Using Photography to Visualize Children's Culture of Play: A Socio‐Spatial Perspective

Visual methodologies have great potential to offer insight into children's culture and how it shapes childhood. We explore children's culture of play in an urban, low‐income neighborhood using photographs as a means of encouraging participatory research with elementary school students. Focus group interviews were conducted to validate children's perspectives on play, and all data were analyzed inductively using open coding to develop categories and emergent themes. Findings suggest that adults often define the physical boundaries of play, but children were largely able to determine the nature of their activities. Children's culture of play in this study highlighted issues of power and privilege, while concurrently emphasizing the socio‐spatial nature of childhood.     

复杂网络视角下时空行为轨迹模式挖掘研究

针对时空行为轨迹大数据的序列性、时空交互性、多维度性等复杂特性,构建结合时间地理学与复杂网络的分析框架,建立时空行为路径与时空行为网络之间的转换关系,利用复杂网络社群发现算法对时空行为轨迹进行社群聚类、模式挖掘与可视化。基于北京郊区居民一周内活动出行GPS轨迹数据的案例分析发现：① 复杂网络分析方法可以有效挖掘具有相似行为的群体特征和识别出典型的行为模式。② 可以灵活处理多元异构与多维度的行为轨迹大数据以及满足不同叙事、不同空间相互作用、不同时序的应用需求。③ 北京郊区被调查居民的行为模式存在日间差异与空间分异。     

社会感知视角下的若干人文地理学基本问题再思考

近年来,不同类型大数据在地理研究中得到了越来越多的重视,许多学者基于手机、社交媒体、出租车等数据开展了大量实证研究。社会感知概念刻画了地理空间大数据基于大量人的行为时空模式获取地理环境特征的的技术手段,该手段有助于重新审视地理学研究中的一些基本问题,因而本文选择了空间分布和空间交互这两个基本地理概念以及定性方法和定量方法这两个人文地理基本研究方法展开讨论。大数据从微观个体和宏观群体两个层面同时感知空间分布和空间交互,可以定量分析其中的距离以及尺度效应。进而,由于小样本访谈人群和场所是定性研究的基础,而大数据可以通过定量方法识别特定人群和场所并进行刻画,因此,社会感知手段为集成定性和定量研究方法,构建混合地理学奠定了基础。     

Integrating social network data into GISystems

Today, online social media outlets provide new and plentiful sources of data on social networks (SNs) and location-based social networks (LBSNs), i.e., geolocated evidence of connections between individuals. While SNs have been used to show how the magnitude of social connectivity decreases with distance, there are few examples of how to include SNs as layers in a GISystem. If SNs, and thus, interpersonal relationships, could be analyzed in a geographic information system (GIS) setting, we could better model how humans socialize, share information, and form social groups within the complex geographic landscape.

Our goal is to facilitate a guide for analyzing SNs (as derived from online social media, telecommunications, surveys, etc.) within geographic space by combining the mature fields of social network analysis (SNA) and GISystems. First, we describe why modeling socialization in geographic space is essential for understanding human behavior. We then outline best practices and techniques for embedding SN nodes and edges in GISystems by introducing terms like ‘social flow’ and ‘anthrospace’, and categorizations for data and spatial aggregation types. Finally, we explore case study vignettes of SNA within GISystems from diverse regions located in Bolivia, China, Côte d’Ivoire, Singapore, the United Kingdom, and the United States, using concepts such as geolocated dyads, ego–alter relationships, node feature roles, modularity, and network transitivity.     

我国省域创新产出的空间特征和时空演化——基于探索性空间数据分析的实证

以我国31个省域作为空间观测单元,以专利申请受理数作为创新产出的衡量指标,对我国1997～2008年期间省域创新产出的空间分布进行了探索性空间数据分析(ESDA)。通过计算区位基尼系数和集中度指数,发现我国的创新活动显示了相当高水平的空间集中,并且这种集中程度在过去的十多年里表现出了稳定的增长趋势;对全局的Moran’s I统计分析表明:省际创新活动之间存在着显著的空间自相关(空间依赖性),证明了知识溢出的存在性和空间局限性;对局部的Moran’s I分析进一步揭示了省际创新活动水平的相关模式,Moran散点图刻画了创新活动的空间集聚模式及其时空演变态势。研究结果说明经过十几年的发展,我国省域创新活动的地域性特征十分显著。     

Mapping spatiotemporal patterns of events using social media: a case study of influenza trends

Tracking spatial and temporal trends of events (e.g. disease outbreaks and natural disasters) is important for situation awareness and timely response. Social media, with increasing popularity, provide an effective way to collect event-related data from massive populations and thus a significant opportunity to dynamically monitor events as they emerge and evolve. While existing research has demonstrated the value of social media as sensors in event detection, estimating potential time spans and influenced areas of an event from social media remains challenging. Challenges include the unstable volumes of available data, the spatial heterogeneity of event activities and social media data, and the data sparsity. This paper describes a systematic approach to detecting potential spatiotemporal patterns of events by resolving these challenges through several interrelated strategies: using kernel density estimation for smoothed social media intensity surfaces; utilizing event-unrelated social media posts to help map relative event prevalence; and normalizing event indicators based on historical fluctuation. This approach generates event indicator maps and significance maps explaining spatiotemporal variations of event prevalence to identify space-time regions with potentially abnormal event activities. The approach has been applied to detect influenza activity patterns in the conterminous US using Twitter data. A set of experiments demonstrated that our approach produces high-resolution influenza activity maps that could be explained by available ground truth data.     

国内外社会空间分异测度研究综述

社会空间分异作为一个具有社会性及空间性的概念,其测度研究直接关系到隔离等级划分的合理性和有效性。本文根据不同历史时期空间分异测度研究所关注的视角,将社会空间分异测度研究分为早期萌芽阶段、多维度群体评估阶段、空间转向阶段、多模型多视角阶段等4个阶段,介绍了社会空间分异测度指标在各阶段的演变特点和主要测度指标,并对其中26个主要指数进行比较和分类,阐述各指数的适用范围和优缺点。分析国内社会空间分异相关研究现状,指出其存在多维度指标使用较少且多为实证性研究,空间分异测算方法缺少理论基础的不足。移动互联网和社交网络空间快速发展,对社会空间分异的测算方法提出新的要求;基于地理位置信息的个人行为空间交互数据和基于虚拟网络的赛博空间交互数据,为社会空间分异研究提供了新的研究视角。     

基于政府采购活动交易数据的东北地区城市网络研究

政企联系是企业外部联系的重要组成部分,基于政府采购活动交易数据构建的城市间供需网络可为城市网络研究提供一个新的视角。采用2018年中国政府采购活动的交易数据,构建东北地区供需城市网络,结合GIS空间分析和社会网络分析方法,揭示东北地区城市网络的空间联系格局和网络结构特征,并对其影响机制进行探讨。结果显示：中央项目层面,空间联系结构呈现出以长春为辐射中心,以哈大城市走廊为主要轴线的联系格局;地方项目网络主要表现为三省内分别以哈尔滨、长春及沈阳为中心的辐射状联系特征;且两种网络涉及节点和联系轴线数量明显不同。哈尔滨、长春及沈阳三大省会城市在网络中占据绝对中心位置,主要扮演着供应商的角色,同时城市网络中存在多个凝聚子群。基于政企联系的东北地区城市供需网络的空间结构受城市经济实力、行政壁垒、地理距离、项目预算来源以及政策引导等多方面的影响。     

行为地理学理论与方法的跨学科应用研究

行为地理学围绕空间与行为间的关系这一学科核心,不断完善理论基础、深化研究方法、拓展研究议题,逐渐走向多元化和社会化,发展成为人文地理学的重要分支学科,其理论、方法以及相应的成果也被广泛应用于诸多领域的研究与实践中。论文首先对行为地理学研究在理论、方法和应用方面的跨学科基础进行梳理,进而从城市规划与设计、移动性规划与管理和社会可持续发展与治理3个方面阐述行为地理学与不同学科相结合的应用,试图探讨行为主义思想对于地理学和相邻学科产生的影响,厘清围绕行为地理学开展应用研究的学科交叉脉络,进一步推进行为地理学的跨学科发展,探索未来的研究与应用方向。     

基于ESDA的河南艾滋病空间格局

以2008 年河南省地级市艾滋病分布数据为基础,利用ESDA空间数据挖掘的方法,对河南省艾滋病空间格局进行全面分析。结果表明：① 综合考虑河南省18 个地级市艾滋病确诊人数数据的空间自相关分析结果和不同传播途径感染单因素空间格局的结果,将河南艾滋病感染区域分为以FPD感染途径为主的豫南、豫东南高度流行区和以高危行为传播途径为主的豫北低度流行区;② 河南省艾滋病感染途径分布中,FPD感染、母婴感染、异性传播感染和注射吸毒传播具有明显的空间正相关,而同性传播途径与输血感染则显示出较大的空间随机分布特征;③ 与FPD 感染存在空间正相关的为注射吸毒传播、异性传播以及母婴传播方式,输血、同性以及其他方式传播途径与FPD感染途径分布不存在空间相关性。     

基于ESDA的城市社会空间研究——以上海市中心城区为例

以上海市中心城区为实证,在因子分析的基础上将ESDA方法应用于城市社会空间研究。运用全局Moran’s I指数、Moran散点图、LISA等指标和方法,从全局和局部两个层面研究了城市社会空间主因子的空间关联特征。结果表明,各主因子都存在显著的空间正相关,呈现趋同集聚,其中社会经济地位因子和居住条件因子的相关性明显强于其他因子,相近社会经济地位和居住条件的社会群体在空间上的集聚对形成城市社会空间的作用更为显著;各主因子都存在不同于全局的局部空间关联模式,存在显著的"热点"和"冷点"地区,其中社会经济地位因子和居住条件因子呈现出更为明显的"热点"和"冷点",具有显著的"同质集聚、异质隔离"特征。相关研究结论对于理解城市社会空间的形成具有重要意义,也可为进一步深入研究的典型案例选择及相关政策制定提供参考。     

南疆三地州贫困与旅游资源优势空间关联研究

2020年全面建成小康社会的目标对贫困治理更具现实意义。本文通过构建SOFM神经网络评估模型,聚类分析南疆三地州24个县市的经济--社会--自然多维度贫困。在评价县域旅游资源优势度的基础上,运用空间数据分析方法(ESDA)分析研究区县域贫困度和旅游资源优势度的空间分布格局,将两者在空间匹配后发现：①致贫因子集合向量的Matlab分类显示,南疆三地州各县市贫困类型可划分为经济型贫困、社会型贫困和生态型贫困,并且贫困空间聚合分布态势显著。②旅游资源优势区集中在地理环境结构复杂和多民族聚居的地区,如喀什市、塔县、阿克陶县、和田市;旅游资源优势区局域空间自相关呈现集群分布特征。③贫困类型与旅游资源优势在县域存在显著的空间关联,出现3类拟合性较好的区域。建议采取“旅游+旧城改造”和“旅游+商品基地”、“领头雁”旅游扶贫等旅游扶贫模式。     

NODAL HETEROLOCALISM AND TRANSNATIONALISM AT THE UNITED STATES‐CANADIAN BORDER*

ABSTRACT. Since the late 1990s Wilbur Zelinsky's theory of “heterolocalism’ has provided human geographers and other social scientists with a new approach to analyzing the spatial patterns and ethnic identities of recent immigrants in the United States. Zelinsky's heterolocal model suggests that, to a degree unknown in the past, new migrants in North American cities may choose to settle in widely dispersed places, rather than in more concentrated ethnic enclaves, while maintaining their ethnic identities. This article expands on and critiques prior work on heterolocalism in Oregon by examining the spatial patterns, ethnic and religious identities, and transnational relationships of two recent refugee groups in three urban areas in the Pacific Northwest. Using data from U.S. and Canadian census records, refugee resettlement agency files, survey questionnaires, structured and unstructured interviews, and participant observation with post‐Soviet Russians and Ukrainians in the Vancouver, British Columbia, Seattle, Washington, and Portland, Oregon metropolitan areas, I analyze the spatial patterns and related social networks that define the identities and residential and religious spaces of these groups to test the efficacy of relating heterolocalism and transnationalism across an international boundary.     

The relationship between walkability and neighborhood social environment: The importance of physical and perceived walkability

This study examines how both physical and perceived walkability is associated with neighborhood social environment. We analyze walkability and the 2004 Homeowner Survey data conducted in Franklin County, Ohio, and employ structural equation modeling. The empirical analysis shows that perceived walkability enhances neighborhood social environment while physical walkability does not. This study suggests that the negative relationship between physical walkability and neighborhood social environment is related to a spatial intersection between high physical walkability and socio-economic distress.     

行为地理学的学科定位与前沿方向

始自行为革命,行为地理学逐渐走向多元化的发展方向,不断扩展自身的理论框架和实践外延,反思并重新认识自身的意义,成为了人文地理学的重要组成部分。伴随着社会经济转型的深入,世界越来越向着多样化、个体性、动态化发展,人们的空间行为决策、选择的差异与个性越来越明显,空间与行为的交互越来越强,为行为地理学带来了新的发展机遇。论文通过梳理行为地理学的学科基础,提出行为地理学的学科定位与内涵外延,并指出行为地理学已经呈现出面向动态人地关系、面向个体生活质量及面向社会可持续发展3个前沿发展方向。在此基础上,论文对行为地理学面临的方法论、研究方法与跨学科的挑战进行讨论,并展望行为地理学的未来发展,以期为中国行为地理学的理论创新与实践探索提供启示。     

Assessing the social context of wildfire-affected areas. The case of mainland Portugal

Wildfires cause different impacts, depending on the conditions and resilience level of the exposed communities. Wildfire occurrence in mainland Portugal was assessed with regard to socioeconomic and demographic parameters, to identify the most distinctive conditions of fire-affected areas, without implying the existence of causal relationships. The latest population and agriculture census data were used to retrieve conditions at the civil parish level, regarding demographic patterns, social and labor conditions, physical structures and agricultural activities. To identify differences between parishes, two groups were created with the communities that showed the highest and lowest 20% of wildfire incidence between 2007 and 2014, separately for density of fire events and for burned area. A stepwise approach based on classification trees and random Forest methods was applied to identify the best discriminant variables between the groups. First, irrelevant variables were removed by an interactive process based on misclassification rates. The second step used random Forest analysis to the remaining variables to evaluate their importance in distinguishing the groups. In the final step, cluster analysis was applied to test the correspondence between the clusters created with the selected variables and the initial groups. Results showed that parishes with higher fire density have higher population density, higher proportion of young and educated people, larger families and more overcrowded buildings. On the contrary, parishes with larger burned area are less populated, less attractive to foreigners, have a higher proportion of elderly people, more degraded housing conditions and agricultural activities, visible in the density of sheep and goat and pastures, are still relevant. The cluster analysis demonstrated a better performance of the model for wildfire density, revealing a strong association with socioeconomic dynamics with an agreement above 0.85, much higher than for burned areas which is 0.29. Overall, the spatial distribution of wildfire impacts is framed by societal settings and particular conditions must be further understood to improve the coping capacity of affected communities.     

基于ESDA方法的黄土高原地区经济发展格局及其演化特征分析

探索式空间数据分析(ESDA)方法可以很好地揭示区域经济增长特征及其与空间环境的关系,是深入了解和把握区域经济的空间分布和演化规律的有效手段之一.本文基于ESDA方法,利用黄土高原地区284个县市级行政单元1990、2000和2007年3期的人均GDP数据,分析了黄土高原地区经济增长的空间分布格局和动态演变特征,验证了...     

Spatial crime distribution and prediction for sporting events using social media

ABSTRACT

Sporting events attract high volumes of people, which in turn leads to increased use of social media. In addition, research shows that sporting events may trigger violent behavior that can lead to crime. This study analyses the spatial relationships between crime occurrences, demographic, socio-economic and environmental variables, together with geo-located Twitter messages and their ‘violent’ subsets. The analysis compares basketball and hockey game days and non-game days. Moreover, this research aims to analyze crime prediction models using historical crime data as a basis and then introducing tweets and additional variables in their role as covariates of crime. First, this study investigates the spatial distribution of and correlation between crime and tweets during the same temporal periods. Feature selection models are applied in order to identify the best explanatory variables. Then, we apply localized kernel density estimation model for crime prediction during basketball and hockey games, and on non-game days. Findings from this study show that Twitter data, and a subset of violent tweets, are useful in building prediction models for the seven investigated crime types for home and away sporting events, and non-game days, with different levels of improvement.     

小尺度环境地形认知与空间行为的关系分析——以南京大学浦口校区为例

地形认知与空间行为间的交互影响是重要的人地关系,也是行为地理学近期重视的课题,但相关研究甚少。为考察日常活动中的上述交互作用,文章选择南大浦口校园为案例区,在预研究基础上,采用分层比例抽样,分别抽取认知与行为样本,并运用言语描述和草图方法获得被试的认知与行为数据。随后,通过绘制公共地形认知与行为地图及地理环境编码等定性方法,同时使用空间叠置与缓冲区及偏相关定量分析方法,得到以下结论：① 被试在认知地图中已编码了地形高程的等级秩序,基本认知了研究区的地形空间格局。② 校园行为节点以必要性活动场所为主,自发性活动与社会性活动场所为次;必要性活动路径分布于校园南部,呈直线,两端连接生活区和教学区;而自发性活动路径离散分布,连接更多的运动场所和环境景点。③ 地形认知与空间行为存在交互影响,具体表现为：地形认知影响了行为的空间格局,但此影响受行为的动机和效率认知的调控;反之空间行为是影响地形认知的主要因素,其影响受行为的动机与持续时间的调控。④ 宿舍位置是影响地形认知与空间行为交互作用的主要因素,而性别与学科的影响不显著。最后探讨了研究不足及发展方向。     

Qualitative GIS and the visualization of narrative activity space data

Qualitative activity space data, i.e. qualitative data associated with the routine locations and activities of individuals, are recognized as increasingly useful by researchers in the social and health sciences for investigating the influence of environment on human behavior. However, there has been little research on techniques for exploring qualitative activity space data. This research illustrates the theoretical principles of combining qualitative and quantitative data and methodologies within the context of geographic information systems (GIS), using visualization as the means of inquiry. Through the use of a prototype implementation of a visualization system for qualitative activity space data and its application in a case study of urban youth we show how these theoretical methodological principles are realized in applied research. The visualization system uses a variety of visual variables to simultaneously depict multiple qualitative and quantitative attributes of individuals' activity spaces. The visualization is applied to explore the activity spaces of a sample of urban youth participating in a study on the geographic and social contexts of adolescent substance use. Examples demonstrate how the visualization can be used to explore individual activity spaces to generate hypotheses, investigate statistical outliers, and explore activity space patterns among subject subgroups.