Spatial Autocorrelation and Spatial Filtering: Gaining Understanding Through Theory and Scientific Visualization (Advances in Spatial Science)

Scientific visualization may be defined as the transformation of numerical scientific data into informative graphical displays. The text introduces a nonverbal model to subdisciplines that until now has mostly employed mathematical or verbal-conceptual models. The focus is on how scientific visualization can help revolutionize the manner in which the tendencies for (dis)similar numerical values to cluster together in location on a map are explored and analyzed. In doing so, the concept known as spatial autocorrelation - which characterizes these tendencies - is further de-mystified.

Advances in Spatial Science

This series of books is dedicated to reporting on recent advances in spatial science. It contains scientific studies focusing on spatial phenomena, utilising theoretical frameworks, analytical methods, and empirical procedures specifically designed for spatial analysis. The series brings together innovative spatial research utilising concepts, perspectives, and methods with a relevance to both basic science and policy making. The aim is to present advances in spatial science to an informed readership in universities, research organisations, and policy-making institutions throughout the world.

The type of material considered for publication in the series includes:

- Monographs of theoretical and applied research in spatial science;

- State-of-the-art volumes in areas of basic research;

- Reports of innovative theories and methods in spatial science;

- Tightly edited reports form specially organised research seminars.

Manuscripts must be prepared in accordance with the guidelines for authors and editors that may be obtained from Springer-Verlag. Manuscripts considered for the series will be reviewed by independent experts to ensure their originality, scientific level, and international policy relevance.