构建住房潜力数据标准，打通多源数据孤岛。
Housing Potential Common Data Model and City Digital Twin
- 提出通用住房潜力数据模型，统一多维度数据格式。
- 建成城市数字孪生系统与可视化仪表板，实现动态评估。
- 识别推广障碍并给出可操作的解决策略，适合城市规划者。
住房潜力评估需综合考虑区划、土地利用、人口特征及服务可达性等多方面因素。本研究提出住房潜力通用数据模型（HPCDM），旨在打破现有数据孤岛，为住房潜力分析所需各类数据集提供集成与互操作标准。报告详细阐述了该模型的评估过程，并构建了用于住房的城市数字孪生系统及试点仪表板应用，展示其实用化落地。除技术框架外，本工作还识别出推广中的关键障碍，并为城市规划者和利益相关方提供可行的应对策略。
原文摘要 · Abstract (English)
The evaluation of housing potential requires consideration of a location from multiple perspectives, ranging from zoning and land use to population characteristics and access to services. This research introduces the Housing Potential Common Data Model (HPCDM) to overcome existing data silos, serving as a standard to support integration and interoperability across the diverse range of datasets that are required for housing potential analysis. This report details the evaluation of the model along with the creation of a City Digital Twin for housing and a pilot dashboard application to demonstrate a practical implementation. Beyond the technical framework, this work identifies critical barriers to adoption and provides actionable mitigation strategies for urban planners and stakeholders.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。