Method and system for forecasting events and threats based on geospatial modeling

DETAILED DESCRIPTION The present invention provides a forecasting engine and method which assists in forecasting occurrences of identifiable events and/or threats based on signature and/or pattern matching.
The present invention derives signature for event-types based on a comparison of actual event data with pre-established representational surfaces.
The surfaces represent proximity measurements and analysis associated with elements of the geospatial boundary being considered.
The measurements and analysis can consider a vast array of potential variables of interest in order to provide a comprehensive, robust forecasting engine.
In one embodiment, the present invention considers past data associated with several event-types in order to arrive at an assessment.
A method of forecasting event likelihoods in accordance with one aspect of the invention involves the steps of: establishing a geospatial boundary and a grid containing a plurality of cells within said boundary; establishing at least one layer imposed upon the grid, the layer being indicative of geospatial characteristics of at least one variable of interest; identifying a proximity measurement of a cell element for each cell to the variable of interest, and for indexing said proximity measurement for each cell; receiving geospatial information related to one or more past events of at least one event type, including location information for said one or more past events; identifying and indexing a proximity measurement from the location information for each of said one or more events to the at least one variable of interest; deriving a signature pattern for said event type; and determining a level of signature match between said derived signature pattern and at least one cell of said plurality of cells through comparison with said proximity measurement.