The book focuses on the development of advanced functions for field-based temporal geographical information systems (TGIS). These fields describe natural, epidemiological, economical, and social phenomena distributed across space and time. The book is organized around four main themes: "Concepts, mathematical tools, computer programs, and applications". Chapters I and II review the conceptual framework of the modern TGIS and introduce the fundamental ideas of spatiotemporal modelling. Chapter III discusses issues of knowledge synthesis and integration. Chapter IV presents state-of-the-art mathematical tools of spatiotemporal mapping. Links between existing TGIS techniques and the modern Bayesian maximum entropy (BME) method offer significant improvements in the advanced TGIS functions. Comparisons are made between the proposed functions and various other techniques (e.g., Kriging, and Kalman-Bucy filters). Chapter V analyzes the interpretive features of the advanced TGIS functions, establishing correspondence between the natural system and the formal mathematics which describe it. In Chapters IV and V one can also find interesting extensions of TGIS functions (e.g., non-Bayesian connectives and Fisher information measures). Chapters VI and VII familiarize the reader with the TGIS toolbox and the associated library of comprehensive computer programs. Chapter VIII discusses important applications of TGIS in the context of scientific hypothesis testing, explanation, and decision making.

CD-ROM contains: BMElib, a set of programs for spatiotemporal geostatistics in Temporal GIS written in MatLab (version 5.3 and later).

This book explores new methods and techniques for research about merchant networks and maritime routes of trade during the First Global Age through the use of Geographic Information Systems (GIS) as a tool to visualize the formation of trading systems, database management, cartography and spatio-temporal analysis in Historical GIS. In doing so, the book focuses on key issues in understanding the birth of the so-called First Global Age (16th to 18th centuries): the integration of spatial economies; the regionalization of markets; the organization of maritime trade routes; and the evolution of self-organizing networks of merchants, producers, communities, and other social agents during the age of expansion. The essays collected here deal with relevant information about historical problems including maritime connections, the organization of oceanic trade and the use of digital cartography and metric analysis of old maps, and social network analysis – commercial networks involved a high level of cooperation and served to move goods and people within a highly open system over an expanding geographic space.

The book deals with the integration of temporal information in Geographic Information Systems. The main purpose of an historical or time-integrative GIS is to reproduce spatio- temporal processes or sequents of events in the real world in the form of a model. The model thus making them accessible for spatial query, analysis and visualization. This volume reflects both theoretical thoughts on the interrelations of space and time, as well as practical examples taken from various fields of application (e.g. business data warehousing, demographics, history and spatial analysis).

There has been an increasing demand in GIS for systems that support historical data: time-series data as well as mobility information. From a modelling perspective, there are advantages in integrating object-oriented analysis and design to databases as well as to visualisation capabilities of GIS. Object-Oriented Design for Temporal GIS explores the major components of the object-oriented analysis and design methods, how they can be used for modelling spatio-temporal data, and how these components are developed and maintained within a GIS. It also offers practical guidance to object-oriented methods by demonstrating the feasibility of applying such methods to issues involved in handling spatio-temporal data. The author demonstrates how this knowledge might be used in a wide range of applications such as political boundary record maintenance (historical data), disease incidence rate analysis in epidemics (diffusion rate), and environmental studies of climate change (time-series data). This understanding contributes to the development of theory in GIS and improves the design of GIS to support the modelling of semantics, space and time elements of geographical information.

Over the last two decades, many researchers have focused on developing countries' urbanization patterns and processes. In this context, the scarcity of spatial data has been an obstacle to studying urbanization quantitatively, especially in Asian and African cities. The use of remote sensing data and geographical information systems (GIS) techniques can overcome the above limitations. Data on land use and land cover, land surface temperature, population density, and energy consumption can be extracted based on remote sensing at various spatial and temporal resolutions. GIS techniques can be used to analyze urbanization patterns and predict future patterns. Thus, the link between urbanization and sustainable urban development has increasingly become a principal issue in designing and developing sustainable cities at the local, regional, and global levels. This volume shows the spatiotemporal analysis of urbanization using GIS and remote sensing in developing countries, with a special emphasis on future urban sustainability in Asia and Africa. Capturing the spatial-temporal variation of urbanization patterns will help introduce proper sustainable urban planning in developing countries, especially for Asian and African cities.

This volume collects the papers presented at the first international conference dedicated to spatial and temporal reasoning in geographic space, entitled "GIS: from space to territory - theories and methods of spatio-temporal reasoning". Within the National Center for Geographic Information and Analysis (NCGIA, one of the supporters of the conference) the importance of spatial and temporal reasoning was recognized several years ago. Initial research found that spatial reasoning in geographic or large-scale space is different from spatial reasoning in small-scale space, as usually dealt with in robotics and expertsystems. Temporal reasoning has attracted interest in the artificial intelligence community. The volume also includes two invited papers: "Do people understand spatial concepts: the case of first-order primtives" by R.G. Golledge, and "Temporal databases" by R.T. Snodgrass.

Geographic Information Systems are computer-based systems for geographic analysis. They have been developed over the past twenty five years and are now widely used. A recent research direction has been the development of geocomputation , representing computer-based geographical analysis beyond the traditional bounds of GIS. In geocomputation, th

This aims to make the computing principles underlying geographic databases understandable and accessible to current and potential users of such systems. It overviews database system philosophy; describes database concepts eg storage, retrieval, architecture, conceptual modelling, and database querying.It then focuses on the characteristics of GIS, spatial data and spatial databases, concluding with a discussion of current/future research trends.

The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book: Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical models and basis function expansions, and finishing with model evaluation Provides a gradual entry to the methodological aspects of spatio-temporal statistics Provides broad coverage of using R as well as "R Tips" throughout. Features detailed examples and applications in end-of-chapter Labs Features "Technical Notes" throughout to provide additional technical detail where relevant Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more The book fills a void in the literature and available software, providing a bridge for students and researchers alike who wish to learn the basics of spatio-temporal statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and statistics, and who is comfortable with basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many people as possible the tools and confidence to analyze spatio-temporal data.