Geospatial web data tessellation and visualization

Abstract

The Internet has penetrated to every aspect of our daily life. Users are feeding their georeferenced knowledge, preference, consumer patterns and behaviors, likes and dislikes, and living patterns to the Web. Proper understanding of these user-provided georeferenced Web data is of great importance. This article combines Web 2.0 and Geospatial Web to retrieve and map user-driven data, and mixes clustering and segmentation to identify informative cluster weighted areas of influence. Case studies are provided to illustrate the working principle of proposed framework, to show how the framework can be applied to many different scenarios, and to demonstrate the usefulness and applicability of the proposed framework.