Exploring spatial data through computational intelligence: a joint perspective

Abstract

The dramatic increase in geospatial data occasioned by developments in digital mapping, remote sensing, IT, and widespread generalization of Geographic Information Systems (GIS), emphasises the importance of exploring new approaches to spatial analysis and modelling. This favours the creation of new knowledge and eventually helps the process of scientific discovery. In this context the special nature of spatial data is particularly relevant and should be taken into account (e.g. observations are not independent and data uncertainty and errors are often spatially structured). The tolerance of imprecision and uncertainty makes soft computing a potentially very useful tool in the GIS environment. Computational Intelligence (or Soft computing) fits particularly well with GIS applications in those cases where computationally hard problems cannot be solved by classical algorithmic approaches.