Identifying specific spatial tasks through clustering and geovisual analysis

Abstract

As people's mobility has increased so too has the use of web maps and other geo-technologies for navigational purposes. Daily usage of these technologies, either embedded in smart phones or through advanced Web GIS, involves carrying out specific spatial tasks. Such spatial tasks can be of various types, context and also consider the physical environment in which the task is being performed. By capturing and analyzing users map interactions, common behavior along with interests and dislikes can be identified and used as a basis on which to study map personalization and adaptation. Completing a spatial tasks essentially corresponds to a mouse trajectory represented as a series of mouse cursor positions on a web map. The challenge is to extract meaning from this spatio-temporal dataset. With the synergy of exploratory visualization and data-mining techniques, we present a novel approach to automatically identify and validate a number of spatial tasks forming complex mouse trajectories within a given study area. The task validation justifies trajectory clustering techniques as well as assisting in attaching semantics to the visual interpretation. This research opens further avenues for studying map personalization.