Wireless sensor networks are deployed to monitor dynamic geographic phenomena, or objects, over space and time. This paper presents a new spatiotemporal data model for dynamic area...
We designed and implemented a simple and fast heuristic for placing multiple labels along edges of a planar network. As a testbed, realworld data from Google Transit is taken: our ...
The categorization of our environment into feature types is an essential prerequisite for cartography, geographic information retrieval, routing applications, spatial decision supp...
Over the past decade, automated systems dedicated to geopositioning have been the object of considerable development. Despite the success of these systems for many applications, th...
Jean-Marie Le Yaouanc, Eric Saux, Christophe Clara...
Abstract. Eye movement recordings produce large quantities of spatiotemporal data, and are more and more frequently used as an aid to gain further insight into human thinking in us...
As an alternative to expensive road surveys, we are working toward a method to infer the road network from GPS data logged from regular vehicles. One of the most important componen...
Behavioral experiments addressing the conceptualization of geographic events are few and far between. Our research seeks to address this deficiency by developing an experimental fr...
Alexander Klippel, Rui Li, Frank Hardisty, Chris W...
Researchers from the cognitive and spatial sciences are studying text descriptions of movement patterns in order to examine how humans communicate and understand spatial informatio...
Xiao Zhang, Prasenjit Mitra, Alexander Klippel, Al...
Semantic similarity measurement is a key methodology in various domains ranging from cognitive science to geographic information retrieval on the Web. Meaningful notions of similar...
Using wireless geosensor networks (WGSN), sensor nodes often monitor a phenomenon that is both continuous in time and space. However, sensor nodes take discrete samples, and an ana...