Marek Lukáš, Tuček Pavel, Pászto Vít
Department of Geoinformatics, Faculty of Science, Palacky University in Olomouc, 17.listopadu 50, 77146, Olomouc, Czech Republic.
Int J Health Geogr. 2015 Jan 28;14:7. doi: 10.1186/1476-072X-14-7.
Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution.
We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics.
Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk.
We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.
可视化分析旨在通过复杂的视觉交互,将信息技术的处理能力与用户的逻辑思维和推理能力联系起来。此外,大多数数据都包含空间成分。因此,对地理可视化工具和方法的需求应运而生。人们既可以开发自己的系统,但研究结果的传播及其可用性可能会存在问题,也可以使用广泛且知名的平台。本文的目的是证明谷歌地球™软件作为一种地理可视化分析工具的适用性,该工具有助于理解疾病分布的时空模式。
我们将复杂的联合时空分析与综合可视化相结合。我们分析了2008年至2012年期间捷克共和国弯曲杆菌病的时空分布。我们在研究中应用了三种主要方法:(1)以气泡图形式可视化的监测数据的地理可视化分析;(2)通过时空克里金法计算的疾病每周发病率曲面的地理可视化分析;(3)为识别受影响市镇的高发病率或低发病率集群而采用的时空扫描统计。最终数据存储在键孔标记语言文件中,并在谷歌地球™中进行可视化,以便应用地理可视化分析。
通过地理可视化分析,我们能够有效地从复杂数据集中显示和检索信息。我们没有在一系列静态地图中寻找模式或使用数值统计,而是创建了一组交互式可视化,以便向更广泛的受众探索和传达分析结果。地理可视化分析的结果确定了疾病行为中的周期性模式以及14个相对风险增加的时空集群。
我们证明谷歌地球™软件是疾病分布地理可视化分析的可用工具。谷歌地球™有许多无可争议的优点(广泛使用、免费可用、界面直观、时空可视化能力和动画、结果交流),然而,仍需要将其与预处理工具相结合,将数据处理成适合地理可视化分析本身的形式。