Research on urban resource allocation optimization supported by population flow big data
人口流动大数据支撑城市资源配置优化研究

摘要

人口流动大数据为城市资源配置提供了更精确的决策依据。通过对不同时间、空间尺度上的人口迁移特征进行动态监测，可揭示常住人口结构变化、通勤规律及功能区活跃度等关键指标，并据此识别资源分布失衡的问题。依托多源数据融合与分析模型，可将人口流动趋势与公共服务供给、产业布局、交通承载能力等需求进行匹配，实现资源优化配置与调控路径的量化评估。研究以人口流动作为核心变量，构建数据驱动的资源配置优化框架，为城市治理精细化和政策优化提供科学支撑。

Abstract

Big data on population mobility provides a more precise basis for urban resource allocation. By dynamically monitoring migration patterns across different temporal and spatial scales, this approach reveals key indicators such as changes in permanent resident demographics, commuting patterns, and functional area activity levels, thereby identifying imbalances in resource distribution. Through multi-source data integration and analytical models, population trends can be aligned with demands for public service provision, industrial layout, and transportation capacity, enabling quantitative evaluation of resource optimization and regulatory pathways. This study establishes a data-driven framework for optimizing resource allocation, using population mobility as the core variable to provide scientific support for refined urban governance and policy optimization.