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!

The modeling of cities and territories has progressed greatly in the last 20 years. This is firstly due to geographic information systems, followed by the availability of large amounts of georeferenced data – both on the Internet and through the use of connected objects. In addition, the rise in performance of computational methods for the simulation and exploration of dynamic models has facilitated advancement. Geographical Modeling presents previously unpublished information on the main advances achieved by these new approaches. Each of the six chapters builds a bibliographic review and precisely describes the methods used, highlighting their advantages and discussing their interpretations. They are all illustrated by many examples. The book also explains with clarity the theoretical foundations of geographical analysis, the delicate operations of model selection, and the applications of fractals and scaling laws. These applications include gaining knowledge of the morphology of cities and the organization of urban transport, and finding new methods of building and exploring simulation models and visualizations of data and results.

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.

This is the era of Big Data and computational social science. It is an era that requires tools which can do more than visualise data but also model the complex relation between data and human action, and interaction. Agent-Based Models (ABM) - computational models which simulate human action and interaction – do just that. This textbook explains how to design and build ABM and how to link the models to Geographical Information Systems. It guides you from the basics through to constructing more complex models which work with data and human behaviour in a spatial context. All of the fundamental concepts are explained and related to practical examples to facilitate learning (with models developed in NetLogo with all code examples available on the accompanying website). You will be able to use these models to develop your own applications and link, where appropriate, to Geographical Information Systems. All of the key ideas and methods are explained in detail: geographical modelling; an introduction to ABM; the fundamentals of Geographical Information Science; why ABM and GIS; using QGIS; designing and building an ABM; calibration and validation; modelling human behavior. An applied primer, that provides fundamental knowledge and practical skills, it will provide you with the skills to build and run your own models, and to begin your own research projects.

Cutting-edge techniques for groundwater modeling using GIS technology Groundwater Modeling Using Geographical Information Systems covers fundamental information on flow and mass transport modeling and demonstrates how GIS technology makes these models and analyses more accurate than ever before. GIS technology allows for swift organization, quantification, and interpretation of large quantities of geohydrological data with computer accuracy and minimal risk of human error. This book's companion Web site provides the Princeton Transport Code, as well as the plug-in extensions required to interface this code with the Argus ONE numerical environment software enclosed with this book. Plug-in extensions for MODFLOW and MT3D computer codes can be found at the Argus ONE Web site (www.argusint.com). The process for using the Geographic Modeling Approach (GMA) to model groundwater flow and transport is demonstrated step by step with a field example from Tucson, Arizona. The GMA is composed of the Argus ONE Geographic Information Modeling system and the Princeton Transport Code groundwater flow and transport model, interfaced through the plug-in extension available on Argus ONE. Enhanced with more than 150 illustrations and screen captures, Groundwater Modeling Using Geographical Information Systems is a fundamental book for civil engineers, hydrologists, environmental engineers, geologists, and students in these fields, as well as software engineers working on GIS applications and environmental attorneys and regulators. When used in combination with the free modeling software, this book provides an excellent student text.

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 title focuses on the evolution of the modeling process and on new research perspectives in theoretical and applied geography, as well as spatial planning. In the last 50 years, the achievements of spatial analysis models opened the way to a new understanding of the relationship between society and geographical space. In this book, these models are confronted by the real conditions of territorial prospect, regional dynamism, cultural policy, HMO, and spatial segregation. This confrontation takes into account the instability of social behavior and the permanence of partial determinist trajectories.