Geovisualization Using HTML5 : a case study to improve animations of historical geographic data

Abstract: Popular science Visualize geographic data Using HTML5 The Scanian Economic-Demographic Database (SEDD) has been assembled by the Centre for Economic Demography (CED), Lund University. It contains demographic and economic information of Scania from the 17th century until the present. The SEDD database has been integrated with geographic data, which are digitized from four independent historical maps. To help the users well understand these data, a web mapping application called SEDD Map has been developed and tested. The previous version of SEDD Map is constructed using Silverlight plugin. It cannot run on most popular portable devices. As Hypertext Markup Languages (HTML) continue to develop, a recent version, HTML5, was published in 2012. It aims to support the latest multimedia formats and reduce the need for plugins. So, to improve the compatibility of SEDD Map, this work using HTML5 to developed a new version of SEDD Map. Before we constructed the new version of SEDD Map, a set of web mapping applications and programs were evaluated. From this evaluation and comparison, we found that SEDD Map could be improved in many area, such as improving the animation of historical geographic data. Animation is a useful tool when presenting historical data. The geographic data in SEDD Map are taken from four independent historical maps. To visualize geographic data as an animation, we need to create a time sense sequential dataset. In this study, we used linear interpolation and the four historical maps as start years and end years to simulate 159 maps to visualize the geographic data as animations. From this study, we found that: The commonly used web mapping applications for investigating demographic data contain functions, such as interactive visualization, statistical graphics, basic map tools, animations, etc; HTML5 can replace (and improve) the used of Silverlight for web mapping; Animations can be generated (filling in what is missing is to improve the data sets).