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1.
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。 相似文献
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A feasibility study in progress to integrate health and air quality information is presented. The methods of using integrated GIS and air quality dispersion modelling tools to assess the effect of the environment on health are discussed. The main aim is to model human personal exposure to air pollutants and compare the predictions to respiratory health data for asthmatics in a health telematics project. The MEDICATE project develops and tests the feasibility of using a health telematic system for asthmatics. Key to this is the determination of the real-time health (lung function) response to the ambient environment. For this, air quality information is related to respiratory measurements by modelling personal exposure through a GIS. The methods of integrating environmental modelling and assessment tools (GIS) in this case are examined. ESRI's ArcView is used to locate and compile environmental information about the patients' locations and lifestyles in the study areas (London and Barcelona). A dispersion modelling extension to ArcView, ADMS Urban, is used to interrogate the spatial environmental databases (e.g. emission inventories) to model air pollution concentrations. Patients' personal exposure is modelled by time-weighted estimates of their exposure to ambient air quality at each defined location. Lung function data can be compared on a time-wise basis with these air quality indicators to see if there is a relationship on an hourly, daily or lagged-day basis. The aim of this paper is to propose a methodology and discuss the integration and practicalities of using air quality assessment tools (inventories, dispersion modelling and a GIS) in assessing the impacts of the environment on human health. 相似文献
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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。 相似文献
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Population data used in GIS analyses is generally assumed to be homogeneous and planar (i.e. census tracts, townships or prefectures) due to the public unavailability of building population data. However, information on building population is required for micro-spatial analysis for improved disaster management and emergency preparedness, public facility management for urban planning, consumer and retail market analysis, environment and public health programs and other demographic studies. This article discusses a GIS approach using the Areametric and Volumetric methods for estimating building population based on census tracts and building footprint datasets. The estimated results were evaluated using actual building population data by visual, statistical and spatial means, and validated for use in micro-spatial analysis. We have also implemented a standalone GIS tool (known as 'PopShape GIS') for generating new building footprint with population attribute information based on user-defined criteria. 相似文献
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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。 相似文献
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新型冠状病毒肺炎（COVID-19）疫情的出现和暴发流行，给社会、经济及人群健康提出巨大的挑战，已经成为重大公共卫生事件和社会问题。作为一种新发传染病，提早发现、迅速采用有效应对举措，是防止病毒蔓延扩散的重要环节。地理信息系统（GIS）在传染病的控制、预防、预警中有举足轻重的地位，移动GIS（Mobile GIS）作为GIS技术的发展，进一步提高了我国卫生部门应对突发传染病的能力。本文以COVID-19防控为例，重点介绍了移动GIS技术在传染病防控中的应用。 相似文献
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基于GIS的农村公共卫生管理信息系统框架设计 总被引：1，自引：0，他引：1
在信息化高度发展的今天,对传统的公共卫生数据传输机制和管理方式进行信息化改革,成为当前农村地区公共卫生建设的当务之急。本文通过调查分析,设计了基于GIS的农村公共卫生管理信息系统的总体结构框架和网络结构框架,将系统人员分成不同的层次,系统功能分设不同的模块,从而有效地进行管理,同时以虚拟专网与上级机构进行通讯,以普通Internet网与农村基层机构建立联系,从而构建有效的传输网络,使公共卫生信息畅通无阻。 相似文献
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Representing Datum-level Uncertainty in Historical GIS 总被引：1，自引：0，他引：1
《制图学和地理信息科学》2013,40(4):319-334
Geographic information systems have great potential as a tool for studying and teaching historical geography. However, using traditional GIS data models, even spatio-temporal forms, has been difficult due to the prevalence of uncertainty—both ambiguity and fuzziness—in source information concerning space, time, and theme. Explicitly uncertain assertions of a geo-historical datum can be modeled as an Evidentiary Set, a hybrid of a fuzzy set with probability and Dempster-Shafer evidence theory. This set formalism is designed to represent continuous and discrete value ambiguity (e.g., "about 10"), and fuzzy membership (e.g., "somewhat Central European"), including ambiguous membership and other fuzzy-ambiguous combinations. The formal set structure can be stored in GIS by representing continuous variation with a patch model, producing logical models for object-oriented and relational GIS databases. The relational implementation was tested in two GIS databases focused on human historical geography, showing the potential for the model to represent datum-level uncertainty in a wide variety of GIS applications. 相似文献
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The COVID-19(coronavirus)disease has affected over 100 countries in a matter of weeks.The way humans live and work on planet Earth has changed profoundly over the last months.Many lives and livelihoods have been lost.Ways of working,shopping,and social interactions are all vastly different for most of us.We do not know when the current crisis will end,or how far we will"return"to the way things were before the pandemic.The world is experiencing one of the most transformative moments of the last 100 years.The social,economic,and political influences of the COVID-19 crisis have already been hugely momentous,we do not utterly understand it.Looking ahead,we have inevitably had to make important public health,economic,governance,and ecological decisions with less information than usual and to reverse recently adopted policies,which can lead to an era of disruptive transformations to sustainability.During these historic times,we must understand the hidden reality of the earth system and attempt to transform our needs so that we all have a sustained future on our planet. 相似文献
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As an important GIS function, spatial interpolation is one of the most often used geographic techniques for spatial query, spatial data visualization, and spatial decision-making processes in GIS and environmental science. However, less attention has been paid on the comparisons of available spatial interpolation methods, although a number of GIS models including inverse distance weighting, spline, radial basis functions, and the typical geostatistical models (i.e. ordinary kriging, universal kriging, and cokriging) are already incorporated in GIS software packages. In this research, the conceptual and methodological aspects of regression kriging and GIS built-in interpolation models and their interpolation performance are compared and evaluated. Regression kriging is the combination of multivariate regression and kriging. It takes into consideration the spatial autocorrelation of the variable of interest, the correlation between the variable of interest and auxiliary variables (e.g., remotely sensed images are often relatively easy to obtain as auxiliary variables), and the unbiased spatial estimation with minimized variance. To assess the efficiency of regression kriging and the difference between stochastic and deterministic interpolation methods, three case studies with strong, medium, and weak correlation between the response and auxiliary variables are compared to assess interpolation performances. Results indicate that regression kriging has the potential to significantly improve spatial prediction accuracy even when using a weakly correlated auxiliary variable. 相似文献
11.
Stacy Supak Huan Luo Laura Tateosian Kunsheng Fang Julia Harrell Cris Harrelson Andrew D. Bailey Hugh Devine 《Transactions in GIS》2012,16(2):89-104
By responding to potentially life‐threatening emergencies such as foodborne illnesses and water contamination, U.S. public health agencies play a vital role in promoting human health and protecting the environment. Local, state, and federal partners must collaborate to strategically plan initiatives, allocate resources, and evaluate emergency response activities. These collaborative decision‐making processes can be improved by using web‐based mapping applications for visualization and analysis. We developed a web‐based GIS framework which is applied to public health data for North Carolina's (NC) Department of Health and Human Services. The application visualizes all state‐regulated food service facilities and supports query and analysis tools crucial for food recalls or radiation contamination tracking. Built with PostgreSQL/PostGIS, GeoServer, and a customized GeoExplorer map viewer, the framework delivers a web‐based mapping tool that is flexible and Open Source. The flexibility of the framework is an important dimension of its scalability, allowing it to be customizable, modular, and portable so that it is easily configurable to support additional research and education initiatives. This approach reverses a trend toward application‐specific web mapping development in Open Source GIS. To demonstrate flexibility, we configured an additional website for forest landowner management to be used by another state agency, the NC Forest Service. 相似文献
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Manfred Ehlers Monika Ghler Ronald Janowsky 《ISPRS Journal of Photogrammetry and Remote Sensing》2003,57(5-6):315
The advent of very high-resolution satellite programs and digital airborne cameras with ultra high resolution offers new possibilities for very accurate mapping of the environment. With these sensors of improved spatial resolution, however, the user community faces a new problem in the analysis of this type of image data. Standard classification techniques have to be augmented with appropriate analysis procedures because the required homogeneity of landuse/landcover classes can no longer be achieved by the integration effect of large pixel sizes (e.g., 20–80 m). New intelligent techniques will have to be developed that make use of multisensor approaches, geographic information system (GIS) integration and context-based interpretation schemes.The ideal goal should be that GIS ‘intelligence’ (e.g., object and analysis models) should be used to automate the classification process. In return, GIS objects can be extracted from a remote sensing image to update the GIS database. This paper presents the development of an automated procedure for biotope type mapping from ultra high-resolution airborne scanner data (HRSC-A). The hierarchical procedure incorporates a priori GIS information, a digital surface model (DSM) and multispectral image data. The results of this study will serve as a basis for a continuous environmental monitoring process in the tidally influenced region of the Elbe River, Germany. 相似文献
14.
Mohammad Z. Al-Hamdan William L. Crosson Sigrid A. Economou Maurice G. Estes Jr Sue M. Estes Sarah N. Hemmings 《国际地球制图》2014,29(1):85-98
We describe a remote sensing and geographic information system (GIS)-based study that has three objectives: (1) characterize fine particulate matter (PM2.5), insolation and land surface temperature (LST) using NASA satellite observations, Environmental Protection Agency (EPA) ground-level monitor data and North American Land Data Assimilation System (NLDAS) data products on a national scale; (2) link these data with public health data from the REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether these environmental risk factors are related to cognitive decline, stroke and other health outcomes and (3) disseminate the environmental datasets and public health linkage analyses to end users for decision-making through the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This study directly addresses a public health focus of the NASA Applied Sciences Program, utilization of Earth Sciences products, by addressing issues of environmental health to enhance public health decision-making. 相似文献
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Shawky MANSOUR 《地球空间信息科学学报》2016,19(1):26-38
Much attention has been given to address public health policy in Saudi Arabia, particularly for the management, quality, and coverage issues. However, assessment of spatial patterns, distribution, and provision of public health services has been neglected. This paper analyzes the availability and accessibility of public health facilities across Riyadh Governorate, Saudi Arabia at the subnational level. Spatial and attribute data of public health facilities potentially have been analyzed using GIS to produce accurate measure of accessibility. The spatial pattern of service distribution was examined using average nearest neighbor. Distances from demand points (populations) to providers (facilities) were calculated for each district using near analysis. In addition, the ratios of public health facility to population were calculated to identify underserved and overserved areas. The findings clearly indicate that the spatial pattern of the distribution of public health facilities was significantly clustered (p value < 0.001) with Z-score of ?10.9. Several districts within the central parts of the governorate were identified as having a higher density of facilities, while most of districts that are located in the marginal parts exhibit very low density of health facilities. Overall, there was a considerable variation in the average distance from district centroids to health facilities. Substantially, less than half of the population (45.4%) living in 61 districts has access to public health facility within less than 1-km distance. In contrast, the greatest increase in distances was observed for 6% of population living in 38 districts. People that live in such districts need to travel long distances for public health care. The output of this analysis can assist policy-makers and authorities of Riyadh Governorate in planning public health delivery. 相似文献
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Thi Hong Diep Dao Craig Ravesloot Lillie Greiman Tannis Hargrove 《Transactions in GIS》2019,23(3):515-537
The geographical explicit ecological momentary assessment (GEMA) data collection platform provides extremely rich geospatial datasets and is very promising to gain behavior insights linking mobility, activities, and health. However, the task of analyzing these large datasets effectively is not straightforward, because they often involve a large multivariable dimension and rich qualitative data formats. Responding to the call for innovative analytic approaches in GIScience, this article advocates the use of spatial association rule mining (SARM) to extract frequent associations among daily activities, daily mobility, and health, including both physical health (e.g. pain) and mental health (e.g. happiness). This inductive mining approach works robustly with large datasets and is suitable for both qualitative and quantitative studies. A novel visualization technique to analyze the mined rules is also developed and presented. 相似文献
17.
Xuke Hu Hongchao Fan Alexey Noskov Zhiyong Wang Alexander Zipf Fuqiang Gu Jianga Shang 《Transactions in GIS》2021,25(1):71-111
Semantically rich maps are the foundation of indoor location‐based services. Many map providers such as OpenStreetMap and automatic mapping solutions focus on the representation and detection of geometric information (e.g., shape of room) and a few semantics (e.g., stairs and furniture) but neglect room usage. To mitigate the issue, this work proposes a general room tagging method for public buildings, which can benefit both existing map providers and automatic mapping solutions by inferring the missing room usage based on indoor geometric maps. Two kinds of statistical learning‐based room tagging methods are adopted: traditional machine learning (e.g., random forests) and deep learning, specifically relational graph convolutional networks (R‐GCNs), based on the geometric properties (e.g., area), topological relationships (e.g., adjacency and inclusion), and spatial distribution characteristics of rooms. In the machine learning‐based approach, a bidirectional beam search strategy is proposed to deal with the issue that the tag of a room depends on the tag of its neighbors in an undirected room sequence. In the R‐GCN‐based approach, useful properties of neighboring nodes (rooms) in the graph are automatically gathered to classify the nodes. Research buildings are taken as examples to evaluate the proposed approaches based on 130 floor plans with 3,330 rooms by using fivefold cross‐validation. The experiments conducted show that the random forest‐based approach achieves a higher tagging accuracy (0.85) than R‐GCN (0.79). 相似文献
18.
《ISPRS Journal of Photogrammetry and Remote Sensing》1999,54(4):234-243
A geologic map is typically a 2D representation of 3D subsurface structures in a given area. It is based on the currently accepted geologists' model explaining the observed phenomena and the processes that shaped them in the geologic past. For historical reasons, this model is recorded in a geologic map with an explanatory booklet that describes the authors' conclusions as well as relevant field observations and other data such as tectonic measurements, drill hole logs or fossil records. Today, however, this variety of information can be better handled by converting it into digital and even hypermedial format. This necessitates the prior conception, development and implementation of a suitable geologic “hypermap model”. The main objective of this study is to design models and tools well-suited for the interaction between users and geologic hypermaps. The unique aspect of this family of applications is that users, in general, are both end-users (e.g., engineers) and designers (e.g., mapmakers). Objectives, concepts and methods for developing a human interface to geologic hypermaps have been tested using a prototype (i.e., GeoHyp) within the GIS environment of ArcView from ESRI. Tools to access the underlying background database via hyperlinks have been implemented, as well as functions especially developed to meet specific geologic requirements. Tests with various types of users have shown that the prototype matches their expectations and serves as a good basis for further development. In this article, we report on our design choices for GeoHyp and the current status of our project. 相似文献
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GIS与Voronoi多边形在医疗服务设施地理可达性分析中的应用 总被引：5，自引：0，他引：5
王远飞 《测绘与空间地理信息》2006,29(3):77-80
地理可达性是研究评价各种服务设施布局及其服务域的重要指标之一,空间距离、交通便捷性、出行成本等是可达性测度的重要因子。由于医疗设施等公共设施通常以服务的公平性和覆盖性为目标,因此可定义居民点到最邻近医院的距离为地理可达性的测度。在此基础上,作者提出了基于GIS与Voronoi多边形的地理可达性计算方法。这一方法不仅将地理可达性分析中的空间点对之间的距离计算简化为空间查询,方便了GIS应用,而且计算的Voronoi多边形在本质上就是最邻近意义上医院的服务域,即服务域内各居民点到该医院的距离就是最邻近距离。此外结合人口分布等属性数据,还可深入分析各医院的服务承载力,本方法为医疗设施等公共服务设施的规划决策提供了重要的工具。 相似文献