温州市新型冠状病毒肺炎时空分布格局演化分析

本文首先结合社交媒体信息和温州市新型冠状病毒肺炎（COVID-19）发展态势,获取疫情传播先验知识,进一步采用DBSCAN自适应聚类算法,分析温州市COVID-19时空分布格局与演化规律。结果表明：①温州市COVID-19易在20~59岁的青壮年人群,以及商业服务人员、农民和工人人群间传播;②我国针对人口流动采取的系列措施能够有效遏制疫情进一步蔓延,使得温州市聚类空间簇数量在时间上呈现先增加后减小的趋势;③温州市鹿城区银泰商贸附近、乐清市南部和瑞安市西部具有疫情扩散高风险,后期需增强防控力度。本文细粒度地分析了温州市疫情时空演化过程,能够更好地辅助温州市政府部门更精细地部署疫情防控措施。     

利用区域人群流动和新兴交通数据支持疫情防控

在传染病疫情早期,对出现疫情的地区进行及时管控、防止疫情跨区域传播,对于减少感染量、减轻疫区应对和救治压力、保障疫情期间社会经济平稳具有重要意义.防止疫情跨区域传播的前提是掌握现有病例在区域中的当前空间分布和预期空间分布.目前常用的人群流动数据仅能提供人群的长期驻留地点,而不能提供短期驻留地或者乘坐的交通工具信息,其对...     

Spatial-temporal modeling of initial COVID-19 diffusion: The cases of the Chinese Mainland and Conterminous United States

COVID-19 outbreaks in China in late December 2019, then in the United States (US) in early 2020. In the initial wave of diffusion, the virus respectively took 14 and 33 days to spread across the provinces/states in the Chinese mainland and the coterminous US, during which there are 43％ and 70％ zero entries in the space-time series for China and US respectively, indicating a zero-inflated count process. A logistic growth curve as a function of the number of days since the first case appeared in each of these countries accurately portrays the national aggregate per capita rates of infection for both. This paper presents two space-time model specifications, one based upon the generalized linear mixed model, and the other upon Moran eigenvector space-time filtering, to describe the spread of COVID-19 in the initial 19 and 58 days across the Chinese mainland and the coterminous US, respectively. Results from these case studies show both models shed new light on the role of spatial structures in COVID-19 diffusion, models that can forecast new cases in subsequent days. A principal finding is that describing the spatio- temporal diffusion of COVID-19 benefits from including a hierarchical structural component to supplement the commonly employed contagion component.     

城市时空大数据驱动的新型冠状病毒传播风险评估——以粤港澳大湾区为例

2019年末至2020年初新型冠状病毒(COVID-19)的快速传播对中国与世界的公共卫生带来巨大的挑战。如何科学合理地评估新型冠状病毒传播风险并制定相应防疫管控措施,是各国所面临的难题,也是科学防治与精准施策的重要依据之一。作为我国最重要的城市群之一,粤港澳大湾区受本次新型冠状病毒影响较大,且春节假期后大量的复工回流人口进一步带来潜在的传播风险。本文面向粤港澳大湾区新型冠状病毒传播风险评估的紧迫需求,结合大湾区多源城市时空大数据与流行病动力学模型,构建适宜大湾区的改进模型,并对新型冠状病毒在大湾区的传播风险和各类防疫管控措施效果进行评估与模拟。首先,引入动态复工回流人口和聚集热点改进现有动力学模型(SEIR模型),对现有动力学模型在不同空间评估单元的传播参数进行纠偏,加强模型在大湾区评估中的适宜性;利用手机信令等多源城市大数据,构建更精细化的人口、疾病流动矩阵和相应的传染病动力学模型,以满足各级防疫部门精细化(如村(社区)级)风险评估的迫切需求。模拟结果表明,相对经典SEIR模型,改进模型在大湾区的传播风险评估中具有更强的适宜性;大湾区高强度的人口流动为病毒的传播带来较高的风险;防疫部门所采取各类管控措施对病毒在大湾区的传播具有较强的抑制作用。     

Investigating factors in indoor transmission of respiratory disease through agent-based modeling

The transmission of respiratory diseases such as COVID-19 is exacerbated in densely populated urban areas and crowded indoor settings. Despite the majority of transmissions occurring in such settings, controlling viral spread through individual-level contacts indoors remains challenging. Experimental studies have investigated the transmission patterns of respiratory behaviors such as coughing or sneezing in controlled spatial environments. However, the effects of dynamic movement and spatial structures have been ignored, making it difficult to apply findings to urban policy and planning. To address this gap, we developed agent-based simulations to investigate individual virus inhalation patterns across multiple scenarios in a symmetrical and formulaic indoor space. We conducted sensitivity analysis using regression emulator models to identify significant factors for viral transmission. Our results indicate positive associations with viral transmission in descending order of: (1) stay time; (2) encounter frequency; and (3) initial infected population; while negative associations are: (4) mask wearing; (5) distance to infected people; (6) nearest infected people's mask wearing; and (7) distance to entrance. We also found that narrow passages between obstacles increase virus transmission from breathing. Furthermore, we conducted a case study to investigate the potential of reducing the amount of individually inhaled virus by controlling behaviors and spatial environments. Our findings suggest that mask wearing and reduced stay time can substantially reduce transmission risk, while a large number of contacts and high grouping time result in the growth of the infected population at a certain threshold. These results provide guidance for decision makers to formulate guidelines for curbing the spread of respiratory diseases in indoor spaces.     

山东省人口分布及空间相关性研究

借助MapInfo7.0平台及其二次开发语言MapBasic对山东省108个县市的人口分布及其空间相关性进行了研究,结果表明:1995-2006年间,山东省各县市人口分布的不均衡指数和集中指数分别由0.0178和0.1306增长到0.0198和0.1454,人口稠密区和人口稀疏区的密度差在不断增大;人口密度分布呈现显著...     

Analysis of population dynamics using satellite remote sensing and US census data

The population dynamics from 1991 to 2006 for the seven-county Twin Cities Metropolitan Area (TCMA), Minnesota, USA, was analysed in this study. Per cent impervious surface areas (%ISA) for 1991, 1999 and 2006 were derived from Landsat Thematic Mapper (TM) images and were modified using two different masking methods. The modified %ISA images of 1991 and 1999 were correlated with 1990 and 2000 census block group data of the ‘two highly developed counties’, ‘five suburban counties’ and ‘all seven counties.’ Populations of both years were then modelled, assessed and compared. Next, the statistical models based on the 1999 %ISA and 2000 census data were applied to the 2006 residential %ISA image to estimate the 2006 population. These 2006 estimates were compared with census county-level population projections for 2006. In comparison to Method A, which uses ‘adjusted %ISA images’ by masking out highway centrelines and areas that have greater than 75% imperviousness, Method B based on ‘pure residential %ISA image’ has higher coefficient of determination (R ²) and much lower, consistent mean absolute relative errors (MARE). For both methods, the strongest R ² and lowest MARE values between modelled population density and true density were found in the five-county model, followed by the seven-county model. The two-county model ranks last in terms of model performance for both years. In general, populations for the two highly developed counties were underestimated whereas the opposite was true for the five suburban counties. Population was most accurately estimated based on data from counties with the same or similar characteristics. By comparing the 1990/1991 and 1999/2000 models, we also found that the rate of population density per unit of impervious surface declined from 1991 to 1999. High accuracy was achieved when applying the 1999/2000 model to predict the 2006 population, suggesting that the relationship between per cent imperviousness and population density were relatively stable between 1999 and 2006.     

Mapping the spatial disparities in urban health care services using taxi trajectories data

The understanding of spatial inequality in health care services is critical for reasonable policy‐making and management. In this study, we present a novel approach to analyze the demand–supply of health care services using taxi data. Taxi data provide observations of individual travel activities, and hence can be used to characterize the actual demand–supply of health care services. We apply the proposed approach in Guangzhou, China to carry out a case study. The results show the spatial disparities in health care service access. About 21.05% of the total population has high hospital accessibility, while the remaining 78.95% has relatively low hospital accessibility (i.e., roughly an “80/20” distribution). It is found that 6.29% of the population lives in high‐density suburban communities but has relatively low hospital accessibility. Most of the hospitals serve a population that is compatible with their capacity. One hospital is found to have a small capacity but to serve a large population, while two hospitals have relatively high capacities but serve small populations. These findings can help improve our understanding of spatial inequalities in public service provision, and may also provide useful information to address the health care problems of an aging population in contemporary, rapidly urbanizing China.     

Spatial rules that generate urban patterns: Emergence of the power law in the distribution of axial line length

This paper studies emergence/generation of power law in rank-order distribution of axial line length, which is a global pattern observed in real cities, due to interaction of a set of seven simple spatial rules at a local scale. These rules and their interactions form a model expected to simulate the morphological structure of free spaces in unplanned organic pedestrian small cities. Effects of each of the seven rules are discussed through repeated simulations of eight possible combinations of the rules, using a bottom-up process. The results show that the rules generate environments with statistically stable rank-order distribution of axial line length that follows the power law. It means that the axial maps of the simulated environments have a scale-free hierarchical structure such that their distributions lean toward short axial lines. It also represents dominance of local spatial structure, as the model renders a faster rate of growth at a local scale while allowing a steady growth at a global scale.     

Linking remotely sensed Urban Green Space (UGS) distribution patterns and Socio-Economic Status (SES) - A multi-scale probabilistic analysis based in Mumbai,India

Urban Green Spaces (UGS) offer social and environmental benefits that enhance quality of life of the residents. However, due to the underlying social and economic disparities, different sections of urban population have disproportionate level of access to UGS. The environmental inequity owing to the varied UGS distribution poses a challenge to urban planners in efficient resource allocation. This study attempts to counter this challenge using a novel remote sensing-based approach. The variations in UGS distribution (in terms of quantity, quality and accessibility) across the neighbourhoods in Mumbai vis-à-vis the socio-economic status (SES) of neighbourhood residents are assessed using remote sensing-based indicators. Further, as these indicators are susceptible to the effect of changing scales, a multi-scale approach is adopted to study the potential variations in the relationship between SES and spatial metrics of UGS with spatial resolution. The neighbourhood SES was assessed using the newly developed Socio-Economic Status Index (SESI) and the neighbourhoods were classified into multiple SES categories. The UGS were extracted from remotely sensed data using Normalized Difference Vegetation Index (NDVI), and their spatial distribution aspects were characterized using indicators at neighbourhood level. The variations in indicators of UGS distribution in the neighbourhoods belonging to different SES categories were analysed using a logistic regression model. The results showed that, while quantity of UGS is not statistically associated with neighbourhoods SES, the quality and accessibility aspects of UGS share a statistically significant relation with SES. Also, this relation was found to vary significantly with spatial resolutions. Further, it was found that the neighbourhoods with higher SES in Mumbai have a better access to green spaces, indicating spatial inequities in UGS distribution in Mumbai. This study has important implications for planning equitable green spaces in cities that are currently in urbanization transition.     

Analysis of geographical disparities in temporal trends of health outcomes using space–time joinpoint regression

Analyzing temporal trends in health outcomes can provide a more comprehensive picture of the burden of a disease like cancer and generate new insights about the impact of various interventions. In the United States such an analysis is increasingly conducted using joinpoint regression outside a spatial framework, which overlooks the existence of significant variation among U.S. counties and states with regard to the incidence of cancer. This paper presents several innovative ways to account for space in joinpoint regression: (1) prior filtering of noise in the data by binomial kriging and use of the kriging variance as measure of reliability in weighted least-square regression, (2) detection of significant boundaries between adjacent counties based on tests of parallelism of time trends and confidence intervals of annual percent change of rates, and (3) creation of spatially compact groups of counties with similar temporal trends through the application of hierarchical cluster analysis to the results of boundary analysis. The approach is illustrated using time series of proportions of prostate cancer late-stage cases diagnosed yearly in every county of Florida since 1980s. The annual percent change (APC) in late-stage diagnosis and the onset years for significant declines vary greatly across Florida. Most counties with non-significant average APC are located in the north-western part of Florida, known as the Panhandle, which is more rural than other parts of Florida. The number of significant boundaries peaked in the early 1990s when prostate-specific antigen (PSA) test became widely available, a temporal trend that suggests the existence of geographical disparities in the implementation and/or impact of the new screening procedure, in particular as it began available.     

基于多源信息与深度学习特征提取的人口空间抽样方法

人口抽样调查是通过人口样本估算区域人口总体的一种手段。由于人口分布通常具有空间差异性,传统的抽样调查理论难以满足日益增长的空间抽样需求,合理高效的人口空间抽样调查方法对于人口统计、研究人类活动、解决城市问题等有重要意义。本文提出一种基于多源信息与深度学习特征提取的人口空间抽样方法。在不透水面信息的辅助下,利用四叉树分割进行分层抽样,初步选择出可能存在人口分布的调查样本,并通过深度学习的常用模型——卷积神经网络估算样本建筑物密度,以辅助最终调查样本的选择与调查方案的制定。研究结果证明,该方法能够有效地筛选与人口分布密切相关的抽样区域,排除大量的无用样本,提高了人口调查的效率,节约了大量调查成本。     

改进分形海面模型散射信号的分形特性分析

针对分形海面模型的功率谱在空间波数小于基波波数时不能满足正幂率的问题,提出一种统计模型和归一化带限Weierstrass分形模型相结合的1维海面模型,确定了表面功率谱的闭式解,表面功率谱和有关文献的数据进行了对比。在满足Kirchhoff近似的条件下推导该模型电磁散射系数的闭式解,计算了散射系数随时间变化的Hurst指数,进而求得其分形维数。从数值仿真结果可知,表面功率谱和PM谱、南海的实测数据都拟合得很好,验证了模型的有效性,海面所接收信号随时间变化是分形的,并且其分形维数与分形海表面的分形维数几乎相等。     

Modelling changing population distributions: an example of the Kenyan Coast, 1979–2009

ABSTRACT

Large-scale gridded population datasets are usually produced for the year of input census data using a top-down approach and projected backward and forward in time using national growth rates. Such temporal projections do not include any subnational variation in population distribution trends and ignore changes in geographical covariates such as urban land cover changes. Improved predictions of population distribution changes over time require the use of a limited number of covariates that are time-invariant or temporally explicit. Here we make use of recently released multi-temporal high-resolution global settlement layers, historical census data and latest developments in population distribution modelling methods to reconstruct population distribution changes over 30 years across the Kenyan Coast. We explore the methodological challenges associated with the production of gridded population distribution time-series in data-scarce countries and show that trade-offs have to be found between spatial and temporal resolutions when selecting the best modelling approach. Strategies used to fill data gaps may vary according to the local context and the objective of the study. This work will hopefully serve as a benchmark for future developments of population distribution time-series that are increasingly required for population-at-risk estimations and spatial modelling in various fields.     

基于缓冲区分析的城市化与地表水质关系研究——以烟台沿海区县为例

将城市化过程中的人为土地定义为建设用地,利用2004年TM影像得到烟台沿海区县建设用地数据。用缓冲区分析提取乡镇水平上建设用地比率和人口密度数据,缓冲半径从100m到2000m,利用ArcView空间分析功能对建设用地比率、人口密度、河网等级和水质进行叠置分析,并结合逐步回归分析方法揭示烟台沿海区县28个水质监测站各水质参量的空间变化情况。结果显示,通过建设用地比率和人口密度共同作用可以解释85%以上的水质参量模型,反映城市化的建设用地比率比人口密度能更好地解释水质参量的空间变化,大多数水质参量的最佳模型出现在2000m的缓冲半径上,表明建设用地比率和人口密度是影响研究区域水质的首要因素。同时,运用缓冲区分析等GIS空间分析方法为区域城市化进程与水环境质量的研究提供了新的途径。     

经济空间场与ESDA结合的公共卫生事件应急策略制定

新型冠状病毒肺炎疫情引起了人们对国家公共卫生事件应对能力的广泛关注。基于波及效应梯度场提出了生产诱发梯度,进一步完善了经济空间场理论,并将其与探索性空间数据分析(exploratory spatial data analysis,ESDA)相结合,对医药制造业波及效应及空间布局进行了研究,制定了有效的公共卫生事件应急策略。经济空间场理论分析结果揭示了产业经济空间中医药制造业与各产业部门之间的波及效应,并由此得到了医药密切相关产业。同时,经济空间场理论与ESDA方法的结合能在区分中国大陆各省空间聚集类型的基础上,评估各省公共卫生事件的应对能力,从而为各省提出相应的应急策略和医药制造业发展建议。该方法综合考虑了产业波及效应和产业空间布局现状,不仅能够促进各省医药制造业的健康合理发展,也有助于增强各省突发公共卫生事件的应对能力。     

Using GIS to improve public health emergency response in rural areas during the COVID-19 crisis: A case study of South Carolina,US

Geographic information systems (GIS) have become essential tools in the public health domain, especially when it comes to monitoring and surveillance of disease. The purpose of this article is to describe and explore the benefits of using GIS to improve public health emergency response during a global pandemic and, in particular, how to effectively optimize the allocation of public health resources in a rural setting using a data-driven approach that considers the multifactorial demand for new COVID-19 testing sites. Herein, the authors present their interprofessional project as an example of such efforts to inform applications for practice. The team developed a GIS-based multicriteria decision analysis model for use by decision-makers and public health experts in similar future planning and response scenarios. Focus is placed on rural characteristics (e.g., accessibility), vulnerable populations, and daily changing conditions (e.g., COVID-19 daily case fluctuations) that create additional challenges for public health agencies and policymakers.     

人口总量及其空间分布特征与经济发展关系的动力学研究

建立了人口—经济系统的微分方程组模型,并在方程中引入人口空间分布与经济发展协调的因子η,通过分析模型的稳定性特征得出以下结论:人口经济系统是复杂的非线性关系;人口的过于快速增长会使经济总量趋向于零;如果η>1并且较高,则人口经济系统发展稳定时,经济总量会高些,也即人口数量稳定在同样水平时,会因为空间分布的不同而有不同的经济产出。说明在控制人口数量的同时必须重视人口空间分布的问题。     

Spatial modelling of sprinkler irrigation suitability in a Central Brazilian Cerrado region

Sprinkler irrigation, an agricultural production system that is causing increasing conflict among water resource users, is expanding quickly in the Central Western Cerrado regions of Brazil. To subsidize watershed management and concession of water rights, GIS-based spatial modelling was applied to spatially predict relative likelihood of the installation of centre sprinkler irrigation systems. Interpretation of multitemporal Landsat Thematic Mapper and Enhanced Thematic Mapper imagery was conducted to map spatial distribution of centre-pivot sprinkler systems. Multi-source data layers on environmental conditions and infrastructure were elaborated to test their predictive power in an Ecological Niche Factor Analysis, a spatial modelling technique for presence-only data. Underpinned by an exploratory analysis of spatial autocorrelation of irrigation systems, suitability predictions were found to be accurate on landscape scale and improved when the model includes underlying ecogeographical factors (EGV) such as farming suitability, soil groupings and distance to the hydrographic network and a density layer of existing irrigations.     

面向重大公共卫生事件的位置服务技术——以COVID-19疫情为例

2020年初暴发的新型冠状病毒肺炎(coronavirus disease 2019,COVID-19)疫情给全球人民生命安全和经济发展带来了严重影响。位置服务以庞大的地理空间信息数据库为依托,能向服务对象提供与地理信息相关的便捷、实时、精准的综合性服务,可很好地运用于紧急救灾、大流量人员追踪、复杂环境下的现场人员管控等事件中。事实证明,位置服务的优势特性在2020年春中国COVID-19疫情防控中起到了非常重要的作用。从北斗车联网平台、基于泛在定位的基础服务、时空大数据分析与疫情防控、智能导航机器人参与抗疫等多个方面阐述了中国COVID-19疫情下的位置服务应用。通过对这些应用及技术手段的分析总结,深化位置服务技术的内涵,可以为今后重大公共卫生事件的应急处置提供解决方案。