1.武汉大学资源与环境科学学院,湖北 武汉,430079
2.澳门城市大学城市与可持续发展研究院,澳门,999078
3.深圳市规划和自然资源数据管理中心,广东 深圳,518000
任福,教授,博士,长期从事地图学理论探索、在线动态专题地图系统研发、智能制图技术体系和行业专题地图服务研究等。E-mail:renfu@whu.edu.cn
石仪玮,博士,主要研究方向为城市地理计算与遥感图像智能解译。E-mail:yiweishi@whu.edu.cn
修回:2026-06-08,
纸质出版:2026-10-05
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任福,韩昊英,石仪玮,等.智慧城市知识框架:概念、内容与前瞻[J].测绘地理信息,2026,51(5):34-41
REN Fu,HAN Haoying,SHI Yiwei,et al.Smart City Knowledge Framework: Concepts, Content ,and Prospects[J].Journal of Geomatics,2026,51(5):34-41
任福,韩昊英,石仪玮,等.智慧城市知识框架:概念、内容与前瞻[J].测绘地理信息,2026,51(5):34-41 DOI: 10.14188/j.2095-6045.20250542.
REN Fu,HAN Haoying,SHI Yiwei,et al.Smart City Knowledge Framework: Concepts, Content ,and Prospects[J].Journal of Geomatics,2026,51(5):34-41 DOI: 10.14188/j.2095-6045.20250542.
从知识框架视角出发,对智慧城市的概念内涵、建设驱动力、内容体系及未来发展趋势进行了系统梳理。首先,基于“智、慧、城、市”的汉字语义,揭示其与信息、人文、物理和社会四类空间之间的映射关系,明确智慧城市“以数为底、以人为本、以城为体、以市为用”的逻辑本质。其次,从感知计算、空间智能与社会治理三个维度分析城市智能化建设的核心驱动力。进而在认知、技术与应用三个层面上,构建了“一个目标、二级问题、三元空间、四层架构、五块数据、六型思维、七类科技、八种模式、九大学科、十样场景”的多维内容体系,为智慧城市这一复杂系统的结构化理解提供支撑。进一步地探讨了智慧城市在全域数智化转型、以人为本的治理格局以及时空智能与数字孪生等方面的演进方向。相关结论为智慧城市系统演化提供理论基础,为技术体系构建、制度设计与场景实践提供结构化参考。
From the perspective of a knowledge framework, this study systematically examines the conceptual connotations, driving forces, content system, and future development trends of smart cities. First, by analyzing the semantic implications of the Chinese characters “Zhi , Hui , Cheng , and Shi ” ,the study reveals their intrinsic correspondence with four dimensions-informational, humanistic, physical, and social spaces—thus clarifying the underlying logic of smart cities as “data-driven, people-centered, city-anchored, and market-oriented.” Second, it identifies three major drivers of smart city development, namely sensing and computing, spatial intelligence, and social governance. Furthermore, the paper constructs a multidimensional content system across cognitive, technological, and application levels, encompassing “one overarching goal, two core problem domains, three spatial dimensions, four architectural layers, five data blocks, six cognitive perspectives, seven technology categories, eight operational patterns, nine disciplinary foundations, and ten application scenarios,” thereby providing a structured lens for understanding the complexity of smart city systems. Building on this framework, the study explores future directions such as holistic digital-intelligent transformation, people-centered governance, spatiotemporal intelligence, and urban digital twins. The proposed framework not only offers theoretical grounding for understanding the evolution of smart city systems, but also provides structured references for technology development, institutional design, and scenario-based implementation.
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