Promoting the development of collaborative innovation networks is crucial for cities to achieve sustainable innovation. Hangzhou was selected as a case study. Based on the cooperation patent data from 2000 to 2017, we examined the scale problem, calculated the topology, and analyzed the coordination mechanisms and spatial characteristics of the topology structure. The results show that in terms of the development trend, collaborative innovation is an important pathway for innovation, and multi-subject collaborative innovation is necessary. Collaborative innovation occurs between enterprises and between enterprises and universities. With regards to topological structure, we found “Zhejiang University as a center, other universities as cores”, with the characteristics of diffusion development and fragmentation. In terms of spatial structure, we observed a networked spatial organization model with multiple centers, such as universities and industrial parks. A circle with a radius of five kilometers around a university was found to be an area of highly concentrated innovation subjects that are synergistically associated with universities. On this basis, the laws are summarized and suggestions are provided to support the research and practice of urban innovation spatial planning in China.

The frequent occurrence of disasters has brought significant challenges to increasingly complex urban systems. Resilient city planning and construction has emerged as a new paradigm for dealing with the growing risks. Infrastructure systems like transportation, lifelines, flood control, and drainage are essential to the operation of a city during disasters. It is necessary to measure how risks affect these systems’ resilience at different spatial scales. This paper develops an infrastructure risk and resilience evaluation index system in city and urban areas based on resilience characteristics. Then, a comprehensive infrastructure resilience evaluation is established based on the risk–resilience coupling mechanism. The overall characteristics of comprehensive infrastructure resilience are then identified. The resilience transmission level and the causes of resilience effects are analyzed based on the principle of resilience scale. Additionally, infrastructure resilience enhancement strategies under different risk scenarios are proposed. In the empirical study of Zhengzhou City, comprehensive infrastructure resilience shows significant clustering in the city area. It is high in the central city and low in the periphery. Specifically, it is relatively high in the southern and northwestern parts of the airport economy zone (AEZ) and low in the center. The leading driving factors in urban areas are risk factors like flood and drought, hazardous materials, infectious diseases, and epidemics, while resilience factors include transportation networks, sponge city construction, municipal pipe networks, and fire protection. This study proposes a “risk-resilience” coupling framework to evaluate and analyze multi-hazard risks and the multi-system resilience of urban infrastructure across multi-level spatial scales. It provides an empirical resilience evaluation framework and enhancement strategies, complementing existing individual dimensional risk or resilience studies. The findings could offer visualized spatial results to support the decision-making in Zhengzhou’s resilient city planning outline and infrastructure special planning and provide references for resilience assessment and planning in similar cities.

Under the background of stock planning, improving the quality of urban public space has become an important work of urban planning, design, and construction management. An accurate diagnosis of the spatial quality of streets and the effective implementation of street renewal planning play important roles in the high-quality development of urban spatial environments. However, traditional planning design and study methods, typically based on questionnaires, interviews, and on-site research, are inefficient and make it difficult to objectively and comprehensively grasp the overall construction characteristics and problems of urban street space in a large area, thus making it challenging to meet the needs of practical planning. Therefore, based on street view images, this study combined machine learning with an artificial audit to put forward a methodological framework for diagnosing the quality issues of street space. The Gongshu District of Hangzhou, China, was selected as a case study, and the diagnosis of quality problems for streets at different grades was achieved. The diagnosis results showed the current situation and problems of the selected area. Simultaneously, a series of targeted strategies for street spatial update planning was proposed to solve these problems. This diagnostic method, based on a combination of subjective and objective approaches, can be conducive to the precise and comprehensive identification of urban public spatial problems, which is expected to become an effective tool to assist in urban renewal and other planning decisions.

Innovation is an inevitable way for cities to achieve sustainable development. The occurrence of innovation activities is a complex systemic behavior. Its spatial distribution has some location selection laws, which are the result of interaction and feedback between various spatial influence factors. We explain the impact mechanism from the microscale using a street unit in a city. Hangzhou was selected as a case study. First, we systematically selected factors influencing the spatial distribution of innovation activities as the independent variable based on the demands of innovation subjects. Patents were used as the dependent variable to represent the spatial distribution of innovation activities. Second, ensemble algorithms (Boosting) were used to analyze the influence contribution of independent variables to dependent variables. Then, based on the aspects of innovation driving force, which are innovation resources and innovation environments, relevant factors were divided into the following seven categories: innovation industry concentration, knowledge intensity, innovative talent resources, service facilities, external transportation convenience, public transportation convenience, and ecological environment. We interpreted the impact mechanism and made corresponding suggestions for urban innovation space planning.

After the decline of water transportation along the Grand Canal, the integration of urban development and the preservation of cultural heritage along the canal has become imperative. This paper takes the titled landscape as its research perspective and investigates the cultural significance of the canal through its historical, spatial, artistic, and spiritual dimensions, identifying the “Ten Canal Scenes” (TCS) that encapsulate both the canal’s heritage and the unique characteristics of Hangzhou, with the aim of establishing notable urban cultural landmarks. Archival analysis, average nearest neighbor (ANN) analysis, nuclear density analysis, and clustering of resource sites are first used to identify cultural landscape features. Evaluation and decision-making techniques are then used to comprehensively assess and categorize the conservation and utilization value for the TCS based on the value evaluation framework. Finally, it proposes strategies for enhancing the comprehensive values of titled landscapes and addressing socio-economic and cultural dimensions. These efforts seek to reconcile the preservation of the canal’s cultural heritage with the ongoing regeneration and development of the city and propose references for a localized canal development model based on titled landscapes.

Innovation districts, as a particular place for knowledge-based urban development strategies, have been praised for promoting sustainable economic developments. They have, however, been criticized for contributing to gentrification, urban inequality, and other problems that hinder sustainability. There has been little research addressing how planners maintain economic sustainability and promote the social and environmental sustainability of innovation districts. This paper takes Hangzhou as a case study, using the policy zoning—a new zoning method based on suitability evaluation—to formulate the applicable place plan for building innovation districts. The results show that the policy zoning can help planners arrange the construction of innovation districts in certain urban areas and take the most targeted measures to improve the sustainability of possible innovation districts. These measures include either enhancing the foundations of the metropolitan area or promoting innovation development by referring to suitability evaluation results. Planning based on policy zoning is of benefit to the sustainability of innovation districts through avoiding the impulsive behavior of policymakers, as well as promoting the better distribution of development achievements among the people, rather than concentrating on land developers and stakeholders who pursue maximum profits.