Diagnosing street-level mismatch in historic district regeneration: a case study of Shuanglong Alley, Kaifeng, China

Historic districts often experience uneven spatial outcomes under market-oriented regeneration, particularly when visible commercial improvement advances faster than everyday street-level support in inner areas. To diagnose this problem, this paper develops a data-driven framework for identifying street-level mismatch in historic district regeneration. Using the Shuanglong Alley Historic District in Kaifeng, China, as a case study, the research proposes the Street Comprehensive Performance Index (SCPI), a street-level assessment indicator that integrates spatial structure derived from Space Syntax analysis, an observed daytime activity proxy derived from the Baidu Huiyan platform, and facility distribution derived from Points of Interest data. The results reveal a contrast between the better-supported outer streets and the less-supported inner residential areas. In particular, some inner streets combine weaker accessibility with lower facility concentration under the observed daytime activity proxy, indicating uneven street support under the current regeneration pattern. By translating these conditions into a measurable street-level framework, the study provides an operational tool for identifying under-supported streets and setting regeneration priorities. The findings suggest that more balanced historic district regeneration requires closer alignment between spatial accessibility, the observed daytime activity proxy, and facility distribution, and that the proposed framework can support evidence-based planning in historic urban areas.