Data-Driven Improvement of an Urban–Rural Integration Development Level from the Perspective of Economy, Society, and Ecology

Abstract Urban–rural integration (URI) is a critical pathway to achieving the United Nations’ Sustainable Development Goals (SDGs), as it enhances quality of life, promotes social equity, and fosters ecological resource sharing. This study advances the understanding of URI by proposing a data-driven framework for measuring, evaluating, and optimizing urban–rural integrated development (URID). Drawing on a comprehensive evaluation index system that integrates economic, social, and ecological dimensions, this research employs three methodological approaches: the entropy-weight technique for order preference by similarity to an ideal solution (TOPSIS) method to quantify URID levels, kernel density estimation to analyze spatiotemporal evolution trends, and an obstacle degree model to diagnose critical barriers impeding URID progress. Using data from China spanning from 2013 to 2022 as a case study, the findings reveal a steady improvement in URID levels nationwide, although pronounced regional disparities persist, underscoring the need for context-specific policy interventions. This work contributes to the global discourse on sustainable development by offering novel analytical frameworks and methodological insights for advancing the integration of rural and urban economies, communities, and natural systems. By highlighting both progress and challenges in URID, this study directly supports SDG 11. The findings provide actionable evidence for policymakers and researchers focused on bridging urban–rural divides while advancing the SDGs.