文献类型：期刊文献

中文题名：城市既有社区更新的可持续性评估:研究进展与分析框架

英文题名：Sustainability assessment of urban community regeneration:Research progress and analytical framework

作者：李文竹[1];王润娴[2];王培晓[3];孙彤宇[2]

机构：[1]华东理工大学艺术设计与传媒学院;[2]同济大学建筑与城市规划学院;[3]中国科学院地理科学与资源研究所

年份：2025

卷号：40

期号：2

起止页码：88

中文期刊名：西部人居环境学刊

外文期刊名：Journal of Human Settlements in West China

收录：;北大核心:【北大核心2023】；

基金：国家重点研发计划(2023YFC3805400);国家自然科学基金(52378068,52408060);中央高校基本科研业务费专项资金(JKZ02252281);华东理工大学教师产学研践习计划(YZ0130518);上海市教育发展基金会和上海市教育委员会“晨光计划”项目;上海市设计学Ⅳ类高峰学科资助。

语种：中文

中文关键词：城市更新;既有社区;可持续性评估;评价指标;可持续发展

外文关键词：urban regeneration;existing communities;sustainability assessment;evaluation indicators;sustainable development

摘要：城市既有社区更新的可持续性评估是促进城市可持续发展的重要工具。尽管当前已存在一系列旨在全球范围内适用的可持续性评估国际标准,然而,社区层面的可持续更新研究尚显薄弱,各城市在经济、社会及环境特征上具有独特性,且既有的评估框架构建及其权重分配往往受限于主观判断与地域局限,难以全面而精准地反映特定城市的实际情况。因此,本研究旨在构建一个适合我国国情的城市既有社区更新的可持续性综合评估框架。该框架涵盖层次结构的构建、评价指标的选择、数据库的建立、要素权重的分配以及综合与单项评估结果的生成。通过整合地方专家的专业知识和居民的实际需求,本研究旨在为城市社区更新提供精确的指导,并选择适合的可持续更新策略,进而促进城市既有社区的可持续发展。
As global urbanization accelerates,the sustainable renewal of urban communities has emerged as a central focus in urban development.Sustainability assessment,encompassing design,construction,and management,serves as a vital quantitative tool for monitoring urban renewal processes and fostering sustainable community development.In recent years,governments and research institutions worldwide have developed various assessment systems to advance urban sustainability,ranging from tools for individual buildings to entire cities.This study begins by reviewing exemplary cases of sustainable urban community renewal,such as the Sino-Singapore Tianjin Eco-City and Masdar City in the UAE.These projects,by adopting sustainability assessment tools tailored to local climates,economies,and cultures,have successfully achieved holistic community sustainability.In contrast,projects lacking robust assessment frameworks often face challenges,such as ambiguous objectives and implementation difficulties.The study further examines established sustainability assessment systems,including LEED-ND,BREEAM Communities,and DGNB-NS,which address areas such as historic district revitalization,environmental improvements,and optimizing built environments.Despite their global prominence,these standards are largely designed for developed countries and struggle to address China’s unique urban renewal challenges,including aging infrastructure,residential environment upgrades,and transportation network optimization.Furthermore,community-scale assessment systems remain underdeveloped,offering limited applicability and maturity compared to tools for buildings or entire cities.Given the distinct social,economic,and environmental characteristics of cities,existing frameworks often fail to capture the specific conditions of Chinese urban communities due to subjective judgments and regional constraints.Therefore,developing a sustainability assessment system tailored to China’s context is a critical task for guiding community renewal and promoting sustainable development.This study proposes a comprehensive assessment framework for urban community renewal in China,offering precise guidance for sustainable development.By integrating qualitative expert input with quantitative analysis,the study establishes a multidimensional,hierarchical structure of sustainability indicator framework.Key indicators are identified through methods such as the Delphi technique,expert scoring,and literature reviews.Appropriate weights are assigned based on the relative impacts of various factors,using expert knowledge,practical experiences,and mathematical modeling.The framework evaluates community sustainability through quantitative analysis of indicators and aggregates these scores using weighted coefficients to derive an overall score.This process identifies communities requiring priority renewal and highlights critical issues,providing actionable insights for tailored renewal strategies.The framework emphasizes addressing key indicators with significant impacts while incorporating expert perspectives and resident needs to develop targeted solutions.Specifically,the assessment framework comprises four levels—objective,criteria,sub-criteria,and indicators—spanning three core dimensions:environmental ecology,social inclusion,and economic vitality.At the criteria level,core components such as land use,green buildings,and industrial vitality are analyzed.The sub-criteria level captures the community’s actual conditions,while the indicator level includes specific,measurable indicators linked to data collection and analysis.This framework includes three objective layers,11 criteria layers,26 sub-criteria layers,and 65 detailed indicators.The environmental ecology dimension evaluates aspects such as land use,green buildings,transportation,resource efficiency,and landscapes.The social inclusion dimension assesses residential environments,social services,safety,and operational management.The economic vitality dimension focuses on economic growth and industrial development.Additionally,the framework introduces an innovative bonus mechanism to encourage the integration of unique local characteristics and indicators.In addition,effective weight allocation is crucial given the varying influence of different factors.The study applies multiple-criteria decision-making(MCDM)methods,including TOPSIS,VIKOR,and GRA for objective weighting,and AHP,ANP,and BWM for subjective weighting.The chosen or integration of these methods ensures a balanced and scientific approach to weight allocation,enhancing decision-making accuracy in complex renewal scenarios.By analyzing community sustainability scores and indicators,the framework identifies priority renewal areas and critical issues.This provides a foundation for developing cost-effective and issue-specific strategies.Additionally,the study underscores the importance of involving community residents and neighborhood committees in refining the framework to align it with actual needs.In the digital era,artificial intelligence(AI)technologies offer transformative potential for sustainability assessments in urban renewal.AI can support data monitoring,processing,decision-making,and resident engagement,contributing to sustainable community development.Future research should further explore AI’s application in advancing intelligent and sustainable urban community renewal.