Geo-data visualization on online and offline mode of mobile web using HTML5

Abstract

Mobile devices including popular smartphone contributes to efficiency improvement of on-site data processing. Mobile environment for real-time data processing needs some additional aspects besides desktop ones, as the style of mobile app, mobile web and mobile web app. Generally, mobile app provides internal storage service so that offline data processing is possible. But mobile app needs separate development according to different types of devices or operating systems, even to different sizes of display panel of mobile devices. Geo-based data are composed of vector and raster formats from complex structure, compared to other data sets including image data and multimedia data. Hence, even though mobile applications development for geo-based data is more complicated than other ones, users' demands with respect to geo-based data processing functionalities on mobile environment are increasing in these days. Mobile web supported by technical basis of HyperText Markup Language5 (HTML5) is regarded as useful service type combining geo-based data processing modules and mobile environments, because it does not require user' downloading or installation of programs and just needs web browsers. Indexed DB Application Programming Interface (API) within this international web standard provides offline data storage functions on mobile environment. Using this API, data sets can be permanently stored into mobile devices, not cache memory. Among numerous geo-data functionalities, visualization topic is basically and commonly used in most mobile services. This study presents an implementation case of mobile web app with geo-based data visualization processing on online and offline mode. Types of geo-based data sets are base map of Open Street Map (OSM), OSM vector layers with Extensible Markup Language (XML) contents and high resolution satellite images of optical sensor. It is thought that the result of this implementation can play a role to create intelligent mobile application fields using both geo-based data sets and earth observation satellite image sets.