Measurements from dynamic environmental phenomena have resulted in the acquisition and generation of an enormous amount of data. This upsurge in data availability can be attributed to the interdisciplinary nature of environmental problem solving and the wide range of acquisition technology involved. In essence, users are dealing with data that is complex in nature, multidimensional and probably of a temporal nature. Also, the frequency by which this data is acquired far exceeds the rate at which it is being explored, a factor that has accelerated the search for innovative approaches and tools in spatial data analysis. These attempts have seen both analytical and visual techniques being used as aids in presentation and scientific data exploration. Examples are seen in techniques as in: data mining, data exploration and visualization.