Rapid urbanization and intensified urban heat island effects have increased the need for effective, equitable cooling strategies. Urban green spaces (UGS), as nature-based solutions, provide critical cooling benefits that support thermal comfort and enhance urban resilience. However, disparities in cooling needs and access persist across gender and age, with vulnerable populations often facing unequal access to UGS resources. Despite growing attention to UGS equity, methods for quantifying demographic-specific mismatches between cooling supply and population demand remain underdeveloped. To address this gap, we developed a supply-demand evaluation framework to examine spatial equity and age- and gender-related environmental injustices in UGS cooling benefits in Fuzhou, China. The results show: 1) UGS cooling benefits supply and demand exhibit broadly similar spatial patterns across demographic groups but divergent patterns between the urban center and periphery. 2) Fuzhou's main urban area faces pronounced supply-demand mismatches, with elderly and female populations more affected by uneven resource distribution. 3) Significant disparities (p < 0.001) exist across age and gender groups, with children and middle-aged adults experiencing greater mismatches, while men face more severe supply deficits. Although UGS spatially favors vulnerable groups, substantial inequities in cooling access remain. Notably, targeted planning and management strategies were proposed for urban and green space systems, tailored to different population groups and types of supply-demand mismatch. This study highlights the urgent need for age- and gender-responsive UGS planning and offers a transferable approach to reduce cooling inequalities, supporting more equitable and climate-resilient urban environments.

Problem, research strategy, and findingsUrban parks offer residents significant physiological and mental health benefits, improving their quality of life. However, traditional park planning often treats parks as static spatial resources, neglecting their temporal dimension of visitation rhythms. With this study, we propose a paradigm shift in classifying, programming, and designing parks. Using 1.5 million mobile phone records, we classified 254 urban parks in Tokyo (Japan) based on their visitation patterns across different times of the day, week, and year. Our results showed that parks are rhythmized by seasonal events and daily activities, exhibiting complex visiting patterns shaped by the combined effects of preference variation and accessibility barriers. We conclude by discussing modes of action for temporal park planning practice.Takeaway for practicePark planners, designers, and policymakers should seek to incorporate temporality in activity-based park design and programming. This can be fulfilled in four ways: (1) tracing year-round, citywide park activities through data-driven methods; (2) implementing temporary and tactical designs for dynamic park demands; (3) establishing an inclusive park system that helps improve spatio-temporal equity; and (4) encouraging public engagement that cultivates the sense of time and identity.

Urban parks are widely recognized as an effective strategy for mitigating regional microclimate. While previous studies have focused on the cooling effect in summer, systematic assessments of multi-factor interactions across seasons remain limited. This study examined the seasonal cooling effects of 130 urban parks in Nanjing, China, using four indicators: two maximum-impact indicators (maximum park cooling area [PCA] and maximum park cooling efficiency [PCE]) and two accumulative-impact indicators (park cooling intensity [PCI] and park cooling gradient [PCG]). Results showed that over 77.7 % of parks exhibited cooling effects, with PCI and PCG showing significant seasonal variation. XGBoost model analysis revealed substantial differences in the importance of each category of factors on cooling indicators across seasons. Park geometric morphology had the highest importance for PCA throughout the year, whereas surrounding environmental factors dominated PCE in spring, autumn, and winter. Specifically, PA showed the highest importance in spring, summer, and extreme heat, with an optimal threshold of 17.389 ha. Geographical Detector analysis further confirmed that PA and PP were key drivers of PCA under extreme heat, and interactions between any two factors significantly enhanced explanatory power. These findings deepen the understanding of seasonal cooling mechanisms and provide insights for climate-adaptive urban park planning.

The concept of self-containment in new towns has been widely discussed from social and economic perspectives. However, localized interpretations within the context of China's development, particularly regarding climate adaptability and urban heat island (UHI) mitigation, are scarce. To fill this gap, our research analyzed self-containment from the perspectives of urban spatial scale and land use function. Focusing on Shanghai’s five new towns, we empirically demonstrated how self-containment influenced the UHI effects from 2005 to 2020, employing the Geodetector method. The findings reveal that during the daytime, the intensity of UHI in new towns decreased, serving as vital connectivity nodes of UHI within the region. Conversely, during the nighttime, both the intensity and area of UHI showed an increasing trend. The research confirmed that expanding the urban scale and functional diversity are effective strategies for mitigating the UHI. Based on these findings, we offer practical suggestions for the development of new towns: Increase population size while ensuring coordination with development scale; enhance mixed-use functions in large-scale development projects like university towns and industrial parks; and be vigilant of potential functional decline in central areas and increasing thermal impact due to new town development. Overall, this study enriches our understanding of self-containment in Chinese new towns and provides valuable insights for mitigating UHI in other similar contexts.

This study examines the effects of subway extension on housing prices in affluent urban neighborhoods, focusing on the Q-line extension in Manhattan, New York City. Utilizing synthetic controls and treatment effects estimators, distinct pricing trends across property types are revealed, particularly condominiums. The observed pricing dynamics deviate from the assumption that increasing supplies are associated with price discounts. Moreover, the connection between price discounts and noise complaints is not observed, highlighting the significant role of demand-side factors, especially neighborhood characteristics, in shaping housing prices. An unexpected demographic shift is observed, suggesting that the Q-line extension may disproportionately benefit non-white and low-income groups, challenging the prevailing gentrification narrative. We use the term “inverse premiumization” to denote the phenomenon where anticipated price increases in affluent neighborhoods due to transit improvements fail to materialize. Furthermore, our analysis of speculative behavior reveals a spike in short-term growth during the public notice period, gradually slowing down during construction and operation phases. These findings offer the nuanced adverse effects of subway extension on housing prices, contributing to our understanding of short-to medium-term price premiums and discounts. These insights are key considerations for city planners and policymakers navigating urban development, housing market, and speculative behavior dynamics.

The wildland-urban interface (WUI) represents landscapes where human settlements coexist with natural features. Trails within the WUI areas, valued for their ecological, recreational, and educational values, lack comprehensive research on landscape sensitivity influenced by both landscape and urban development. This paper addresses the gap by proposing a comprehensive landscape sensitivity index (CLSI) using multiple regression, cluster analysis, and correlation analysis. The Appalachian Trail (AT) serves as a case study to explore the characteristics of high sensitivity areas, considering various attributes and their connection with federal reserved land. Results show that eliminating covariance in landscape indices refines the landscape aggregation pattern, with Moran's I decreasing from 0.776 to 0.449, aligning with the observed fragmented landscape. In comparison to modified landscape indices (MLSI), the CLSI reveals that 85.6% of the area experiences changes in landscape sensitivity, with 42.5% of the AT region displaying significant landscape sensitivity, including 4.9% as having high landscape sensitivity (HLS), influenced by rock formations, wetlands, and biodiversity. A spatial mismatch is identified between HLS and current federal preservation efforts, with a correlation of only 0.011. The paper proposes tailored conservation strategies for HLS areas in urban, wilderness, and protected regions. Considering the combined impact of ecological and urbanization forces, this study assists in prioritizing land conservation objectives and finding a balance between wilderness protection and urban development.

New town developments aim to improve spatial layout and quality of human habitats in metropolitan areas. However, due to high-density compact development and inadequate long-term land use planning, new towns are vulnerable to urban heat island effects. This study addresses this concern by analyzing five new towns in Shanghai, using spatial pattern analysis to examine morphological conditions of urban heat island and Point-ofInterest datasets to derive functional characteristics. Geodetector is then used to detect the influence of land use function density on urban heat island. Findings reveal that new towns are more prone to urban heat island effects, with core-type dominant in suburban new towns, loop-type in sprawling new towns, and bridge-type in regional new towns. The study proposed targeted strategies based on morphological characteristics, including greenbelt transformations for core-types and using greenbelts to interrupt bridge-type connections. Findings also reveal strong thermal influence from public services, interactive effects of parks with other functions, and lower thermal influence from mixed education and commercial developments. Similar thermal mechanisms stem from spatial proximity and similar development patterns in new towns. Incorporating these target strategies into planning practice enables urban planners and policymakers to develop effective interventions against urban heat island in new towns.

Connected and Autonomous Vehicles (CAVs) are reshaping urban systems, demanding substantial computational support. While existing research emphasizes the significance of establishing physical and virtual infrastructure to facilitate CAV integration, a comprehensive framework for designing CAV-related infrastructure principles remains largely absent. This paper introduces a holistic framework that addresses gaps in current literature by presenting principles for the design of CAV-related infrastructure. We identify diverse urban infrastructure types crucial for CAVs, each characterized by intricate considerations. Deriving from existing literature, we introduce five principles to guide investments in physical infrastructure, complemented by four principles specific to virtual infrastructure. These principles are expected to evolve with CAV development and associated technology advancements. Furthermore, we exemplify the application of these principles through a case study in Oxford, UK. In doing so, we assess urban conditions, identify representative streets, and craft CAV-related urban infrastructure tailored to distinct street characteristics. This framework stands as a valuable reference for cities worldwide as they prepare for the increasing adoption of CAVs.

The rationality and efficiency of the spatial structure of an urban park system are critical in building a livable urban environment. Fractal theory is currently treated as the frontier theory for exploring the law of complex systems; however, it has rarely been applied to urban park systems. This study applied the aggregation, grid and correlation dimension models of fractal theory in Fuzhou, China. The spatial structure and driving factors of the urban park system were analyzed and an innovative model was proposed. The evidence shows that the spatial structure of the park system has fractal characteristics, although self-organization and optimization have not yet been fully formed, revealing a multi-core nesting pattern. Moreover, the core is cluster of four popular parks with weakening adsorption, and the emerging Baima River Park is located at the geometric center, which is likely to be further developed. The system structure is primarily driven by geographical conditions, planning policies, and transportation networks. Against this backdrop, an innovative model for the park system was proposed. The central park has heterogeneity and synergistic development, relying on the kinds of flow which can lead to the formation of a park city, a variation of a garden city. At the regional scale, relying on the geographical lines, the formation of a regional park zone could be realized. These findings provide new perspectives to reveal the spatial structure of urban park systems. The information derived can assist policy makers and planners in formulating more scientific plans, and may contribute to building a balanced and efficient urban park system.

为探究目标树经营对杉木人工林林分空间结构的改善效果,在3个林龄(8、12、21 a)的杉木人工林中分别设置3块标准地,选取4个空间结构参数(角尺度、大小比数、开敞度和竞争指数)与胸径因子构建单木综合评价指标模型来确定目标树、干扰木和一般木,通过模拟采伐干扰木,计算并分析间伐前后林分空间结构参数的变化.结果表明,林分空间结构单元多以1株中心木和5～6株近邻木构成;林龄为8、12和21 a的杉木人工林样地的干扰木数量分别占林分的33.93％、31.80％、11.20％;3个林龄各样地林木均为随机分布,林木分化明显,生长空间不足,竞争压力较大.经目标树抚育模拟间伐干扰木后,林龄为8、12和21 a的杉木人工林样地大小比数和竞争指数的平均值均降低,林木间竞争压力减小,竞争优势地位提升;林龄为8、12 a的杉木人工林样地角尺度和开敞度的平均值均增大,林木空间分布格局越来越优,生长空间大幅增加,而林龄为21 a的杉木人工林样地的改善程度不明显.

Land surface temperature (LST) is a joint product of physical geography and socio-economics. It is important to clarify the spatial heterogeneity and binding factors of the LST for mitigating the surface heat island effect (SUHI). In this study, the spatial pattern of UHI in Fuzhou central area, China, was elucidated by Moran’s I and hot-spot analysis. In addition, the study divided the drivers into two categories, including physical geographic factors (soil wetness, soil brightness, normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI), water density, and vegetation density) and socio-economic factors (normalized difference built-up index (NDBI), population density, road density, nighttime light, park density). The influence analysis of single factor on LST and the factor interaction analysis were conducted via Geodetector software. The results indicated that the LST presented a gradient layer structure with high temperature in the southeast and low temperature in the northwest, which had a significant spatial association with industry zones. Especially, LST was spatially repulsive to urban green space and water body. Furthermore, the four factors with the greatest influence (q-Value) on LST were soil moisture (influence = 0.792) > NDBI (influence = 0.732) > MNDWI (influence = 0.618) > NDVI (influence = 0.604). The superposition explanation degree (influence (Xi ∩ Xj)) is stronger than the independent explanation degree (influence (Xi)). The highest and the lowest interaction existed in ”soil wetness ∩ MNDWI” (influence = 0.864) and “nighttime light ∩ population density” (influence = 0.273), respectively. The spatial distribution of SUHI and its driving mechanism were also demonstrated, providing theoretical guidance for urban planners to build thermal environment friendly cities.

城市道路绿带是城市绿地系统的重要组成部分,绿地绿量对热岛效应的调控功能受到广泛关注.以福州市仓山区道路绿带为研究对象,基于2019年9月的Landsat-8 OLI/TIRS和12月的GF-1影像数据,利用辐射传输方程法进行地表温度反演,并采用面向对象分类法和分层分类法提取典型树种,结合实地测定叶面积指数完成对道路绿带绿量的计算,进而分析城市道路绿带绿量与地温的关系.结果表明:1)道路绿带对周边环境具有一定的降温作用;2)道路绿带的位置与面积差异会对其发挥降温效应产生影响;3)在不同绿带面积范围内,绿量与地温的关系不同.当绿带面积<1 hm2或>10 hm2时,地温分布几乎与绿量无关,在1～10 hm2面积范围内,二者呈负相关;4)绿量在绿带面积为1～4 hm2的降温效率优于在4～10 hm2,单位绿量可分别平均降温0.343℃ ～0.373℃、0.0878℃ ～0.1572℃.通过分析不同面积范围内城市道路绿带绿量与地温的关系,以期为缓解城市热岛效应,科学规划城市道路绿地提供新思路与理论指导.