are enormous. Under this context, urban renewal provides opportunities to address these challenges and enhance urban sustainability. Thus, promoting urban renewal projects and improving their performance is a global topic. In many circumstances, urban renewal is planned and initiated on the project scale, but on the area scale, overall coordination of the projects can bring about comprehensive benefits to urban areas on a macro view. In practice, it still lacks a systematic evaluation approach to obtain a clear picture of such comprehensive benefits. In academia, the existing research studies are mainly focused on single-project evaluation. An integrated framework that provides a holistic assessment of area-scale project benefits is missing. Few fully consider the coupling coordination benefits between several urban renewal projects from an area-scale perspective. Thus, this paper aims to propose a framework for integrating an indicator evaluation system through a hybrid entropy weight method with Back Propagation (BP) neural network methods to evaluate the comprehensive benefit of urban renewal projects on the area scale, which is the level at which most development area-scale renewal projects take place in a city. The feasibility and effectiveness of this proposed framework are then verified in a case study of Chongqing, China. The results indicate that the proposed method that integrated multi-project characteristics can contribute to a bigger picture of benefit evaluation of urban renewal based on an area scale perspective. This therefore provides not only guidance for urban planners and policymakers to make better decisions, but also new insight for benefit evaluation in the field of urban development.
Keywords: area scale; back propagation neural network; comprehensive benefit evaluation; entropy weight method; urban renewal.