Search Results (86)

(1) Background: The provision of monofunctional or inadequately distributed services in urban park green spaces often constrains residents’ opportunities and diversity for outdoor activities, particularly limiting access and participation for specific age groups or activity preferences. However, functional nodes with temporal and spatial flexibility demonstrate high-quality characteristics of resilient and shared services through integrated development. Accurately identifying user demand provides a solid basis for optimizing the functional configuration of urban parks. (2) Methods: This study took the old city area of Zhengzhou, Henan Province, China, as a case study. By collecting and integrating various types of data, such as geographic spatial data, field investigation data, and behavioral observations, we developed a population demand quantification method and a modular analysis approach for park service functions. This framework enabled correlation analysis between diverse user needs and park services. The study further classified and combined park functions into modular units, quantifying their elastic and shared service capabilities—namely, the adaptive flexibility and shared utilization capacity of park services. Additionally, we established a demand-responsive evaluation system for identifying and diagnosing problem areas in park services based on multi-source data. (3) Results: The demand response index and diagnostic results indicate that the supply of fitness facilities—particularly equipment-based installations—is insufficient within the old urban district of Zhengzhou. Among the three user groups—children, young and middle-aged adults, and the elderly—the elderly population exhibited the lowest demand response index, revealing a significant gap in meeting their specific needs. (4) Conclusions: Based on the research findings, a three-tier optimization strategy is proposed: A. improve green space connectivity to expand the service coverage of parks; B. implement multifunctional overlay and coordinated integration in spatial design based on site characteristics and demand diagnostics; and C. increase the total supply of facilities to enhance spatial efficiency in parks. By integrating the demand assessment data and diagnostic results, this approach enabled a data-driven reorganization of service types and targeted allocation of resources within existing park infrastructure, offering a practical tool and reference for the planning of urban outdoor activity spaces. Full article

The integration of shared autonomous vehicles into historic urban areas presents both opportunities and challenges. In heritage-rich environments like very old Asian (such as Suzhou old town, which serves as a use case example) or European (especially Mediterranean coastal cities) areas—characterized by narrow alleys, dense development, and sensitive cultural landscapes—shared autonomous vehicle adoption raises critical spatial and social questions. This study employs a qualitative, user-centered approach based on the ripple model to examine residents’ perceptions across four dimensions: residential patterns, parking land use, regional accessibility, and street-level infrastructure. Semi-structured interviews with 27 participants reveal five key findings: (1) public trust depends on transparent decision-making and safety guarantees; (2) shared autonomous vehicles may reshape generational residential clustering; (3) the short-term parking demand remains stable, but the long-term reuse of space is feasible; (4) shared autonomous vehicles could enhance accessibility in historic cores; (5) transport systems may evolve toward intelligent, human-centered designs. Based on these insights, the study proposes three strategies: (1) transparent risk assessment using explainable artificial intelligence and digital twins; (2) polycentric development to diversify land use; (3) hierarchical street retrofitting to balance mobility and preservation. While this study is limited by its qualitative scope and absence of simulation, it offers a framework for culturally sensitive, small-scale interventions supporting sustainable mobility transitions in historic urban contexts. Full article

The inequity in the distribution of green spaces in megacities has a detrimental effect on the physical and mental well-being of their inhabitants, highlighting the necessity for careful and strategic urban planning, along with appropriate regulatory interventions. Nevertheless, scholarly articles addressing the equity of access to urban green spaces primarily concentrate on urban parks, with limited studies examining the influence of alternative types of green spaces. This research initially recognized and categorized informal green spaces (IGS) located within the Third Ring Road of Chengdu, utilizing the UGS-1m dataset and area of interest (AOI) data, in accordance with a well-defined classification framework. Then, the G2SFCA method and Gini coefficient were employed to assess the impact of IGS on the green space accessibility, especially scenario analysis of open and shared use of green space. The findings indicate that (1) IGS in the narrow sense constitute 21.2% of the overall green spaces within the study area, resulting in a reduction of the Gini coefficient by 0.103; (2) IGS in the broad sense, including public affiliated green spaces, shows an even more positive effect on improving the equity of green space supply, with a reduction of the Gini coefficient by 0.28; (3) there exists great spatial disparity in accessibility improvement effect by different types of IGS, so public policies must be customized to reflect local circumstances, taking into account the practicality and associated costs of management and maintenance of various IGS as well as accessibility enhancement; (4) certain older residential areas may not be amenable to effective enhancement through the use of IGS alone, and these should then adopt a multidimensional greening strategy such as green-roof. The findings of this research offer valuable insights for the planning and management of green spaces in densely populated urban environments, thereby aiding in the development of more refined models for the development of “Garden Cities”. Full article

Rapid urbanization in the Global South poses challenges to ecological integrity, cultural heritage, and equitable access to green infrastructure. This study evaluates the effectiveness of recent green infrastructure projects in Addis Ababa, Ethiopia, including flagship parks and upgraded road corridors, through the lens of the Urban Nature Futures Framework (UNFF). To operationalize the UNFF’s three perspectives—Nature for Nature (NN), Nature for Society (NS), and Nature as Culture (NC)—a context-specific set of indicators was developed through the existing literature, global assessment frameworks, and stakeholder consultations. A mixed-methods approach, combining structured surveys with both qualitative and quantitative thematic analysis, was applied across four stakeholder groups: residents, park visitors, corridor users, and experts. The results indicate that while social benefits (NS) are widely recognized, ecological (NN) and cultural (NC) dimensions receive comparatively less emphasis. Regression analysis shows that education, employment, and green space use frequency significantly shape perceptions of NS and NC, while NN are more consistently shared across groups. This study demonstrates the practical value of the UNFF as an assessment tool and offers a replicable methodology for evaluating multifunctional green infrastructure. The findings underscore the need for more inclusive, biodiversity-positive, and culturally grounded urban renewal strategies. These insights are relevant for planners and policymakers aiming to foster equitable and resilient urban environments in rapidly growing cities. Full article

This study aimed to check whether physical signs of children’s presence in the urban space have an impact on sense of safety and preferences. We based the study on an intra- and inter-group design, whereby respondents assessed two types of space: housing estates and green areas. The photos were manipulated to create three scenarios: control (without elements related to children), denotation (spaces supplemented with children’s playgrounds), and connotation (spaces containing elements associated with children). Each scenario was assessed by a separate group of respondents, who were further split between men and women. Analyses have shown that in residential districts, spaces with child-related connotations foster a feeling of safety and enhance the general appeal of the place, especially among women. In turn, direct signs of the presence of children (denotation) have a lesser impact on the positive assessment of the space. In green areas, adding child-related details did not affect women’s feelings but lowered men’s evaluations of safety and preference. The findings suggest that elements associated with children should be used selectively, taking into account the type of space and differences in perception between the sexes. These observations can support the creation of sustainable urban environments: safe and inclusive housing estate and park designs, especially in the context of building cities that foster social integration without exclusions. This is a preliminary study that paves the way for further exploration of the topic. In order to be able to analyse adults’ preferences and safety in more depth, it seems interesting to investigate the shared perception of landscape by children and adults and the possibilities of participatory design of public spaces. Full article

This paper shows a case study on a novel community-based sustainability planning framework that balances environmental, social, cultural dimensions for a high-density urban setting. The case study presents a community-driven “Four-Zero” sustainability model—zero energy, zero water, zero food, and zero waste—as a foundation for environmental sustainability practices implemented in a high-density estate in Hong Kong, alongside community-led ecological and heritage initiatives that reinforce place-based resilience. Through integrated activities, such as community farming, aquaponics, organic waste composting, biodiversity monitoring, and heritage mapping, the residents co-produced knowledge and activated novel bottom–up planning schemes and fostered social cohesion while advancing environmental objectives. Notably, the discovery of rare species and historic Dairy Farm remnants catalyzed a community-led planning proposal for an eco-heritage park that stimulated policy dialogues on conservation. These collective efforts illustrate how circular resource systems and cultural and ecological conservation can be balanced with urban development needs in compact, high-density communities. This case offers policy insights for rethinking urban sustainability planning in dense city contexts, contributing to global discourses on urban political ecology by examining socio–nature entanglements in contested urban spaces, to environmental justice by foregrounding community agency in shaping ecological futures, and to commoning practices through shared stewardship of urban resources. Full article

Most of the time, urban planning tends to exclude the specific needs and perceptions of women, resulting in spaces that fail to meet their safety needs. This study explores the impact of physical environment factors on women’s safety perceptions in neighborhood parks in Jordan. While a few studies on this topic have been conducted in Jordan, this research makes a unique contribution by focusing on the interaction between physical design factors and demographic characteristics, examining how these factors influence women’s safety perceptions. Focusing on women’s safety in neighborhood parks, a survey was conducted and involved a sample of 380 women, using a random sampling method. confirmatory factor analysis (CFA) was employed to identify underlying relationships between safety-related factors, while cluster analysis was used to group women based on their shared safety perceptions. The results revealed statistically significant differences and identified five distinct clusters, demonstrating varied perceptions of safety among women. This study emphasizes the importance of tailoring park designs to meet women’s specific safety needs, recognizing the diversity of priorities across demographic groups. The findings offer actionable insights for urban planners and policymakers, guiding the development of safer public spaces that respond to the varied needs of women. Full article

With the rapid development of geographic information technology, the expression of topographical spatial semantic relationships has become a research hotspot in the field of intelligent geographic information systems. Geographical spatial semantic relationships refer to the spatial relationships and inherent meanings between geographical entities, including topological relationships, metric relationships, etc. This study proposes a novel method of viewshed analysis, which solves the limitation of treating the viewshed as a unified unit in traditional viewshed analysis by decomposing the viewshed into multiple viewsheds and quantifying their spatial semantic relationships. The method uses a DBSCAN clustering algorithm with terrain adaptability to divide a viewshed into spatially different viewsheds and characterizes these viewsheds through a systematic measurement framework, including azimuth, area, and sparsity. The method was applied to a case study of Purple Mountain in Nanjing. The experiment used 12.5 m accuracy topographic data from Purple Mountain, and two observation points were selected. For the first observation point near the mountain park, during the DBSCAN clustering partition of the viewshed, the number of clusters and the number of noise points were compared with determine the neighborhood radius of 18 m and the minimum sample point number of 4. Five viewsheds were successfully generated, with the largest viewshed having 468 visible points and the smallest only 16, located in different locations from the observer, reflecting the spatial variability of terrain features. All viewsheds are basically distributed to the north of the observer, two of which also share the northeast 87° direction with the observer in a straight line distribution but at different distances. In three-dimensional space, the distance between the two viewsheds is 317.298 m. Azimuth angle verification showed significant aggregation in the northeast direction. The second point is near the ridgeline, where one viewshed accounts for 87.52% of the total viewshed, showing significant visual effects. One viewshed is 3121.113 m away from the observer, with only 113 visible points, and is not located at a low altitude, so it is suitable for a long-distance fixed-point intermittent observation. The experimental results of the two observation points reveal the directional dominance and distance stratification of viewshed spatial relationships. This paper proposes a model to express topographical viewshed spatial relationships. The model analyzes and describes the spatial features of the viewshed through quantitative and qualitative methods. These metric features provide a basis for constructing spatial topological relationships between observation points and viewsheds, helping optimize viewpoint selection and enhance landscape planning. Compared with traditional methods, the proposed method significantly improves the resolution of spatial semantic relationship expression and has practical application value in fields such as archaeology, tourism planning, and urban design. Full article

The dendroflora of an urban arboretum (The Botanic Park of Timișoara, Romania), consisting of 193 species, was ecologically characterized as bioforms, phytogeographical elements, and preferences for moisture, temperature, and soil pH. The aim of the research was to determine whether the native ecological requirements of the woody species, along with certain biological and evolutionary traits of them, such as plant life-form and plant family, could serve as tools for explaining and understanding the strategies employed by the urban woody phytocoenoses to acclimate and adapt to an established environment, such as an urban arboretum. The inventoried species are grouped in 111 genera and 45 families. The native and non-native dendroflora share 16 common families. The most representative family both in the native and non-native dendroflora is Rosaceae. The monotypic families are largely present (22.22% in the native dendroflora, and 42.22% in the non-native dendroflora). The plant life-form spectrum is dominated by megaphanerophytes (49%), followed by mesophanerophytes (41%). The chorological spectrum of the native species comprises 16 chorological types and is dominated by Eurasians (32%) and Europeans (30%). The species characteristics of the Pontic-Carpathian space, to which Romania belongs, are rare in the analyzed urban botanical park (4%). The mesophyte, mesothermal and slightly acido-neutrophilous species dominate both the native and non-native dendroflora. In the acclimation process of the non-native dendroflora, 37% of species exceeded their native requirements for moisture, 41% for temperature, and 50% for soil pH. The species requirements for temperature are associated to those for moisture and soil pH. The results show the potential of the analysed woody species to exceed their native requirements within the acclimation and adaption process, and in this process, for the studied temperate site, the plant life-form is important, and also the plant family. The species of the analyzed urban arboretum, both native and non-native, are taxonomically and biogeographically diverse, with specific habitat requirements, suggesting their great ability in acclimating, adapting and resisting. Full article

Urban parks enhance urban life by providing essential spaces for recreation, relaxation, and social interaction. However, there is a lack of understanding of how park settings influence usage patterns by socio-demographic characteristics. This study seeks to address this gap by exploring the association between park characteristics and gendered usage patterns across different times of the day. We employed big data analytics and computer vision techniques to analyze human behavior in two urban parks. These parks have comparable environments characterized by shared features, including paths, playgrounds, seating, lawns, greenery, and amenities. One is designed as a linear park, while the other is trapezoid-shaped. The distribution of facilities varies within the parks’ spaces. The key innovation of this approach lies in the use of computer vision for spatial analysis based on user-specific characteristics, particularly gender. City surveillance cameras are leveraged to gather extensive data on park usage. A comparative evaluation of the two urban parks includes a detailed examination of temporal and spatial usage patterns, offering new insights into the dynamics of urban park utilization. Findings reveal specific park features, such as playgrounds and paths, showed varying levels of utilization by different genders, highlighting the importance of tailored urban design. Males favored open lawns with dog facilities, whereas females preferred areas near playgrounds. The application of smart city technologies, such as city cameras, sets the stage for future directions in urban planning and design, highlighting opportunities to integrate advanced analytics into planning practices. Full article

The pollution and congestion caused by the shortage of parking spaces are threatening the sustainable development of cities. Smart parking platforms are one of the major tools to solve the problem by providing the efficient usage of parking resources. However, current platforms can only realize limited functions, and shared parking is far from being implemented on a large scale. Since off-street parking provides the majority of potential shared parking spaces, this paper takes periodic off-street parking lots as the starting point for opening the shared parking market. Based on data from the Ningbo Yongcheng parking platform, power spectral density (PSD) and the autocorrelation function (ACF) are used to identify periodic parking lots. A Density-Based Spatial Clustering of Applications with Noise (DBSCAN)-based method is applied to clustering the occupancy time series. Land use, user type, parking duration, and parking patterns are then analyzed to study shared parking supply characteristics. The results show that (1) 31.3% of off-street parking lots are periodic parking lots, and 90.3% of them have regular users exceeding 50%. (2) Periodic parking lots are classified into four types. Most parking lots show convex flat peak, double peak, or triple peak characteristics. (3) The shared parking spaces demonstrate spatial and temporal imbalances. But in a small area, even considering the concentration of land use and the peak period, there are still enough spaces available. The above research is of significance for the large-scale implementation of shared parking, which can promote the sustainable development of a city. Full article

Urban parks have become more important in residents’ daily lives owing to both rapid urbanization and increasing environmental pressures. Globally, there is growing concern regarding equitable access to urban parks, particularly in densely populated countries such as China. This study focuses on the accessibility and equity of urban parks in Jiujiang using walking route data obtained from an open-source platform through an application programming interface to assess park accessibility. We explored the equity of park accessibility from three perspectives: spatial, opportunity, and group equity. The results indicated that urban parks in central Jiujiang have significantly better accessibility than those in suburban areas. Less than half of the study area was covered within a 1500 m walking distance. There is a large service blind catchment in park accessibility. Similarly, disparities in the equity of park accessibility were observed. The Penpu sub-district has the best accessibility; in contrast, the Qili Lake sub-district benefits from less than 10% of park accessibility. Wealthier communities benefit more from park accessibility than disadvantaged communities. Our study aims to provide strategies for urban planning for policymakers. Strategies such as increasing park entrances, opening gated communities, and creating shared green spaces may help ensure environmental equity. Full article

With the continuous increase in car ownership, alleviating traffic congestion and reducing carbon emissions have become key challenges in urban traffic management. This study constructs a multi-agent model to evaluate the impact of various traffic optimization interventions on citizens’ travel behavior and traffic carbon emission levels. Different from previous mathematical models, this model integrates computer technology and geographic information systems, abstracting travelers as agents with self-control capabilities who can make independent decisions based on their own circumstances, thus reflecting individual differences in travel behavior. Using the real geographical and social environment of the high-density travel area in Xiaodian District, Taiyuan City as a case study, this research explores the overall improvement in the urban transportation system through the implementation of multiple traffic optimization interventions, such as a parking reservation system, the promotion of the park-and-ride mode, and the optimization of public transportation services. Studies have demonstrated that, compared to reducing bus fares, travelers exhibit a greater sensitivity to waiting times. Reducing bus departure intervals can increase the proportion of park-and-ride trips to 25.79%, surpassing the 19.19% increase observed with fare adjustments. A moderate increase in the proportion of reserved parking spaces can elevate the public transport load to 49.85%. The synergistic effect of a combined strategy can further boost the public transport share to 50.62%, while increasing the park-and-ride trip proportion to 33.6%, thereby highlighting the comprehensive benefits of implementing multiple strategies in tandem. When the parking reservation system is effectively implemented, carbon dioxide emissions can be reduced from over 800 kg to below 200 kg, and the proportion of vehicle cruising can decrease from over 20% to under 15%. These results underscore the critical role of the parking reservation strategy in optimizing traffic flow and advancing environmental sustainability. Full article

With the continuous increase in the number of vehicles worldwide, parking challenges have become more severe, making it a shared goal for governments to alleviate parking difficulties in urban centers. Shared parking has emerged as an effective solution to address parking problems and has been widely studied in recent years. However, existing research primarily focuses on static or single-period parking matching, often neglecting the conflicts between overdue parking users and subsequent users. Therefore, addressing the impact of overdue parking on shared parking systems is highly important. This study proposes a multi-period dynamic matching decision model (MDMD), which divides the operation period of the shared parking platform into multiple decision points. At each decision point, parking demands are classified into four categories: newly arriving demands, allocated demands with a start time not within the current decision point, overdue demands during the current decision point, and demands affected by overdue parking. Three decision variables are established to determine matching schemes for the first, second, and fourth types of parking demands, facilitating a dynamic decision-making process that effectively mitigates the impact of overdue parking. A corresponding algorithm is designed to solve the model. Since the single-period model is a linear programming model, the CPLEX solver obtains allocation schemes for each decision point. These schemes, along with new parking demands, are used as input for the next decision point, achieving a dynamic matching process. Simulation experiments are conducted to compare the MDMD model with the traditional First-Book-First-Served (FBFS) model based on platform revenue, parking space utilization, and parking demand acceptance rate. The experimental results show that, compared to FBFS, MDMD improves long-term earnings by 83%, actual profits in recent profits by 6.6%, and parking space utilization by 8% while maintaining a similar parking demand acceptance rate. To validate the robustness of the model, additional simulations are performed under various overdue probability scenarios, demonstrating that MDMD maintains stable system performance across different probabilities. These improvements highlight the advantages of the dynamic matching strategy, distinguishing this study from existing methods lacking adaptability. These findings provide valuable insights for the optimization of shared parking systems, contributing to sustainable transportation solutions and efficient urban mobility management. Full article

The market share of electric vehicles (EVs) is growing rapidly. However, given the huge demand for parking and charging of electric vehicles, supporting facilities generally have problems such as insufficient quantity, low utilization efficiency, and mismatch between supply and demand. In this study, based on the actual EV operation data, we propose a driver travel-charging demand prediction method and a fuzzy bi-objective optimization method for location and size planning of charging parking lots (CPLs) based on existing parking facilities, aiming to reduce the charging waiting time of EV users while ensuring the maximal profit of CPL operators. First, the Monte Carlo method is used to construct a driver travel-charging behavior chain and a user spatiotemporal activity transfer model. Then, a user charging decision-making method based on fuzzy logic inference is proposed, which uses the fuzzy membership degree of influencing factors to calculate the charging probability of users at each road node. The travel and charging behavior of large-scale users are then simulated to predict the spatiotemporal distribution of charging demand. Finally, taking the predicted charging demand distribution as an input and the number of CPLs and charging parking spaces as constraints, a bi-objective optimization model for simultaneous location and size planning of CPLs is constructed, and solved using the fuzzy genetic algorithm. The results from a case study indicate that the planning scheme generated from the proposed methods not only reduces the travelling and waiting time of EV users for charging in most of the time, but also controls the upper limit of the number of charging piles to save construction costs and increase the total profit. The research results can provide theoretical support and decision-making reference for the planning of electric vehicle charging facilities and the intelligent management of charging parking lots. Full article