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 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.

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.

Point process statistics is successfully used in fields such as material science, human epidemiology, social sciences, animal epidemiology, biology, and seismology. Its further application depends greatly on good software and instructive case studies that show the way to successful work. This book satisfies this need by a presentation of the spatstat package and many statistical examples. Researchers, spatial statisticians and scientists from biology, geosciences, materials sciences and other fields will use this book as a helpful guide to the application of point process statistics. No other book presents so many well-founded point process case studies. From the reviews: "For those interested in analyzing their spatial data, the wide variatey of examples and approaches here give a good idea of the possibilities and suggest reasonable paths to explore." Michael Sherman for the Journal of the American Statistical Association, December 2006

Stochastic Geometry is the mathematical discipline which studies mathematical models for random geometric structures. This book collects lectures presented at the CIME summer school in Martina Franca in September 2004. The main lecturers covered Spatial Statistics, Random Points, Integral Geometry and Random Sets. These are complemented by two additional contributions on Random Mosaics and Crystallization Processes. The book presents a comprehensive and up-to-date description of important aspects of Stochastic Geometry.

The metaphor of a "cognitive map" has attracted interest since the 1940s. Researchers from many fields have explored how humans process and use spatial information, why they make errors or not. This text brings together contributors from diverse fields to explore the

Thi s book ari ses from The Fourth European Coll oqui urn on Theoret i ca 1 and Quant itat i ve Geography wh i ch was he 1 din Ve 1 dhoven, The Netherlands in September 1985. It contains a series of papers on spatial choice dynamics and dynamical spatial systems which were presented at the colloquium, together with a few other soll icited ones. The book is intended primarily as a state-of-the art review of mainly European research on these two fastly growing problem areas. As a consequence of this decision, the book contains a selection of papers that differs in terms of focus, level of sophistication and conceptual background. Evidently, the dissimination of ideas and computer software is a time-related phenomenon, which in the European context is amplified by differences in language, the profile of geography and the formal training of geographers. The book reflects such differences. It would have been impossible to produce this book without the support of the various European study groups on theoretical and quantitative geography. Without their help the meetings from which this volumes originates would not have been held in the first place. We are also indebted to the Royal Dutch Academy of Science for partly funding the colloquium, and to SISWO and TNOjPSC for providing general support in the organisation of the conference.

Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. - Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography - Provides an overview, methods and case studies for each application - Expresses concepts and methods at an appropriate level for both students and new users to learn by example

Transportation engineering and transportation planning are two sides of the same coin aiming at the design of an efficient infrastructure and service to meet the growing needs for accessibility and mobility. Many well-designed transport systems that meet these needs are based on a solid understanding of human behavior. Since transportation systems