Location Intelligence: An Innovative Approach to Business Location Decision‐making

As one of the leading ‘world cities’, London is particularly reliant on sources of foreign direct investment (FDI). In the face of increasing global competition and a difficult economic climate, the capital must compete effectively to encourage and support such investors. Through a collaborative study with London's official FDI promotion agency, Think London, the need for a coherent framework for data, methodologies and tools to inform business location decision‐making became apparent. This article discusses the development of a rich environment to explore, compare and rank London's business neighbourhoods. This is achieved through the development and evaluation of a model for location‐based decision support. First, we discuss the development of a geo‐business classification for London which draws upon methods and practices common in geodemographic neighbourhood classification. A geo‐business classification is developed, encapsulating relevant location variables using Principal Components Analysis into a set of composite area profiles. Second, we discuss the implementation of an appropriate Multi‐Criteria Decision Making methodology, in this case Analytical Hierarchy Process (AHP), enabling the aggregation of the geo‐business classification and decision‐makers' preferences into discrete decision alternatives. Finally, we present the results of the integration of both data and model through the development and evaluation of a web‐based prototype.     

The stability of geodemographic cluster assignments over an intercensal period

A geodemographic classification provides a set of categorical summaries of the built and socio-economic characteristics of small geographic areas. Many classifications, including that developed in this paper, are created entirely from data extracted from a single decennial census of population. Such classifications are often criticised as becoming less useful over time because of the changing composition of small geographic areas. This paper presents a methodology for exploring the veracity of this assertion, by examining changes in UK census-based geodemographic indicators over time, as well as a substantive interpretation of the overall results. We present an innovative methodology that classifies both 2001 and 2011 census data inputs utilising a unified geography and set of attributes to create a classification that spans both census periods. Through this classification, we examine the temporal stability of the clusters and whether other secondary data sources and internal measures might usefully indicate local uncertainties in such a classification during an intercensal period.     

Participation in higher education: A geodemographic perspective on the potential for further expansion in student numbers

Higher education in England has expanded rapidly in the last ten years with the result that currently more than 30% of young people go on to university. Expansion is likely to continue following the recommendations of a national committee of inquiry (the Dearing Committee). The participation rate is known to vary substantially among social groups and between geographical areas. In this paper the participation rate is calculated using a new measure, the Young Entrants Index (YEI), and the extent of variation by region, gender and residential neighbourhood type established. The Super Profiles geodemographic system is used to facilitate the latter. This is shown to be a powerful discriminator and to offer great potential as an alternative analytical approach to the conventional social class categories, based on parental occupation, that have formed the basis of most participation studies to date. Received: 20 October 1998/Accepted: 5 May 1999     

Temporal Uncertainty in a Small Area Open Geodemographic Classification

The 2001 Output Area Classification (2001 OAC) is an open source geodemographic classification of the UK built exclusively from 2001 UK Census data. There has been considerable user interest in its applicability to subsequent time periods, particularly given the potential propensity of characteristics and attributes in some areas to change during inter‐censual periods. Users often purchase commercial geodemographic classification products in the belief that purely census‐based classifications such as the 2001 OAC are uniformly unreliable because there is no temporal updating of input data. Yet there is evidence to suggest that whilst some UK neighborhoods are prone to sudden changes, many others change very little over protracted time periods. Using measures that are available at the small area level, temporal uncertainty indicators can be constructed to identify those areas that are less stable. Using mid‐year population estimates and dwelling stock data, this article develops three temporal uncertainty indicators. These provide a reliable means of gauging the stability or otherwise of neighborhood conditions. The conclusion from this is that while a large number of small areas in the UK do experience change over time, this change is not uniform in either degree or distribution, or by geodemographic type.     

Towards Real‐Time Geodemographics: Clustering Algorithm Performance for Large Multidimensional Spatial Databases

Geodemographic classifications provide discrete indicators of the social, economic and demographic characteristics of people living within small geographic areas. They have hitherto been regarded as products, which are the final “best” outcome that can be achieved using available data and algorithms. However, reduction in computational cost, increased network bandwidths and increasingly accessible spatial data infrastructures have together created the potential for the creation of classifications in near real time within distributed online environments. Yet paramount to the creation of truly real time geodemographic classifications is the ability for software to process and efficiency cluster large multidimensional spatial databases within a timescale that is consistent with online user interaction. To this end, this article evaluates the computational efficiency of a number of clustering algorithms with a view to creating geodemographic classifications “on the fly” at a range of different geographic scales.     

Geodemographics and spatial interaction: an integrated model for higher education

Spatial interaction modelling and geodemographic analysis have each developed as quite separate research traditions. In this paper, we present an integrated model that harnesses the power of spatial interaction modelling to behavioural insights derived from a geodemographic classification. This approach is applied to the modelling of participation in higher education (HE). A novel feature of the paper is the integration of national schools, colleges and HE data; a national model is then calibrated and tested against actual recorded flows of students into HE. The model is implemented within a Java framework and is presented as a first step towards providing a quantitative tool that can be used by HE stakeholders to explore policies relating to such topics as widening access to under-represented groups.     

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.     

A multiple indicator, multiple cause method for representing social capital with an application to psychological distress

This paper describes a structural equation methodology for obtaining social capital scores for survey subjects from multiple indicators of social support, neighbourhood and trust perceptions, and memberships of organizations. It adjusts for variation that is likely to occur in levels of social capital according to geographic context (e.g. level of area deprivation, geographic region, level of urbanity) and demographic group. Social capital is used as an explanatory factor for psychological distress using data from the 2006 Health Survey for England. A highly significant effect of social capital in reducing the chance of psychiatric caseness is obtained after controlling for other individual and geographic risk factors. Allowing for social capital has considerable effects on the impacts on psychiatric health of other risk factors. In particular, the impact of area deprivation category is much reduced. There is also evidence of significant differentiation in social capital between population categories and geographic contexts.     

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 analysis of public health facilities in Riyadh Governorate,Saudi Arabia: a GIS-based study to assess geographic variations of service provision and accessibility

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.     

Improving decision-making activities for meningitis and malaria

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community’s capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.     

大型公共建筑应急疏散救援系统构建

公共建筑要求更高的安全性,应急救援系统是保障建筑安全的重要因素.本研究以GIS作为基础,构建了一个面向大型公共建筑应急的疏散救援系统.分别从系统整体框架、系统构建流程,以及主要功能方面对系统进行了介绍.开发的系统可为大型公共建筑的应急工作提供有效的信息支持和决策辅助,可为类似系统的开发提供借鉴.     

Using GIS and Dispersion Modelling Tools to Assess the Effect of the Environment on Health

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.     

Spatial and temporal variations of spatial population accessibility to public hospitals: a case study of rural–urban comparison

Quantification and assessment of nationwide population access to health-care services is a critical undertaking for improving population health and optimizing the performance of national health systems. Rural–urban unbalance of population access to health-care services is widely involved in most of the nations. This unbalance is also potentially affected by varied weather and road conditions. This study investigates the rural and urban performances of public health system by quantifying the spatiotemporal variations of accessibility and assessing the impacts of potential factors. Australian health-care system is used as a case study for the rural–urban comparison of population accessibility. A nationwide travel time-based modified kernel density two-step floating catchment area (MKD2SFCA) model is utilized to compute accessibility of travel time within 30, 60, 120, and 240 min to all public hospitals, hospitals that provide emergency care, and hospitals that provide surgery service, respectively. Results show that accessibility is varied both temporally and spatially, and the rural–urban unbalance is distinct for different types of hospitals. In Australia, from the perspective of spatial distributions of health-care resources, spatial accessibility to all public hospitals in remote and very remote areas is not lower (and may even higher) than that in major cities, but the accessibility to hospitals that provide emergency and surgery services is much higher in major cities than other areas. From the angle of temporal variation of accessibility to public hospitals, reduction of traffic speed is 1.00–3.57% due to precipitation and heavy rain, but it leads to 18–23% and 31–50% of reduction of accessibility in hot-spot and cold-spot regions, respectively, and the impact is severe in New South Wales, Queensland, and Northern Territory during wet seasons. Spatiotemporal analysis for the variations of accessibility can provide quantitative and accurate evidence for geographically local and dynamic strategies of allocation decision-making of medical resources and optimizing health-care systems both locally and nationally.     

Remote sensing-based global crop monitoring: experiences with China's CropWatch system

Monitoring the production of main agricultural crops is important to predict and prepare for disruptions in food supply and fluctuations in global crop market prices. China's global crop-monitoring system (CropWatch) uses remote sensing data combined with selected field data to determine key crop production indicators: crop acreage, yield and production, crop condition, cropping intensity, crop-planting proportion, total food availability, and the status and severity of droughts. Results are combined to analyze the balance between supply and demand for various food crops and if needed provide early warning about possible food shortages. CropWatch data processing is highly automated and the resulting products provide new kinds of inputs for food security assessments. This paper presents a comprehensive overview of CropWatch as a remote sensing-based system, describing its structure, components, and monitoring approaches. The paper also presents examples of monitoring results and discusses the strengths and limitations of the CropWatch approach, as well as a comparison with other global crop-monitoring systems.     

基于互联网地理信息公共服务平台的智慧医疗可行性研究

智慧医疗作为医疗数据化在医疗卫生的新应用广受关注。依托地理信息系统,也使我国智慧医疗化地理信息应用日趋普及。基于地理信息服务平台的智慧医疗,把广泛的医疗数据与地理信息定位相结合,是一项前景广阔的公益项目。本文将探讨基于地理信息服务平台的智慧医疗的可行性。     

城市公共卫生安全应急管理系统技术集成研究

从国内城市公共卫生安全应急管理系统的研究和应用现状出发,指出城市公共卫生安全应急管理系统建设的核心要务是集成现有的卫生信息系统、消除卫生信息孤岛、实现数据共享与交换;并提出了城市公共卫生安全应急管理系统数据采集类型和业务支持部门。在此基础上,构建了一个基于数据仓库、以GIS为应急响应支持平台、能统一管理信息、可与其他电子政务系统互连互通的城市公共卫生安全应急管理系统框架结构,并详细阐述了各业务模块的基本功能和系统实现的关键技术方法。     

基于北斗地基增强系统的位置服务关键技术研究

利用省级北斗地基增强系统资源,结合自然资源行业生产的需求,基于时空信息技术开展“虚拟格网技术”和“大规模并发用户的位置服务响应技术”等关键技术研究,研发福建省北斗地基增强系统位置服务平台,集成了系统运行维护、公共服务、成果展示和数据共享等功能,提升了公共服务的水平和能力,满足了大规模实时位置服务的需求.      

龙岗区信息采集终端管理与指挥平台系统设计和研究

结合龙岗区网格化管理的实际,通过对龙岗区网格数据管理需求的分析,探索龙岗区信息采集终端指挥与管理平台的架构。该移动业务系统的主要功能是:为龙岗区基层网格信息员和网格志愿者、社会公众等提供信息服务,建设龙岗区工作动态实时监控、高效管理的信息指挥平台,以及完成该系统与市区其他业务系统的数据对接。基于此,本文分别从技术、系统架构和系统功能等方面对龙岗区信息采集终端管理与指挥平台系统进行设计和研究。     

直管公房管理系统设计与实现

为了提供实时、准确的公房信息,使住房保障管理工作更加高质高效,本文提出了构建基于MapGIS的直管公房管理系统。本文以MapGIS开发平台为基础,根据公房数据的特征,设计并实现了该系统,重点介绍了该系统的设计方案、功能和开发实现。