Following the ‘people-oriented’ concept, increased attention should be paid to the heterogeneity of community residents when configuring public service facilities. Taking Shanghai as an example, this study analyzed the spatial pattern of urban and rural community differentiation and evaluated spatial differences in the level of accessibility to four types of public service facilities based on the shortest travel distance. There were significant differences between community types in Shanghai, with a clear circular structure in the urban and rural spaces. Here, facility accessibility decreased from the core to the periphery. Population density, income level, and the shortest walking distance to facilities revealed a significant negative correlation. Age level, household registration, and the shortest walking distance to facilities were partially weakly correlated or uncorrelated. The spatial matching of population density and facility accessibility simultaneously presented a circular pattern and heterogeneity, while planned new towns in suburbs and mid-suburbs presented a double-medium-sized match of the same community type. From the perspective of community differentiation, mechanisms behind the formation of the spatial pattern of facility accessibility included urban-rural pattern continuity and differences in allocation specifications, the continuity of population agglomeration and the accumulation of facility construction, and urban planning guidance and population agglomeration.

Community parks are the primary locations for urban residents to engage in nature, exercise, and establish social contact. This study used System for Observing Play and Recreation in Communities (SOPARC) to conduct field surveys of three typical community parks in Hangzhou, focusing on analyzing the differences in subspace vitality within community parks. First, we classified park spaces into four types: courts, lawns, fitness grounds, and pavilions. We selected 11 variables to assess the landscape features of the subspaces; then, visitor density, activity richness, activity evenness, and time stability were selected to quantify the vitality characteristics of the four space types. Finally, a mixed linear model was used to explore the relationship between landscape features and different types of spatial vitality and to select the key influencing factors affecting spatial vitality. The study found that (1) the vitality of different types of spaces in community parks differed significantly, showing three types of vitality. Among them, high activity richness and evenness, low visitor density and time stability were observed in courts and lawns. However, fitness grounds showed the opposite vitality pattern. Pavilions exhibited exceptionally high visitor density but low activity richness, activity evenness, and time stability. (2) The key influences affecting subspace vitality mainly include hydrophilicity and accessibility and exhibit enhancing or inhibiting effects on different types of spaces. The study found water-friendliness positively contributed to visitor density, activity richness, and time stability in all types of subspaces. Sports facilities increased visitor density and time stability on courts, lawns, and fitness grounds but reduced their activity evenness. Accessibility had an enhancing effect on activity richness but an inhibiting effect on the activity evenness of pavilions. We suggest that community parks be made more vibrant by adding natural elements to the space, installing multifunctional and compact facilities, and subdividing spatial functions.

With the acceleration of urbanization, climate problems affecting human health and safe operation of cities have intensified, such as heat island effect, haze, and acid rain. Using high-resolution remote sensing mapping image data to design scientific and efficient algorithms to excavate and plan urban ventilation corridors and improve urban ventilation environment is an effective way to solve these problems. In this paper, we use unmanned aerial vehicle (UAV) tilt photography technology to obtain high-precision remote sensing image digital elevation model (DEM) and digital surface model (DSM) data, count the city’s dominant wind direction in each season using long-term meteorological data, and use building height to calculate the dominant wind direction. The projection algorithm calculates the windward area density of this dominant direction. Under the guidance of K-means, the binarized windward area density map is used to determine each area and boundary of potential ventilation corridors within the threshold range, and the length and angle of each area’s fitted elliptical long axis are calculated to extract the ventilation corridors that meet the criteria. On the basis of high-precision stereo remote sensing data from UAV, the paper uses image classification, segmentation, fitting, and fusion algorithms to intelligently mine potential urban ventilation corridors, and the effectiveness of the proposed method is demonstrated through a case study in Zhuji City, Zhejiang Province.

With the advancement of urbanization and the impact of industrial pollution, the issue of urban ventilation has attracted increasing attention. Research on urban ventilation corridors is a hotspot in the field of urban planning. Traditional studies on ventilation corridors mostly focus on qualitative or simulated research on urban climate issues such as the intensified urban heat island effect, serious environmental pollution, and insufficient climate adaptability. Based on the high-precision urban remote sensing image data obtained by aeromagnetic oblique photography, this paper calculates the frontal area density of the city with reference to the urban wind statistics. Based on the existing urban patterns, template matching technology was used to automatically excavate urban ventilation corridors, which provides scientific and reasonable algorithmic support for the rapid construction of potential urban ventilation corridor paths. It also provides technical methods and decision basis for low-carbon urban planning, ecological planning and microclimate optimization design. This method was proved to be effective through experiments in Deqing city, Zhejiang Province, China.

Castells proposed that “space of flow” has multiple layers, and considered that transportation infrastructure is the carrier of its formation. However, few studies have focused on whether the infrastructure behind factor flows can provide sufficient support. In this paper, the basic supporting role of traffic networks in regional factor flows is examined. Firstly, we use traffic-connection data, enterprise-investment data and human-flow data to build a traffic network, enterprise-association network and inter-city-trip network, respectively. Then, we construct fitting models of the traffic network and the other two networks from two aspects: centrality and connection degree. Finally, this paper analyzes the standard residuals of the fitting results and looks for outliers that are greater than 1.65 or less than −1.65. Through outliers, we can find out where the traffic network cannot support the inter-city factor flows, and where the traffic network is too developed. The conclusions are as follows: First, the immaterial capital flows are still affected by the connectivity of transport facilities. With an improvement in traffic conditions, the capital links between cities can be enhanced correspondingly. Therefore, cities can gather more capital. Second, the attraction and radiation power of high-grade cities in terms of both human and capital flows are far beyond the traffic condition. They also motivate the neighboring cities to form a scale of capital- and human-flow connection that exceeds the average traffic conditions of the whole province. By analyzing the relationship between factor flows and infrastructure, and identifying mismatched networks, this paper will be helpful in many regards. It can provide guidance for Zhejiang Province in formulating transportation strategies. In addition, the conclusions can also provide decision-making support for optimizing regional infrastructure construction.