基于多源数据融合的成都市职住空间特征及影响因素研究

Employment-residence Space Characters and Their Influencing Factors Based on Multi-sourced Data Integration,Chengdu

传统的职住空间研究往往以单一数据为主,大数据的应用为更精细化、精准化地研究职住平衡带来了全新视角。文章发挥多源数据优势叠加效应,尝试构建一个系统全面分析职住空间分布及其耦合关系的方法框架,以成都市为例,科学、合理地识别其职住空间的分布特征、通勤出行特征,建立职住空间的动态联系,并围绕职住用地比例、住房产品结构、公服设施供给和交通出行环境四大影响因素,探寻职住失衡的原因,为后续有针对性地提出优化策略提供依据和参考。

Traditional researches on employment-residence space are mostly based on single source data,while big data has opened a new vista for more accurate research on balancing employment-residence space.Taking advantage of the overlapping effects of multi-sourced data,the paper establishes a methodological framework for the comprehensive analysis of employment and residential spaces distribution and their coupling relations.With Chengdu as an example,the paper recognizes the distribution of employment and residential spaces and the commuting characters,sets up the dynamic interaction between employment and residential spaces,and studies the reasons of their imbalance in land use percentage,housing structure,public service facility,and transportation environment.It provides a foundation and reference for future improvement strategies.