Patterns in spatial point locations: local indicators of spatial association in a minefield with clutter
The problem of detecting a minefield in the presence of clutter can be abstracted to that of detecting a spatial pattern within a set of point locations. The point locations are superpositions of several patterns, one of which corresponds to mines. In contrast to previous articles that take a formal, model-based approach, this article proposes a statistical methodology that is distinctly exploratory. Each point location is considered separately, and its contributions to a global measure of spatial distances between locations are featured. Different patterns and unusual points can be more easily identified on the new scale. Both minefield data and simulated point patterns demonstrate the power of the method.