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Designed to be a high-level, approachable resource for engineers who need further insight into spatial temporal information systems from an ontological perspective, Spatial Temporal Information Systems: An Ontological Approach using STK® explains the dynamics of objects interaction from signal analysis to trajectory design, spatial modeling, and other spatial analytics by using STK®, which is a general-purpose modeling and analysis application for any type of space, defense, or intelligence system. Building a foundation to begin the study of spatial temporal information systems, the book details a form of analysis that is a powerful tool for modeling, engineering, and operations of space, cyberspace, satellites, missile defense, and electronic systems. It discusses the many applications of space technologies by using a mission-proven software for timely and cost-effective development that serves public interests in civil, commercial, academic, national, and international space communities. Written for readers with a background in physics or engineering, the book is also designed for the beginning analyst sitting behind a desk who needs more information on STK. Upon reading this book, STK new users and power users will not only understand what the tools are, but also how the software can be used to make their job easier. In addition, satellite operators and analysts benefit from the ability to utilize a variety of propagators satellite applications. Analytics, semi-analytic and numerical integrators are discussed, including Keplerian orbital elements and full numerical integration of STK’s High Precision Orbit Propagation or simplified as a two-body analysis. This tool, as well as this book, will bring breadth and depth to the understanding of systems dynamics and the ontology of objects in relationship to other objects and vehicles including central bodies.
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).
Spatio-Temporal Databases explores recent trends in flexible querying and reasoning about time- and space-related information in databases. It shows how flexible querying enhances standard querying expressiveness in many different ways, with the aim of facilitating extraction of relevant data and information. Flexible spatial and temporal reasoning denotes qualitative reasoning about dynamic changes in the spatial domain, characterized by imprecision or uncertainty (or both). Many of the contributions focus on GIS, while some others are more general, or focus on related application fields, presenting theoretical viewpoints and techniques that are inspiring or can be adapted for GIS. The first part bundles the contributions on advances at the theoretical level, also discussing examples and opening further perspectives. The second part presents contributions on well-developed applications. The authors explain how to handle imprecision and uncertainty, demonstrating how advanced techniques can help to solve diverse problems related to GIS.
CD-ROM contains: BMElib, a set of programs for spatiotemporal geostatistics in Temporal GIS written in MatLab (version 5.3 and later).
This book constitutes the refereed proceedings of the 15th International Symposium on Spatial and Temporal Databases, SSTD 2017, held in Arlington, VA, USA, in August 2017.The 19 full papers presented together with 8 demo papers and 5 vision papers were carefully reviewed and selected from 90 submissions. The papers are organized around the current research on concepts, tools, and techniques related to spatial and temporal databases.
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.
Spatio-temporal networks (STN)are spatial networks whose topology and/or attributes change with time. These are encountered in many critical areas of everyday life such as transportation networks, electric power distribution grids, and social networks of mobile users. STN modeling and computations raise significant challenges. The model must meet the conflicting requirements of simplicity and adequate support for efficient algorithms. Another challenge is to address the change in the semantics of common graph operations, such as, shortest path computation assuming different semantics, or when temporal dimension is added. Also paradigms (e.g. dynamic programming) used in algorithm design may be ineffective since their assumptions (e.g. stationary ranking of candidates) may be violated by the dynamic nature of STNs. In recent years, STNs have attracted attention in research. New representations have been proposed along with algorithms to perform key STN operations, while accounting for their time dependence. Designing a STN database would require the development of data models, query languages, and indexing methods to efficiently represent, query, store, and manage time-variant properties of the network. The purpose of Spatio-temporal Networks: Modeling and Algorithms is to explore this design at the conceptual, logical, and physical level. Models used to represent STNs are explored and analyzed. STN operations, with an emphasis on their altered semantics with the addition of temporal dimension, are also addressed.
Mining Spatio-Temporal Information Systems, an edited volume is composed of chapters from leading experts in the field of Spatial-Temporal Information Systems and addresses the many issues in support of modeling, creation, querying, visualizing and mining. Mining Spatio-Temporal Information Systems is intended to bring together a coherent body of recent knowledge relating to STIS data modeling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the latest techniques for the practical design of STIS, essential for complex query processing. Mining Spatio-Temporal Information Systems is structured to meet the needs of practitioners and researchers in industry and graduate-level students in Computer Science.
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.
Winner of the 2013 DeGroot Prize. A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods Noel Cressie and Christopher K. Wikle, are also winners of the 2011 PROSE Award in the Mathematics category, for the book “Statistics for Spatio-Temporal Data” (2011), published by John Wiley and Sons. (The PROSE awards, for Professional and Scholarly Excellence, are given by the Association of American Publishers, the national trade association of the US book publishing industry.) Statistics for Spatio-Temporal Data has now been reprinted with small corrections to the text and the bibliography. The overall content and pagination of the new printing remains the same; the difference comes in the form of corrections to typographical errors, editing of incomplete and missing references, and some updated spatio-temporal interpretations. From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models. Cressie and Wikle supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes. Topics of coverage include: Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs Spatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes Development of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation Quantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental data Throughout the book, interesting applications demonstrate the relevance of the presented concepts. Vivid, full-color graphics emphasize the visual nature of the topic, and a related FTP site contains supplementary material. Statistics for Spatio-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.