融合多源大数据的街道品质评估方法及应用策略研究——以厦门市中山路街区为例

Comprehensive Evaluation Method and Application Strategy of Street Quality based on Multi-source Big Data:A Case Study of Xiamen Zhongshan Road Block

在城市更新背景下,人本层面的品质提升是街道设计的核心目标,需要一套从使用者多样化需求出发、精准科学的综合评价体系对街道品质进行精准感知。研究以厦门市中山路街区为例,融合多源大数据构建以“功能多样”“景观丰富”“出行便利”“居住舒适”4个街道主导功能维度的评价指标,采用回归模型与层次分析法对指标体系进行校核、赋权和评分,进而形成了一套街道品质综合评价方法。基于评价结果,提出街道品质提升策略,并开发面向规划管理部门、设计部门和空间使用者的应用平台,便于城市规划的各方利益主体参与其中,从而为规划编制、管理和实践提供科学支撑,落实该评价方法的可操作性和应用性。

Under the background of urban renewal,the improvement of people-oriented quality is the core goal of street design,which requires a set of comprehensive evaluation system that starts from users'needs,covers multiple dimensions and is accurate and scientific to accurately perceive street quality.Taking the Zhongshan road block in Xiamen as an example,this study combines multi-source big data to build an evaluation index oriented to the four leading functions of the street,namely,"multiple functions""rich landscape""convenient travel"and"comfortable living",and uses regression model and analytic hierarchy process to check,weight and score the index system,thus forming a set of comprehensive evaluation methods for street quality.Based on the evaluation results,the street quality improvement strategy is put forward,and an application platform for planning management departments,design departments and space users is developed,which is convenient for all stakeholders in urban planning to participate in,thus providing scientific support for planning preparation,management and practice,and implementing the operability and application of the evaluation method.