Spatial filters have been used as an easy and intuitive way to create smoothed disease maps. Birth weight data from New York State for 1994 and 1995 are used to compare the traditional filter type of fixed geographical size with a filter size of constant or nearly constant population size. The latter are more appropriate for mapping disease in geographic areas with widely varying population den...

Evaluation of a spatial join typically has two steps: a filter step that applies the join on approximations of spatial objects and a refinement step that determines the actual intersection of two spatial objects. In this paper, we study the effectiveness of filters with different approximations including minimum bounding rectangles, rectilinear approximations, minimum 5-corner bounding convex p...

In this paper, the authors use Spatial Interaction Filters (SIF) to simulate human experts’ visual process in tracking spatial interactive objects. The algorithm includes spatial density based pixel clustering and object interaction descriptions, such as Contact Area Index (CAI) and correlation filter. The algorithm is designed to automatically track the Harmful Algae Bloom (HAB) targets. In th...

We propose a simultaneous spatiotemporal filter optimization algorithm for the single trial ElectroEncephaloGraphy (EEG) classification problem. The algorithm is a generalization of the Common Spatial Pattern (CSP) algorithm, which incorporates non-homogeneous weighting of the crossspectrum matrices. The spectral weighting coefficients and the spatial filter are alternately updated. The validat...

We introduce a new file organization for the storage and manipulation of spatial (or multidimensional) data that is able to execute spatial join operations with great efficiency. The Filter Tree information structure is a hierarchical organization that tends to separate spatial entities by size, placing larger entities at the higher levels of the Filter Tree, and smaller entities at lower level...