不动产大数据在城市更新潜力空间评估中的应用

我国在发展新常态与城市精细化治理背景下，对城市更新精准施策与量化评估提出了更高的要求。城市更新过程与人、地、房的相互作用紧密相关。不动产登记数据包含丰富的人、地、房空间属性信息，能够在城市的建成环境评估过程中发挥重要作用，现有城市更新评估模型几乎均未使用这一数据支持。本文从大数据量化评估视角出发，在文献研究的基础上，利用不动产登记大数据构建城市更新潜力评估体系，建立评估方法，并以南京市为应用案例，在街道（乡、镇）尺度上，对评估对象区域进行城市更新潜力的量化评估，实现精细化尺度的空间分析，辅助城市更新方向与选址，引导精准施策。

Application of real estate big data in spatial evaluation model of urban renewal potential

China’s development in the era of new normalcy and refinement of urban governance lift the demand for more accurate policy-making based on quantitative evaluations. While the process of urban renewal is closely related to the interaction of people, land and buildings, real-estate big data, which contains rich information about the people-land-building relationships, may provide a strong support for the quantitative evaluations related to urban renewal. However, few existing evaluation model has yet addressed the usage of this data. This paper proposes an evaluation model of urban renewal potential based on real estate big data. The model is applied to Nanjing on the Jiedao level, demonstrating the model’s ability in identifying Jiedaos’ suitability and directions for urban renewal, which contributes to more accurate policy-making in the urban development process.