| 摘要: |
| 城市数字孪生平台在近年来取得长足发展，但也暴露出“重物理精度轻社会认知”和“重场景应用轻数据体系”的问题，难以满足精细化城市治理的需求。因此，有必要界定以城市治理为导向的数字孪生平台应当具备哪些特征，并构建相应的精细化评估机制，以实现对于数字孪生城市实践的正确引导。为此本研究探索了映射率的方法体系，以数据为核心，围绕“有没有”、“活不活”、“连不连”的问题提出了数据分辨率、数据新鲜度和数据关联度3项指标，同时搭建了一套可量化、易推广的映射率评估模型，分别用于评估具体城市数字孪生平台项目中数据收集的完善程度、数据更新的及时程度以及数据网络的关联程度。进而以上海浦东新区花木街道数字孪生平台为例，对各项指标开展计算，并搭建了城市数字孪生平台数据映射率的实时评估平台。本研究围绕映射率实现了对以往难以评估的城市数字孪生平台发展质量的深入到数据层面的精细化解析，有助于推动城市数字孪生平台更好应对城市治理的复杂需求，促进“自下而上”的科学化城市治理体系建构。 |
| 关键词: 数字孪生城市 精细化城市治理 数据评估模型 数字孪生映射率 |
| DOI： |
| 分类号:TU98 |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| Building the Digital Twin Mapping Rate towards Refined Urban Management |
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ZHANG Yiping,CHEN Xinghan,LI Jianing,YE Yu
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| Abstract: |
| Digital twin city platforms have made significant progress in recent years. However, the existing platforms often have the problems of "focusing on accuracy of the physical model rather than social cognition" and "focusing on specialized application rather than data system,” which make it difficult to meet the actual needs of refined urban management. Therefore, it is necessary to define the characteristics of a digital twin platform oriented to urban management and build a corresponding refined evaluation mechanism to realize the guidelines for practice. This study explores the methodology framework of mapping rate, proposing three indicators: data resolution, data freshness and data relevance. A quantifiable and easily replicable evaluation model was built to assess the perfection of data collection, the timeliness of data updates, and the degree of data network correlation. Taking the digital twin platform of Huamu Street in the Pudong New Area in Shanghai as an example, each indicator is calculated and a comprehensive mapping rate evaluation is formed. This study further builds an actionable path for the development of the urban digital twin platform from L1 to L4 staging and a real-time evaluation platform for the mapping rate. This study achieves a quantitative analysis of the development quality of digital twin city platforms, which was previously difficult to assess. This study also helps to promote the digital twin city platform to respond to the complex needs of urban management and to facilitate the construction of a "bottom-up" scientific urban management system. |
| Key words: digital twin city refined urban management data evaluation model digital twin mapping rate |
