Applied Geography最新文献_第3页

Spatio-temporal heterogeneity and influencing factors in the synergistic enhancement of urban ecological resilience: Evidence from the Yellow River Basin of China 协同增强城市生态复原力的时空异质性及其影响因素：来自中国黄河流域的证据

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-11-05 DOI: 10.1016/j.apgeog.2024.103459

Zhiheng Yang , Xuehua Cui , Yanling Dong , Jiawei Guan , Jing Wang , Zenglei Xi , Chenxi Li

Urban ecological resilience (UER) reflects the ability of cities to adapt to environmental changes and cope with natural disasters. Further, UER is an important perspective for understanding human–land relations in the Yellow River Basin (YRB). We constructed a novel system of UER evaluation indicators from the perspective of synergistic enhancement, with 99 cities in the YRB as objects for the research conducted from 2011 to 2021. The spatiotemporal heterogeneity and network pattern of UER were measured using the Theil index and modified gravity model. The factors influencing UER in the YRB were analysed using a multiscale geographically weighted regression model. The results show that (1) regarding time-series analysis, the UER in the YRB shows a fluctuating upward trend from 20.89 in 2011 to 26.23 in 2021, with the contribution of ecological image being the largest. The UER at different reaches, urban agglomerations, and cities varied considerably. (2) Regarding spatial analysis, the UER has a ‘center-periphery’ spatial distribution pattern dominated by provincial capital cities. The spatial network shows a '几'-shaped distribution pattern similar to the YRB mainstream distribution. Regarding UER connectivity, the ability for cross-regional joint development has improved. (3) The main influencing factors were urbanisation rate, education level, Normalized Difference Vegetation Index, and upgrading of the industrial structure, which represent urban development progress and geographical ecological characteristics. This study expands UER measurement and provides a basis and reference for synergistic enhancement of UER in the YRB.

城市生态复原力（UER）反映了城市适应环境变化和应对自然灾害的能力。此外，UER 还是理解黄河流域人地关系的重要视角。我们以黄河流域 99 个城市为研究对象，从协同增效的角度构建了一套新颖的 UER 评价指标体系，研究时间跨度为 2011 年至 2021 年。采用 Theil 指数和修正的引力模型对 UER 的时空异质性和网络格局进行了测量。采用多尺度地理加权回归模型分析了影响长滩区 UER 的因素。结果表明：(1) 从时间序列分析，长江河段 UER 呈波动上升趋势，从 2011 年的 20.89 升至 2021 年的 26.23，其中生态形象的贡献最大。不同河段、城市群和城市的 UER 相差较大。(2) 从空间分析来看，UER 呈现以省会城市为主的 "中心-外围 "空间分布格局。空间网络呈 "几 "字形分布，与长三角主流分布相似。在 UER 连接方面，跨区域联合发展的能力有所提高。(3) 城市化率、教育水平、归一化差异植被指数和产业结构升级是主要影响因素，代表了城市发展进程和地理生态特征。本研究拓展了 UER 的测量方法，为协同提升长三角地区的 UER 提供了依据和参考。

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引用次数: 0

Multiple local co-agglomeration: Modelling spatial-temporal variations of coworking spaces and creative industries clustering in two central European Capitals 多重地方聚集：欧洲中部两个首都的协同工作空间和创意产业集群的时空变化建模

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-11-04 DOI: 10.1016/j.apgeog.2024.103456

Pavel Bednář , Grzegorz Micek , Lukáš Danko

Economies of agglomeration play a crucial role in the creation of innovation in regional innovation systems. In the last decade, coworking spaces have become an organisational innovation of the sharing economy in these systems. Therefore, research on spatial co-agglomeration between coworking spaces and service industries is rising, identifying creative industries as the most significant services for colocation with coworking spaces. Previous studies on spatial association between coworking spaces and service industries have focused on the global distance measurement of their co-agglomeration. Hence, the paper provides insight into the extension of the research by comparing two cross-sectional datasets at different times by locally measured multiple colocations between coworking spaces and the selected creative industries in Prague and Warsaw. The present study is expected to contribute to understanding the spatial association in the long-term trajectories of coworking spaces with creative industries. The results underline the importance of the usage of local colocation quotients in space-time perspective for the detection of spatial association between coworking spaces and creative industries for determining trajectories of their spatial interactions, which resulted in both intensification and spatial diffusion of CBD functions in the adjacent inner city and along urban arterial roads supporting the polycentric metropolis model.

集聚经济在区域创新体系的创新创造中发挥着至关重要的作用。在过去十年中，协同办公空间已成为这些系统中共享经济的一种组织创新。因此，有关协同办公空间与服务业空间协同集聚的研究正在兴起，并将创意产业确定为与协同办公空间集聚的最重要服务业。以往关于协同办公空间与服务业空间关联的研究主要集中在协同集聚的全球距离测量上。因此，本文通过比较不同时期的两个横截面数据集，对布拉格和华沙的协同工作空间与所选创意产业之间的多重聚落进行了本地测量，从而为研究的扩展提供了深入的见解。预计本研究将有助于理解协同工作空间与创意产业长期轨迹中的空间关联。研究结果强调了从时空角度利用本地同位商数检测协同办公空间与创意产业之间空间关联的重要性，以确定它们的空间互动轨迹，这导致 CBD 功能在邻近内城和城市干道沿线的强化和空间扩散，支持多中心大都市模型。

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引用次数: 0

Pathways mediating neighborhood green spaces on emotions of populations with different mental health in Nanjing, China 中国南京社区绿地对不同心理健康人群情绪的影响途径

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-11-02 DOI: 10.1016/j.apgeog.2024.103457

Rui Ma, Min Zhang

Previous studies on the relationship between green spaces exposure and emotions paid limited attention to populations with varying mental health conditions, especially the pathways of influence on high-risk mental health populations are less clear. The current study explored the differences of pathways among people with varying mental health conditions using cross-sectional data from 859 individuals residing in 9 neighborhoods in Nanjing, China. Evident illustrate that the neighborhood safety associated with green spaces is important across all populations. The relationship between green spaces and emotional benefits is more complex in populations with good mental health Environmental attractiveness in serial mediation model was a crucial factor influencing later mediators. This study validated emotional benefits are more sensitive to buffer size. In future urban planning, coordinated interventions for different mental health populations should be emphasized.

以往关于绿地暴露与情绪关系的研究对不同心理健康状况人群的关注有限，尤其是对高危心理健康人群的影响途径不甚清晰。本研究利用南京市9个社区859名居民的横断面数据，探讨了不同心理健康状况人群的影响途径差异。结果表明，与绿地相关的邻里安全对所有人群都很重要。在心理健康状况良好的人群中，绿地与情感益处之间的关系更为复杂。在序列中介模型中，环境吸引力是影响后期中介因素的关键因素。这项研究验证了情感益处对缓冲区大小更为敏感。在未来的城市规划中，应强调针对不同心理健康人群的协调干预措施。

引用次数: 0

Unveiling the spatially varied nonlinear effects of urban built environment on housing prices using an interpretable ensemble learning model 利用可解释的集合学习模型揭示城市建筑环境对房价的空间非线性影响

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-10-31 DOI: 10.1016/j.apgeog.2024.103458

Xiaochang Liu , Renlu Qiao , Zhiqiang Wu , Tianren Yang , Xiuning Zhang , Xueliang Zhang , Zhiliang Zhu

The relationship between urban built environment (UBE) and housing prices manifests as complex, exhibiting significant nonlinearities and spatial heterogeneity that remain inadequately understood. Taking Shanghai as a testbed, this study employs a novel ensemble learning approach, augmented by Bayesian optimization and Monte Carlo simulation, to decipher the intricate and nonlinear impacts of UBE factors on housing markets across diverse urban geographies. Our analysis unveils substantial spatial variations in how transit accessibility, amenities, residential density, and green/blue spaces influence real estate values. Proximity to metro stations and bike-sharing facilities exerts a more pronounced positive effect than bus stops. Moreover, residents in central areas demonstrate a higher willingness-to-pay for public service amenities, while those in outer suburbs prioritize access to public transportation infrastructure. Intriguingly, it invokes an optimal threshold range of urban density for properties in new cities, thereby increasing the vitality and dense socio-economic networks. Furthermore, the sprawling suburbs have identified an adverse economic impact of large conservation green/blue spaces. These insights can guide policymakers in crafting spatially-tailored strategies that harness localized built environment drivers to catalyse equitable and prosperous urban development. Tailored policies informed by this spatially explicit understanding of nonlinear built environment-housing interactions can foster more sustainable, liveable, and inclusive cities.

城市建筑环境（UBE）与房价之间的关系错综复杂，表现出显著的非线性和空间异质性，但人们对这一关系的认识仍然不足。本研究以上海为试验平台，采用了一种新颖的集合学习方法，并辅以贝叶斯优化和蒙特卡洛模拟，来解读城市建筑环境因素对不同城市地域住房市场的复杂非线性影响。我们的分析揭示了公交可达性、便利设施、住宅密度和绿地/蓝地对房地产价值的影响存在巨大的空间差异。与公交车站相比，靠近地铁站和共享单车设施会产生更明显的积极影响。此外，中心区的居民对公共服务设施的支付意愿更高，而外围郊区的居民则优先考虑公共交通基础设施。耐人寻味的是，它为新城市的房产设定了一个最佳的城市密度阈值范围，从而增强了新城市的活力和密集的社会经济网络。此外，无序扩张的郊区还发现了大型保护性绿地/蓝地对经济的不利影响。这些见解可以指导政策制定者制定空间定制战略，利用本地化的建筑环境驱动因素来促进公平和繁荣的城市发展。通过对建筑环境与住房之间非线性相互作用的空间明确理解，制定有针对性的政策，可以促进城市的可持续发展、宜居性和包容性。

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引用次数: 0

The emergence of Industry 4.0 technologies across Chinese cities: The roles of technological relatedness/cross-relatedness and industrial policy 工业 4.0 技术在中国各城市的兴起：技术关联性/交叉关联性和产业政策的作用

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-10-30 DOI: 10.1016/j.apgeog.2024.103455

Xiaozhen Qin , Eddie Chi-Man Hui , Jianfu Shen

Industry 4.0 technologies have emerged as a focal point of regional technological competition in the Fourth Industrial Revolution. However, research on the emergence and determinants of innovation in Industry 4.0 technologies remains limited, especially in developing countries. Using Chinese patent data from 2001 to 2020, this study identifies the emergence of Industry 4.0 technologies across Chinese cities and explores the driving roles of relatedness/cross-relatedness and industrial policy in this process. Our findings indicate that relatedness/cross-relatedness between new technologies and Industry 4.0, Industry 3.0, and other technologies significantly increase the probability of a city developing a new specialization in Industry 4.0 technologies. The positive impact of relatedness within Industry 4.0 technologies indicates a self-reinforcing characteristic in their development. Furthermore, cross-relatedness between Industry 4.0 and Industry 3.0 technologies only promotes the specialization in Industry 4.0 technologies related to Industry 3.0 and benefits cities with a substantial Industry 3.0 foundation. Industrial policy also plays a crucial role, directly fostering specialization in Industry 4.0 technologies and indirectly enhancing the effects of relatedness/cross-relatedness. This study offers valuable policy insights for developing regional strategies to foster innovation in Industry 4.0 technologies.

工业 4.0 技术已成为第四次工业革命中区域技术竞争的焦点。然而，对工业 4.0 技术的兴起及其创新决定因素的研究仍然有限，尤其是在发展中国家。本研究利用 2001 年至 2020 年的中国专利数据，确定了工业 4.0 技术在中国各城市的兴起，并探讨了关联性/交叉关联性和产业政策在这一过程中的推动作用。我们的研究结果表明，新技术与工业 4.0、工业 3.0 和其他技术之间的关联性/交叉关联性会显著提高一个城市发展工业 4.0 技术新专业的概率。工业 4.0 技术内部关联性的积极影响表明，其发展具有自我强化的特点。此外，工业 4.0 和工业 3.0 技术之间的交叉关联性只会促进与工业 3.0 相关的工业 4.0 技术专业化，并使拥有大量工业 3.0 基础的城市受益。产业政策也发挥着至关重要的作用，它直接促进了工业 4.0 技术的专业化，并间接增强了相关性/交叉相关性的效果。本研究为制定促进工业 4.0 技术创新的区域战略提供了宝贵的政策见解。

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引用次数: 0

A multi-scale user-friendliness evaluation approach on cycling network utilizing multi-source data 利用多源数据对自行车网络进行多尺度用户友好度评估的方法

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-10-28 DOI: 10.1016/j.apgeog.2024.103454

Xiaoyang Deng , Zilong Zhao , Luliang Tang , Hong Yang , Yi Yu , Guineng Liao

Cycling is a promising solution to transportation decarbonization and urban sustainability. To enhance the cycling environment, it's essential to assess the user-friendliness of cycling networks. Existing related studies lack large-scale quantitative assessments and typically focus on segments, which are cost-ineffective for extensive spatial coverage and disregard the comprehensive impact of the cycling network system. Therefore, we propose a multi-scale user-friendliness evaluation approach for cycling networks utilizing multi-source geospatial data. First, we construct the cycling network using bike-sharing trajectory data. Then, to assess the user-friendliness of individual cycling segments as transportation spaces, we derive and evaluate six fine-grained quantitative indicators of bike lanes (separation, shade, width, pavement, slope undulation, and connectivity) from streetview images, DEM, and the aforementioned cycling topological network. Thirdly, cycling communities, representing inhabitants' daily living spaces, are detected based on trajectory density that informs cycling patterns, and their user-friendliness is evaluated by combining the performance of cycling segments with the spatial distribution of POI facilities within each community. An empirical study in Xiamen, China demonstrates the effectiveness of the proposed method in pinpointing specific indicators at particular segments/underdeveloped communities, thus guiding investment and optimization of cycling infrastructure to promote greater adoption of cycling as a mode of transportation.

骑自行车是实现交通脱碳和城市可持续发展的一个前景广阔的解决方案。要改善骑行环境，就必须评估骑行网络的用户友好性。现有的相关研究缺乏大规模的定量评估，通常只关注片段，对于大范围的空间覆盖而言成本效益不高，而且忽视了自行车网络系统的综合影响。因此，我们提出了一种利用多源地理空间数据对自行车网络进行多尺度用户友好性评估的方法。首先，我们利用共享单车的轨迹数据构建自行车网络。然后，为了评估单个自行车路段作为交通空间的用户友好性，我们从街景图像、DEM 和上述自行车拓扑网络中得出并评估了自行车道的六个细粒度量化指标（分隔、遮阳、宽度、路面、坡度起伏和连通性）。第三，代表居民日常生活空间的自行车社区是根据轨迹密度检测出来的，轨迹密度为自行车骑行模式提供了信息，通过将自行车路段的性能与每个社区内 POI 设施的空间分布相结合来评估其用户友好性。在中国厦门进行的一项实证研究表明，所提出的方法能够有效地确定特定路段/欠发达社区的具体指标，从而指导自行车基础设施的投资和优化，促进更多的人将自行车作为一种交通方式。

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引用次数: 0

Uncovering travel communities among older and younger adults using smart card data 利用智能卡数据发现老年人和年轻人的旅行群体

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-10-28 DOI: 10.1016/j.apgeog.2024.103453

Jiaomin Wei , Zihan Kan , Mei-Po Kwan , Dong Liu , Lixian Su , Yanyan Chen

Individual movements within transport networks create activity spaces that shape travel communities. However, few studies have examined the spatial structures within bus travel and the associated factors across different geographic areas, which may overlook the underlying travel patterns and characteristics within these communities. Taking one-month bus smart card data in Beijing, China as a case study, we first build spatial interaction networks for older and younger adults, and conduct analysis on various network measures. Then we detect travel communities using Leiden algorithm and further investigate the determinants for bus flows across different communities based on Poisson regression models. The findings indicate that older adults have a shorter peak interval, more localized activity spaces, lower network connectivity, and weaker interaction strength, suggesting limited mobility in bus travel compared to younger adults. The study highlights that travel duration and land use mix are important predictors for both groups regardless of geographic areas, and there are also differences in the factors influencing bus travel across various regional communities. The results of this study could better portray the mobility patterns, travel networks, activity structures, and determinants impacting bus travel flows among older and younger adults, thereby providing nuanced and efficient strategic support for urban transportation development.

交通网络中的个人移动创造了活动空间，形成了旅行社区。然而，很少有研究考察不同地域公交出行的空间结构和相关因素，这可能会忽略这些群体的基本出行模式和特征。以中国北京一个月的公交智能卡数据为例，我们首先建立了老年人和年轻人的空间互动网络，并对网络的各种指标进行了分析。然后，我们利用莱顿算法检测出行社区，并基于泊松回归模型进一步研究不同社区间公交车流量的决定因素。研究结果表明，与年轻人相比，老年人的高峰间隔更短、活动空间更本地化、网络连通性更低、交互强度更弱，这表明老年人在公交出行中的流动性有限。研究强调，无论在哪个地理区域，出行时间长短和土地使用组合对这两个群体来说都是重要的预测因素，而且在不同地区的社区中，影响公交出行的因素也存在差异。这项研究的结果可以更好地描述老年人和年轻人的流动模式、出行网络、活动结构以及影响公交出行流量的决定因素，从而为城市交通发展提供细致有效的战略支持。

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引用次数: 0

The proposal of a 15-minute city composite index through integrating GPS trajectory data-inferred urban function attraction based on the Bayesian framework 基于贝叶斯框架，通过整合 GPS 轨迹数据推断的城市功能吸引力，提出 15 分钟城市综合指数的建议

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-10-25 DOI: 10.1016/j.apgeog.2024.103451

Dong Liu , Zihan Kan , Jinhyung Lee

The chrono-urbanism framework suggests that urban life quality decreases with increased time spent in transportation, particularly motorized modes. The 15-min city concept, aligned with chrono-urbanism, emphasizes the importance of reaching essential urban functions within a short active travel time and has gained global attention. This study aims to develop a 15-min city composite index score (CIS) using the chrono-urbanism framework. The CIS integrates spatial accessibility to six key urban functions, providing a holistic assessment of the 15-min city status in Wuhan, China. Urban function accessibility is computed based on visitor volume inferred from GPS trajectory data using the Bayesian framework. Results reveal CIS hotspots in Hongshan, Wuchang, Jiangan, and Qingshan districts, with Hongshan having the highest concentration. However, Wuhan faces challenges in achieving comprehensive 15-min city status, as hotspots are mainly concentrated in specific areas like university towns and traditional city centers. The proposed assessment approach is applicable to accurately evaluate the 15-min status in other urban contexts using GPS trajectory data. The study's findings can assist policymakers in understanding CIS hotspot distribution and developing future planning policies to enhance the overall 15-min city status.

时间城市主义框架认为，城市生活质量会随着交通时间的增加而降低，尤其是机动车模式。与 "时间城市主义 "相一致的 "15 分钟城市 "概念强调了在较短的主动出行时间内到达基本城市功能区的重要性，这一概念已受到全球关注。本研究旨在利用时间城市主义框架开发 15 分钟城市综合指数（CIS）。CIS 综合了六大城市功能的空间可达性，对中国武汉的 15 分钟城市状态进行了整体评估。城市功能可达性的计算基于贝叶斯框架从 GPS 轨迹数据推断出的游客量。结果显示，CIS 热点集中在洪山区、武昌区、江岸区和青山区，其中洪山区最为集中。然而，由于热点主要集中在大学城和传统城市中心等特定区域，武汉在实现 15 分钟城市综合目标方面面临挑战。所提出的评估方法适用于利用 GPS 轨迹数据准确评估其他城市的 15 分钟状况。研究结果可帮助政策制定者了解 CIS 的热点分布，并制定未来的规划政策，以提高 15 分钟城市的总体水平。

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引用次数: 0

Towards ecological civilization: Spatiotemporal heterogeneity and drivers of ecological quality transitions in China (2001–2020) 走向生态文明：中国生态质量转型的时空异质性与驱动因素（2001-2020 年）

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-10-24 DOI: 10.1016/j.apgeog.2024.103439

Jiaxing Xin , Jun Yang , Huisheng Yu , Jiayi Ren , Wenbo Yu , Nan Cong , Xiangming Xiao , Jianhong (Cecilia) Xia , Xueming Li , Zhi Qiao

Global urbanization and climate change have a profound influence on the ecological quality (EQ) of China. In this study, utilizing the Google Earth Engine, we calculated the spatiotemporal heterogeneity of the China Remote Sensing Ecological Index (RSEI) for the period 2001–2020. We analyzed its drivers using land use, socioeconomic, and climate data. According to the results, the national average RSEI values for 2001, 2010, 2016, and 2020 were 0.39, 0.41, 0.46, and 0.45, respectively, and the proportions of the moderate and upper grades were 54 % in 2001, 64 % in 2010, 76 % in 2016, and 73 % in 2020. The RSEI value in the forest cover area was higher than that in the urban built-up and non-vegetation cover area by 0.1–0.2. The correlation coefficients between each variable and RSEI presented a ladder distribution (along the trend distribution of the Huanyong line). Moreover, maximum temperature (Tmmx) consistently contributed the most to RSEI (the contribution rate was between 35 % and 40 %), followed by precipitation accumulation (Pre, the contribution rate was between 18 % and 28 %), and then DEM, GDP, population (PPP), and wind speed (VS), all with relatively lower contributions around 10 %. Furthermore, temperature surpassing 24 °C, precipitation below 90 mm, population exceeding 50, or GDP above 10,000 showed a negative correlation with RSEI. This study analyzed the regional differences in RSEI drivers in different regions of China, providing a reference for local targeted improvement measures.

全球城市化和气候变化对中国的生态质量（EQ）有着深远的影响。在本研究中，我们利用谷歌地球引擎计算了 2001-2020 年间中国遥感生态指数（RSEI）的时空异质性。我们利用土地利用、社会经济和气候数据分析了其驱动因素。结果显示，2001 年、2010 年、2016 年和 2020 年的全国 RSEI 平均值分别为 0.39、0.41、0.46 和 0.45，中上等级的比例在 2001 年为 54%，2010 年为 64%，2016 年为 76%，2020 年为 73%。森林覆盖区的 RSEI 值比城市建成区和非植被覆盖区高 0.1-0.2。各变量与 RSEI 之间的相关系数呈阶梯分布（沿环永线趋势分布）。此外，最高气温（Tmmx）对 RSEI 的贡献率一直最高（贡献率在 35% 至 40% 之间），其次是累积降水量（Pre，贡献率在 18% 至 28% 之间），然后是 DEM、GDP、人口（PPP）和风速（VS），贡献率均在 10% 左右，相对较低。此外，气温超过 24 °C、降水量低于 90 毫米、人口超过 50 或 GDP 超过 10,000 都与 RSEI 呈负相关。本研究分析了中国不同地区 RSEI 驱动因素的地区差异，为当地采取有针对性的改善措施提供了参考。

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引用次数: 0

Analyzing disruptions in post-pandemic population return patterns: A network perspective on Chinese cities 分析大流行后人口回流模式的中断：中国城市的网络视角

IF 4 2区地球科学 Q1 GEOGRAPHY

Applied Geography

Pub Date : 2024-10-23 DOI: 10.1016/j.apgeog.2024.103448

Xiaoyuan Zhang , Minrui Zheng , Peipei Wang , Yin Ma , Xinqi Zheng

The COVID-19 pandemic has fundamentally reshaped global socio-economic structures, precipitating a profound transformation in people's lifestyles. An in-depth analysis of the disruptions in post-pandemic population returns patterns and the evolving driving factors can facilitate socio-economic recovery, development, and macro-control. This paper employs social network analysis to examine the spatial patterns and evolving urban locational attributes of the Population Mobility Network (PMN) during post-holiday returns in major Chinese cities amid the pandemic, assessing the impact of varying proximities on the PMN. The results indicate that: (1) During the pandemic, the geographic patterns of population mobility in China underwent significant fluctuations, with distinct regional and temporal variations, while intercity connections increasingly shifted toward shorter trips. (2) From 2019 to 2022, major Chinese cities experienced notable changes in status and connectivity, evolving into a multi-centric structure within the national population mobility network. (3) Community clusters predominantly adhere to provincial demarcations, maintaining stable structures within major urban agglomerations despite intense intra-regional competition, with clear distinctions in community stability between northern and southern regions. (4) Beyond traditional socio-economic factors, the level of digital finance has emerged as a new driver of population mobility, with the varied attributes of inter-city relationships also significantly influencing the PMN. Studying spatial patterns and urban location from the perspective of population mobility can inform post-pandemic optimization of national resource allocation and urban recovery strategies.

COVID-19 大流行从根本上重塑了全球社会经济结构，引发了人们生活方式的深刻变革。深入分析疫情后人口回流模式的混乱和不断变化的驱动因素，有助于社会经济的恢复、发展和宏观调控。本文运用社会网络分析方法，研究了大流行期间中国主要城市节后人口回流过程中人口流动网络（PMN）的空间模式和城市区位属性的演变，评估了不同的邻近性对人口流动网络的影响。结果表明(1）疫情期间，中国人口流动的地理格局发生了显著波动，具有明显的区域性和时间性差异，而城市间的联系则越来越多地转向短途旅行。(2）从 2019 年到 2022 年，中国主要城市的地位和连通性发生了显著变化，在全国人口流动网络中演变为多中心结构。(3）社区集群主要遵循省域划分，尽管区域内竞争激烈，但主要城市群内部结构保持稳定，南北地区社区稳定性差异明显。(4）除了传统的社会经济因素外，数字金融水平已成为人口流动的新动力，城市间关系的不同属性也对 PMN 产生了显著影响。从人口流动的角度研究空间模式和城市位置，可以为疫情后国家资源分配和城市恢复战略的优化提供参考。

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引用次数: 0