城市计算是计算机科学跟城市科学相融合的新兴领域。城市中多种来源的异构数据（即多源城市数据）是支撑城市计算的有效工具。然而，由于学科和行业之间的分割限制，现有的城市计算研究对于城市科学的相关知识利用并不充分，在多源数据应用的深度和广度上都不能满足城市研究的实际需求。针对这一现状，本项目组建了跨学科的研究团队，从多学科融合的角度，对城市计算中的多源数据建模与分析方法进行了深入研究。项目组针对城市数据在“时空结构”与“多系统耦合”方面的特殊性质，从“宏观”、“中观”、“微观”三个城市尺度上构建了一系列多源数据的融合与分析模型，解决了跨系统和多尺度的城市数据建模问题。本项目采用了“模型-案例”相结合的研究方式，在进行数据模型研究的同时，还对北京、深圳、无锡三座城市中的规划、交通、人口、卫生等典型案例进行了建模分析。研究成果在计算机科学和城市科学两个领域上都具有不错的理论价值和应用前景。

Urban computing is an interdisciplinary field fusing the computing science with traditional city science fields like transportation, civil engineering, economy, ecology, and sociology in the context of urban spaces. Heterogeneous data generated by a diversity of sources in cities, i.e., multi-source urban data, are strong supports for urban computing to tackle the major issues that cities face, e.g., air pollution, increased energy consumption and traffic congestion. However, limited by the discipline classification of computer science and city science, existing urban computing works does not fully utilize knowledge of city science. Therefore, it could not fully realize potential of multi-source urban data. In order to solve this problem, we are planning to study theories and methods of multi-source urban data modeling in this project from an interdisciplinary perspective with the assistance of computer science researchers and city science researchers. The project will develop a series of multi-source urban data integration and analysis models on the “macroscopic”, “medium-scopic”, and “microscopic” urban study scales based on the “spatio-temporal structuring” and “multiple systems coupling” features of city systems. These models should have capacity to integrate multi-source urban data crossing different urban systems and different city scales. In our program, the implementation of the project will use a “model-and-case” combination research mode, i.e., for each model, we will use real multi-source data of a case city to verify effectiveness of the model, and meanwhile, use the model to solve a challenge problem of the case city. In our plan, three Chinese cities: Beijing, Shenzhen, and Wuxi were selected as case cities. We will use the proposed models to analyze urban planning, transportation, population, and anti-epidemic problems of these case cities, and propose solutions to these problems. The expected modeling and case analysis research findings of this project could be very valuable for both urban computing field and city science related fields.