Spatial decisions and processes are fundamental to the understanding of spatial structure. In the earlier stages of spatial analysis proposed explanations were typically on the aggregate, phenomenological level. Now a new field has evolved and matured which calls for a deeper understanding of spatial structure with a particular emphasis on spatial decisions and processes. The present volume serves as a guide and as an anthology by discussing a wide variety of new modelling approaches, techniques and issues related to spatial decision and processes and drawing these seemingly disparate, but interlocking parts together.

This volume collects the papers presented at the European Conference on Spatial Information Theory (COSIT '93) held on the island of Elba, Italy, inSeptember 1993. Spatial information theory includes disciplinary topics and interdisciplinary issues dealing with the conceptualization and formalization of large-scale (geographic) space. It contributes towards a consistent theoretical basis for Geographic Information Systems (GIS). Geographic information systems are widely used in administration,planning, and science in many different countries, and for a wide variety ofapplications. Research results which relevant for GIS are distributed between many disciplines and contacts between researchers have been limited. At the same time, the development of GIS has been hinderedby the lack of a sound theoretical base. This conference was intended to help remedies these problems.

This volume is an attempt to provide a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, with special emphasis placed on fundamental classes of models and algorithms as well as on their applications, e.g. in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R which are widely used in the mathematical community. It can be seen as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods.

Previous research in the field of geography has generally supported the contention that much of the information that man receives from and about his external environment is filtered through, and distorted in, the very mind that receives the data. For the observer, this filtered information comes to constitute the objective world. Behavioral geography has concentrated on examining this complex phenomenon, seeking to isolate and to understand the influence of those components of external reality that pass these filters, and how they have been altered in the very act of being perceived and assimilated. The argument is made that if scientists can come to understand how and why human minds process information they have received from the outside, and can identify what is transmuted and used, it then becomes possible not only to explain the basis on which individual choices are made by those inhabiting cognized environments, but also to shape the environments themselves so as to influence behavior within them.

This book provides an overview of research in the field of spatial data quality, which looks at understanding, measuring, describing, and communicating information about the imperfections of geographic data used by GIS and other mapping software. It presents results from a number of research projects in this area, from the assessment of data accuracy to legal aspects relating to the quality of geographic information. The international contributors focus on the relationship between the quality of geographic data and the quality of decisions based on such data.

Spatial econometrics deals with spatial dependence and spatial heterogeneity, critical aspects of the data used by regional scientists. These characteristics may cause standard econometric techniques to become inappropriate. In this book, I combine several recent research results to construct a comprehensive approach to the incorporation of spatial effects in econometrics. My primary focus is to demonstrate how these spatial effects can be considered as special cases of general frameworks in standard econometrics, and to outline how they necessitate a separate set of methods and techniques, encompassed within the field of spatial econometrics. My viewpoint differs from that taken in the discussion of spatial autocorrelation in spatial statistics - e.g., most recently by Cliff and Ord (1981) and Upton and Fingleton (1985) - in that I am mostly concerned with the relevance of spatial effects on model specification, estimation and other inference, in what I caIl a model-driven approach, as opposed to a data-driven approach in spatial statistics. I attempt to combine a rigorous econometric perspective with a comprehensive treatment of methodological issues in spatial analysis.