Geographical Models with Mathematica provides a fairly comprehensive overview of the types of models necessary for the development of new geographical knowledge, including stochastic models, models for data analysis, for geostatistics, for networks, for dynamic systems, for cellular automata and for multi-agent systems, all discussed in their theoretical context. The author then provides over 65 programs, written in the Mathematica language, that formalize these models. Case studies are provided to help the reader apply these programs to their own studies. - Provides theoretical, stochastic and dynamic system models - Covers data science, both in a spatial and spatio-temporal analysis - Presents a microstructural understanding of the mechanical behavior of granular materials

This unique book brings together a comprehensive set of papers on the background, theory, technical issues and applications of agent-based modelling (ABM) within geographical systems. This collection of papers is an invaluable reference point for the experienced agent-based modeller as well those new to the area. Specific geographical issues such as handling scale and space are dealt with as well as practical advice from leading experts about designing and creating ABMs, handling complexity, visualising and validating model outputs. With contributions from many of the world’s leading research institutions, the latest applied research (micro and macro applications) from around the globe exemplify what can be achieved in geographical context. This book is relevant to researchers, postgraduate and advanced undergraduate students, and professionals in the areas of quantitative geography, spatial analysis, spatial modelling, social simulation modelling and geographical information sciences.

Currently, spatial analysis is becoming more important than ever because enormous volumes of spatial data are available from different sources, such as GPS, Remote Sensing, and others. This book deals with spatial analysis and modelling. It provides a comprehensive discussion of spatial analysis, methods, and approaches related to human settlements and associated environment. Key contributions with empirical case studies from Iran, Philippines, Vietnam, Thailand, Nepal, and Japan that apply spatial analysis including autocorrelation, fuzzy, voronoi, cellular automata, analytic hierarchy process, artificial neural network, spatial metrics, spatial statistics, regression, and remote sensing mapping techniques are compiled comprehensively. The core value of this book is a wide variety of results with state of the art discussion including empirical case studies. It provides a milestone reference to students, researchers, planners, and other practitioners dealing the spatial problems on urban and regional issues. We are pleased to announce that this book has been presented with the 2011 publishing award from the GIS Association of Japan. We would like to congratulate the authors!

First published in 1967, this book explores the theme of geographical generalization, or model building. It is composed of eight of the chapters from the original Models in Geography, published in 1967. The first chapter broadly outlines geographical generalization and examines the nature and function of generalized statements, ranging from conceptual models to scale models, in a geographical context. The following chapter deals with model theory in a wider scientific framework and the rest of the book discusses models of physical systems and information models. The book considers model-type generalizations that are applied in the three fields of geomorphology, meteorology and climatology, and hydrology before focusing on the transference of information and ideas in geography. This text represents a robustly anti-idiographic statement of modern work in one of the major branches of geography.

The uneven geographical distribution of economic activities is a huge challenge worldwide and also for the European Union. In Krugman’s New Economic Geography economic systems have a simple spatial structure. This book shows that more sophisticated models should visualise the EU as an evolving trade network with a specific topology and different aggregation levels. At the highest level, economic geography models give a bird eye’s view of spatial dynamics. At a medium level, institutions shape the economy and the structure of (financial and labour) markets. At the lowest level, individual decisions interact with the economic, social and institutional environment; the focus is on firms’ decision on location and innovation. Such multilevel models exhibit complex dynamic patterns – path dependence, cumulative causation, hysteresis – on a network structure; and specific analytic tools are necessary for studying strategic interaction, heterogeneity and nonlinearities.