Presents a unique study of Integrative Problem-Solving (IPS). The consideration of 'Decadence' is essential in the scientific study of environmental and other problems and their rigorous solution, because the broad context within which the problems emerge can affect their solution. Stochastic reasoning underlines the conceptual and methodological framework of IPS, and its formulation has a mathematical life of its own that accounts for the multidisciplinarity of real world problems, the multisourced uncertainties characterizing their solution, and the different thinking modes of the people involved. Only by interpolating between the full range of disciplines (including stochastic mathematics, physical science, neuropsychology, philosophy, and sociology) and the associated thinking modes can scientists arrive at a satisfactory account of problem-solving, and be able to distinguish between a technically complete problem-solution, and a solution that has social impact.

Trustonlymovement. Life happens at the level of events not of words. Trust movement. A. Adler As its title suggests,the main goal of this book is the development of advanced fu- tions for field-based Temporal Geographical Information Systems (TGIS).These fields may describe a variety of natural, epidemiological, economical, and social phen- ena distributed across space and time.Within such a framework,the book makes an attempt to establish links between, (a) the currently conceived TGIS techniques, and (b) the Bayesian maximum entropy (BME) techniques of Modern Spatiotemporal G- statistics.This link could be vital for offering significant improvements in the advanced functions of TGIS analysis and modelling, as well as generating useful information in a variety of real-world decision making and planning situations. To achieve the above goals, the eight Chapters of the book are organized around four main themes: Concepts, mathematical tools, computer programs, and applications. In fact, the focus is mainly on the step-by-step implementation of the compu- tional BME approach and the extensive use of illustrative examples and real-world applications.Indeed,because of the applied character of the present book,no detailed theoretical explanations or mathematical derivations are included. Instead,the reader is referred to the earlier book by Christakos (Modern Spatiotemporal Geostatistics, Oxford Univ.Press,New York, N.Y., 2000) for a comprehensive presentation of these BME aspects.With this in mind, the chapter-by-chapter organization of the book is described next.

Presents a unique study of Integrative Problem-Solving (IPS). The consideration of 'Decadence' is essential in the scientific study of environmental and other problems and their rigorous solution, because the broad context within which the problems emerge can affect their solution. Stochastic reasoning underlines the conceptual and methodological framework of IPS, and its formulation has a mathematical life of its own that accounts for the multidisciplinarity of real world problems, the multisourced uncertainties characterizing their solution, and the different thinking modes of the people involved. Only by interpolating between the full range of disciplines (including stochastic mathematics, physical science, neuropsychology, philosophy, and sociology) and the associated thinking modes can scientists arrive at a satisfactory account of problem-solving, and be able to distinguish between a technically complete problem-solution, and a solution that has social impact.

Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus provides a holistic, conceptual and quantitative framework for Environmental Health Modelling in space-time. The holistic framework integrates two aspects of Environmental Health Science that have been previously treated separately: the environmental aspect, which involves the natural processes that bring about human exposure to harmful substances; and the health aspect, which focuses on the interactions of these substances with the human body. Some of the fundamental issues addressed in this work include variability, scale, uncertainty, and space-time connectivity. These topics are important in the characterization of natural systems and health processes. Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus explains why modern stochastics is the appropriate mechanical vehicle for addressing such issues in a rigorous way. In particular, modern stochastics incorporates concepts and methods from probability, classical statistics, geostatistics, statistical mechanics and field theory. The authors present a synthetic view of environmental health that embraces all of the various components and focuses on their mutual interactions. Spatiotemporal Environmental Health Modeling: A Tractatus Stochasticus includes new material on Bayesian maximum entropy estimation techniques and space-time random field estimation methods. The authors show why these methods have clear advantages over the classical geostatistical estimation procedures and how they can be used to provide accurate space-time maps of environmental health processes. Also included are expositions of diagrammatic perturbation and renormalization group analysis, which have not been previously discussed within the context of Environmental Health. Finally, the authors present stochastic indicators that can be used for large-scale characterization of contamination and investigations of health effects at the microscopic level. This book will be a useful reference to both researchers and practitioners of Environmental Health Sciences. It will appeal specifically to environmental engineers, geographers, geostatisticians, earth scientists, toxicologists, epidemiologists, pharmacologists, applied mathematicians, physicists and biologists.

This multidisciplinary reference takes the reader through all four major phases of interdisciplinary inquiry: adequate conceptualization, rigorous formulation, substantive interpretation, and innovative implementation. The text introduces a novel synthetic paradigm of public health reasoning and epidemic modelling, and implements it with a study of the infamous 14th century AD Black Death disaster that killed at least one-fourth of the European population.

This multidisciplinary reference takes the reader through all four major phases of interdisciplinary inquiry: adequate conceptualization, rigorous formulation, substantive interpretation, and innovative implementation. The text introduces a novel synthetic paradigm of public health reasoning and epidemic modelling, and implements it with a study of the infamous 14th century AD Black Death disaster that killed at least one-fourth of the European population.

Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus provides a holistic, conceptual and quantitative framework for Environmental Health Modelling in space-time. The holistic framework integrates two aspects of Environmental Health Science that have been previously treated separately: the environmental aspect, which involves the natural processes that bring about human exposure to harmful substances; and the health aspect, which focuses on the interactions of these substances with the human body. Some of the fundamental issues addressed in this work include variability, scale, uncertainty, and space-time connectivity. These topics are important in the characterization of natural systems and health processes. Spatiotemporal Environmental Health Modelling: A Tractatus Stochasticus explains why modern stochastics is the appropriate mechanical vehicle for addressing such issues in a rigorous way. In particular, modern stochastics incorporates concepts and methods from probability, classical statistics, geostatistics, statistical mechanics and field theory. The authors present a synthetic view of environmental health that embraces all of the various components and focuses on their mutual interactions. Spatiotemporal Environmental Health Modeling: A Tractatus Stochasticus includes new material on Bayesian maximum entropy estimation techniques and space-time random field estimation methods. The authors show why these methods have clear advantages over the classical geostatistical estimation procedures and how they can be used to provide accurate space-time maps of environmental health processes. Also included are expositions of diagrammatic perturbation and renormalization group analysis, which have not been previously discussed within the context of Environmental Health. Finally, the authors present stochastic indicators that can be used for large-scale characterization of contamination and investigations of health effects at the microscopic level. This book will be a useful reference to both researchers and practitioners of Environmental Health Sciences. It will appeal specifically to environmental engineers, geographers, geostatisticians, earth scientists, toxicologists, epidemiologists, pharmacologists, applied mathematicians, physicists and biologists.

The book focuses on the development of advanced functions for field-based Temporal Geographical Information Systems (TGIS). These fields describe natural, epidemiological, economic, and social phenomena distributed across space and time. The book is organized around 4 main themes: concepts, mathematical tools, computer programs, and applications.The reader is also familiarized with the TGIS toolbox of advanced functions and the associated library of comprehensive computer programs, BMElib.A CD-ROM is included with the book, so that the reader can readily use the computerized advanced TGIS functions of the BMElib to reconstruct many of the numerical applications discussed in the book.

Quantitative Analysis and Modeling of Earth and Environmental Data: Space-Time and Spacetime Data Considerations introduces the notion of chronotopologic data analysis that offers a systematic, quantitative analysis of multi-sourced data and provides information about the spatial distribution and temporal dynamics of natural attributes (physical, biological, health, social). It includes models and techniques for handling data that may vary by space and/or time, and aims to improve understanding of the physical laws of change underlying the available numerical datasets, while taking into consideration the in-situ uncertainties and relevant measurement errors (conceptual, technical, computational). It considers the synthesis of scientific theory-based methods (stochastic modeling, modern geostatistics) and data-driven techniques (machine learning, artificial neural networks) so that their individual strengths are combined by acting symbiotically and complementing each other. The notions and methods presented in Quantitative Analysis and Modeling of Earth and Environmental Data: Space-Time and Spacetime Data Considerations cover a wide range of data in various forms and sources, including hard measurements, soft observations, secondary information and auxiliary variables (ground-level measurements, satellite observations, scientific instruments and records, protocols and surveys, empirical models and charts). Including real-world practical applications as well as practice exercises, this book is a comprehensive step-by-step tutorial of theory-based and data-driven techniques that will help students and researchers master data analysis and modeling in earth and environmental sciences (including environmental health and human exposure applications).

Spatiotemporal Random Fields: Theory and Applications, Second Edition, provides readers with a new and updated edition of the text that explores the application of spatiotemporal random field models to problems in ocean, earth, and atmospheric sciences, spatiotemporal statistics, and geostatistics, among others. The new edition features considerable detail of spatiotemporal random field theory, including ordinary and generalized models, as well as space-time homostationary, isostationary and hetrogeneous approaches. Presenting new theoretical and applied results, with particular emphasis on space-time determination and interpretation, spatiotemporal analysis and modeling, random field geometry, random functionals, probability law, and covariance construction techniques, this book highlights the key role of space-time metrics, the physical interpretation of stochastic differential equations, higher-order space-time variability functions, the validity of major theoretical assumptions in real-world practice (covariance positive-definiteness, metric-adequacy etc.), and the emergence of interdisciplinary phenomena in conditions of multi-sourced real-world uncertainty.

This scholarly introductory treatment explores the fundamentals of modern geostatistics, viewing them as the product of the advancement of the epistemic status of stochastic data analysis. The focus on the Bayesian maximum entropy approach for studying spatiotemporal distributions of natural variables offers a deeper understanding of geostatistics in models of scientific mapping. 2000 edition.

The validity of certain critical reasoning steps carried out during or on the sidelines of the environmental science, public health survey, medical experiment, population risk assessment, or disease space-time mapping under conditions of in situ uncertainty and space-time heterogeneity, is often not given sufficient attention and may even be out of the investigator's line of thought. For example, the technical complexity of an environmental exposure experiment may overshadow the logical assumptions made when moving from one phase of the experiment to the next, or the study of population risk assessment may focus on analytical and computational matters, whereas methodological and cultural factors are neglected.This book helps health investigators structure their thinking so that they avoid logical mistakes and argument pitfalls, and also gain new insights about reality, improve their awareness of the environment and context within which one's thinking takes place.