Advances In Spatio Temporal Analysis
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Author |
: Xinming Tang |
Publisher |
: CRC Press |
Total Pages |
: 252 |
Release |
: 2007-08-23 |
ISBN-10 |
: 9780203937556 |
ISBN-13 |
: 0203937554 |
Rating |
: 4/5 (56 Downloads) |
Synopsis Advances in Spatio-Temporal Analysis by : Xinming Tang
Developments in Geographic Information Technology have raised the expectations of users. A static map is no longer enough; there is now demand for a dynamic representation. Time is of great importance when operating on real world geographical phenomena, especially when these are dynamic. Researchers in the field of Temporal Geographical Infor
Author |
: Gidon Eshel |
Publisher |
: Princeton University Press |
Total Pages |
: 337 |
Release |
: 2012 |
ISBN-10 |
: 9780691128917 |
ISBN-13 |
: 069112891X |
Rating |
: 4/5 (17 Downloads) |
Synopsis Spatiotemporal Data Analysis by : Gidon Eshel
How do we study the storm's mutation into a deadly twister? Avian flu cases are reported in China.
Author |
: Michael Gertz |
Publisher |
: Springer |
Total Pages |
: 454 |
Release |
: 2017-08-07 |
ISBN-10 |
: 9783319643670 |
ISBN-13 |
: 3319643673 |
Rating |
: 4/5 (70 Downloads) |
Synopsis Advances in Spatial and Temporal Databases by : Michael Gertz
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.
Author |
: Hsu, Wynne |
Publisher |
: IGI Global |
Total Pages |
: 292 |
Release |
: 2007-07-31 |
ISBN-10 |
: 9781599043890 |
ISBN-13 |
: 1599043890 |
Rating |
: 4/5 (90 Downloads) |
Synopsis Temporal and Spatio-Temporal Data Mining by : Hsu, Wynne
"This book presents probable solutions when discovering the spatial sequence patterns by incorporating the information into the sequence of patterns, and introduces new classes of spatial sequence patterns, called flow and generalized spatio-temporal patterns, addressing different scenarios in spatio-temporal data by modeling them as graphs, providing a comprehensive synopsis on two successful partition-based algorithms designed by the authors"--Provided by publisher.
Author |
: Gavin Shaddick |
Publisher |
: CRC Press |
Total Pages |
: 383 |
Release |
: 2015-06-17 |
ISBN-10 |
: 9781482237047 |
ISBN-13 |
: 1482237040 |
Rating |
: 4/5 (47 Downloads) |
Synopsis Spatio-Temporal Methods in Environmental Epidemiology by : Gavin Shaddick
Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological StudiesSpatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling. In response to the growing need for collaboration between statisticians and
Author |
: Gerald Corzo |
Publisher |
: Elsevier |
Total Pages |
: 194 |
Release |
: 2018-11-20 |
ISBN-10 |
: 9780128117316 |
ISBN-13 |
: 0128117311 |
Rating |
: 4/5 (16 Downloads) |
Synopsis Spatiotemporal Analysis of Extreme Hydrological Events by : Gerald Corzo
Spatio-temporal Analysis of Extreme Hydrological Events offers an extensive view of the experiences and applications of the latest developments and methodologies for analyzing and understanding extreme environmental and hydrological events. The book addresses the topic using spatio-temporal methods, such as space-time geostatistics, machine learning, statistical theory, hydrological modelling, neural network and evolutionary algorithms. This important resource for both hydrologists and statisticians interested in the framework of spatial and temporal analysis of hydrological events will provide users with an enhanced understanding of the relationship between magnitude, dynamics and the probability of extreme hydrological events. - Presents spatio-temporal processes, including multivariate dynamic modelling - Provides varying methodological approaches, giving the readers multiple hydrological modelling information to use in their work - Includes a variety of case studies making the context of the book relatable to everyday working situations
Author |
: Christopher K. Wikle |
Publisher |
: CRC Press |
Total Pages |
: 397 |
Release |
: 2019-02-18 |
ISBN-10 |
: 9780429649783 |
ISBN-13 |
: 0429649789 |
Rating |
: 4/5 (83 Downloads) |
Synopsis Spatio-Temporal Statistics with R by : Christopher K. Wikle
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.
Author |
: Noel Cressie |
Publisher |
: John Wiley & Sons |
Total Pages |
: 612 |
Release |
: 2015-11-02 |
ISBN-10 |
: 9781119243045 |
ISBN-13 |
: 1119243041 |
Rating |
: 4/5 (45 Downloads) |
Synopsis Statistics for Spatio-Temporal Data by : Noel Cressie
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.
Author |
: Anthony G.O. Yeh |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 250 |
Release |
: 2012-06-06 |
ISBN-10 |
: 9783642259265 |
ISBN-13 |
: 364225926X |
Rating |
: 4/5 (65 Downloads) |
Synopsis Advances in Spatial Data Handling and GIS by : Anthony G.O. Yeh
This book provides a cross-section of cutting-edge research areas being pursued by researchers in spatial data handling and geographic information science (GIS). It presents selected papers on the advancement of spatial data handling and GIS in digital cartography, geospatial data integration, geospatial database and data infrastructures, geospatial data modeling, GIS for sustainable development, the interoperability of heterogeneous spatial data systems, location-based services, spatial knowledge discovery and data mining, spatial decision support systems, spatial data structures and algorithms, spatial statistics, spatial data quality and uncertainty, the visualization of spatial data, and web and wireless applications in GIS.
Author |
: Elias T. Krainski |
Publisher |
: CRC Press |
Total Pages |
: 284 |
Release |
: 2018-12-07 |
ISBN-10 |
: 9780429629853 |
ISBN-13 |
: 0429629850 |
Rating |
: 4/5 (53 Downloads) |
Synopsis Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA by : Elias T. Krainski
Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications. This book has been authored by leading experts in spatial statistics, including the main developers of the INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications: * Spatial and spatio-temporal models for continuous outcomes * Analysis of spatial and spatio-temporal point patterns * Coregionalization spatial and spatio-temporal models * Measurement error spatial models * Modeling preferential sampling * Spatial and spatio-temporal models with physical barriers * Survival analysis with spatial effects * Dynamic space-time regression * Spatial and spatio-temporal models for extremes * Hurdle models with spatial effects * Penalized Complexity priors for spatial models All the examples in the book are fully reproducible. Further information about this book, as well as the R code and datasets used, is available from the book website at http://www.r-inla.org/spde-book. The tools described in this book will be useful to researchers in many fields such as biostatistics, spatial statistics, environmental sciences, epidemiology, ecology and others. Graduate and Ph.D. students will also find this book and associated files a valuable resource to learn INLA and the SPDE approach for spatial modeling.