Donna Peuquet

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Spatial estimations are increasingly used to estimate geocoded ambient particulate matter (PM) concentrations in epidemiologic studies because measures of daily PM concentrations are unavailable in most U.S. locations. This study was conducted to a) assess the feasibility of large-scale kriging estimations of daily residential-level ambient PM(More)
The advancement of GIS data models to allow the eŒective utilization of very large heterogeneous geographic databases requires a new approach that incorporates models of human cognition. The ultimate goal is to provide a cooperative human-computer environment for spatial analysis. We describe the pyramid framework as an example of this new approach within(More)
Correspondence: Donna J. Peuquet, Department of Geography, 302 Walker Building, The Pennsylvania State University, University Park, Pennsylvania 16802, U.S.A. Tel: 814863-0390; Fax: 814-863-7943; E-mail: Abstract In the modern computing context, the map is no longer just a final product. Maps are now being used in a fundamentally different(More)
A dendrogram that visualizes a clustering hierarchy is often integrated with a re-orderable matrix for pattern identification. The method is widely used in many research fields including biology, geography, statistics, and data mining. However, most dendrograms do not scale up well, particularly with respect to problems of graphical and cognitive(More)
While current GISystems (geographic information systems) can represent observational spatial data well, they have limited capabilities in representing some non-observational social elements and goal-driven behaviors that can be important factors in a wide range of geographic issues. Such social elements and behaviors can include laws, regulations, polices,(More)
The unprecedented large size and high dimensionality of existing geographic datasets make the complex patterns that potentially lurk in the data hard to ®nd. Clustering is one of the most important techniques for geographic knowledge discovery. However, existing clustering methods have two severe drawbacks for this purpose. First, spatial clustering methods(More)
Representations used historically within GIS assume a world that exists only in the present. Information contained within a spatial database may be added to or modified over time, but a sense of change or dynamics through time is not maintained. This limitation of current GIS capabilities has been receiving substantial attention recently, and the impetus(More)