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The concept of city information modeling (CIM) has become increasingly popular in recent years. A literature review of previous CIM studies is presented in this paper. First, a bibliometric analysis of the current global CIM research is described, revealing that CIM has become a significant research hotspot. Next, three main research areas of the current CIM technique, namely data collection, integration, and visualization, are summarized to describe the characteristics of CIM research. Furthermore, some widely used CIM platforms are compared, and typical application cases of the CIM technique at different stages of the city life cycle are summarized. Finally, the current issues in CIM research are discussed, and future development directions are proposed. The findings of this study are expected to help researchers understand the current state of CIM and identify future development directions, thereby promoting CIM research development.

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Being the necessary data of the city-scale seismic damage simulations, structural types of buildings of a city need to be collected. To this end, a prediction method of structural types of buildings based on machine learning (ML) is proposed herein. Specifically, using the training data of 230,683 buildings in Tangshan city, China, a supervised ML solution based on a decision forest model was designed for the prediction. The scale sensitivity and regional applicability of the designed solution are discussed, respectively, and the results show that the supervised ML solution can maintain high accuracy for different scales; however, it is only suitable for cities similar to the sample city. For wide applicability for various cities, a semi-supervised ML solution was designed based on sampling investigation and self-training procedures. The downtowns of Daxing and Tongzhou districts in Beijing were selected as a case study for the designed semi-supervised ML solution. The overall prediction accuracies of structural types for Daxing and Tongzhou downtowns can reach 94.8% and 99.5%, respectively, which are acceptable for seismic damage simulations. Based on the predicted results, the distributions of seismic damage in Daxing and Tongzhou downtown were output. This study provides a smart and efficient method for obtaining structural types for a city-scale seismic damage simulation.

This article studies the lifetime interprovincial migration of the Canada‐born elderly (aged 60 and over), based on the data of the 1996 population census. The outcomes of the lifetime migration are found to be highly consistent with the human capital investment theory: there were substantial net transfers of migrants from the ‘have not’ provinces to the ‘have’ provinces, and the migrants moving in the ‘right’ direction, on average, achieved long‐term income improvements. However, the long‐term income improvements attributable to lifetime migration, both directly and indirectly via educational improvement, were in general not large enough to compensate for the disadvantages of being born in the ‘have not’ provinces and to francophone parents. The lifetime migration is also found to be highly selective by mother tongue and to have aggravated somewhat the spatial polarisation between Francophones and non‐Francophones.

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To improve urban seismic resilience, a reasonable seismic retrofitting scheme for buildings is required. Urban cities contain a large number of buildings, making it challenging to precisely assess the seismic retrofitting benefits of each one. This paper proposes a cost–benefit assessment framework that takes into account seismic risk, seismic damage, retrofit costs, economic losses, and cost–benefit analyses for the city-scale seismic retrofitting of buildings. The proposed framework adopts readily available building parameters, including the number of stories, construction year, total height, structural type, floor area, and response spectrum for structural design. It makes use of empirical seismic retrofitting models and a newly developed story-level seismic loss assessment method combining the physical mechanism and empirical loss ratios. For city-scale cost–benefit analysis, the framework can strike a good balance between data accessibility, computational workload, level of result details, and result accuracy. It can adapt nimbly to earthquake-induced indirect losses and budgetary constraints on retrofitting. The analysis of 98,618 buildings in Xi’an city, China, is carried out. The findings indicate that, when potential indirect economic loss ratios of buildings are neglected, the retrofitting benefits of unreinforced masonry and old buildings are the most significant.