Through an evolution from an emerging marketing narrative to a geographical fact around the globe, smart city is increasingly understood as a city’s effort to make itself smart. There seems no single city in the world to be commonly recognized as a real smart city yet, albeit many cities have already tried hard in this missionary commitment. Yet some common features can still be seen and identified, particularly from the urban governance perspective. This article explores the practice of smart city construction in China through a lens of governance by observing the interactive involvement of key stakeholders in the process. By taking three cities (Hangzhou, Wuhan, and Shanghai) in China as study cases, a conceptual framework is established in which three sets of actors, i.e., ICT-related enterprises, government, and civil society, and, accordingly, three types of approaches, i.e., ICT-led, planning-led, and place-making-and-community-oriented, are identified. It is found that the evolution of smart city construction rather follows a nonlinear trajectory and is very dependent on whether or not the primary actors and related stakeholders can form an affirmative acting power in triggering the city’s implementation. In other words, there is no “one-size-fits-all” approach to smart city construction. Each city may have its specialization in smartness based on awareness of and respecting its unique existing setting. The empirical study also shows that smart city construction tends to be converged in recognition that the core of smart city is not the smartness of technology but the smartness of all institutions and people enabled to utilize smart tools properly and efficiently in pursuit of people’s well-being, institutional capacity building, and better spatial arrangement towards a sustainable, resilient, and inclusive city in and for the future. From a geographical perspective, that is how to build a smart urban space to make the city a better place to not just accommodate but facilitate and meet people’s increasing demand for a better life in their living places.

With the vigorous development of industrialization and urbanization, rural space faces many difficulties in achieving sustainable development, such as the spatial structure being unbalanced. To explore the sustainable development of rural space, this study evaluates the spatial evolution and multi-scenario simulation of rural space with reference to the three dominant functions of land use, namely “production–ecological–living” (PEL), based on the interpretation of land use remote sensing data in 2000, 2010, and 2020. The change characteristics and the formation mechanism of the territorial spatial pattern were quantitatively analyzed by gravity center transfer, territorial spatial transfer matrix, standard deviational ellipse, geo-detector, and artificial neural network CA simulation. The results showed that (1) from 2000 to 2020, the rural production space in Beijing continued to decrease, the rural living space continued to increase and then gradually contracted, and the rural ecological space as a whole also showed a downward trend. (2) During the study period, the formation and evolution of the ecological spatial pattern of rural production and living in Beijing were affected by both regional physical geographical factors and human, social, and economic factors, with significant differences; the interaction between two driving factors is stronger than that within a single factor, and the main mode of action is double factor enhancement and nonlinear enhancement. (3) Compared with the other three scenarios, the performance of Beijing’s rural space in 2030 under the harmonious development scenario is more compact and stable, the rural production space is basically guaranteed, the intensity of rural living space is enhanced, and the overall situation of rural ecological space is stable. Our results show that in the future decision-making of rural land and space development around a metropolis, we should fully consider the evolution law of rural spatial pattern, as well as the driving force of natural geographical factors and economic activity factors and discuss the optimization and overall management of rural production and living ecological space through multi-scenario spatial simulation.