Spatial and Spatio Temporal Geostatistical Modeling and Kriging

Spatial and Spatio Temporal Geostatistical Modeling and Kriging

This text will also prove to be a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.

Author: José-María Montero

Publisher: John Wiley & Sons

ISBN: 9781118762431

Category: Mathematics

Page: 400

View: 996

Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R. This book includes: Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods. The most innovative developments in the different steps of the kriging process. An up-to-date account of strategies for dealing with data evolving in space and time. An accompanying website featuring R code and examples
Categories: Mathematics

Modern Spatiotemporal Geostatistics

Modern Spatiotemporal Geostatistics

An innovative contribution to the field of space and time analysis, this volume offers many potential applications in epidemiology, geography, biology, and other fields.

Author: George Christakos

Publisher: Courier Corporation

ISBN: 9780486310930

Category: Science

Page: 304

View: 852

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 book's main focus is the Bayesian maximum entropy approach for studying spatiotemporal distributions of natural variables, an approach that offers readers a deeper understanding of the role of geostatistics in improved mathematical models of scientific mapping. Starting with a overview of the uses of spatiotemporal mapping in the natural sciences, the text explores spatiotemporal geometry, the epistemic paradigm, the mathematical formulation of the Bayesian maximum entropy method, and analytical expressions of the posterior operator. Additional topics include uncertainty assessment, single- and multi-point analytical formulations, and popular methods. An innovative contribution to the field of space and time analysis, this volume offers many potential applications in epidemiology, geography, biology, and other fields.
Categories: Science

Statistics for Spatio Temporal Data

Statistics for Spatio Temporal Data

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 ...

Author: Noel Cressie

Publisher: John Wiley & Sons

ISBN: 9780471692744

Category: Mathematics

Page: 588

View: 330

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.
Categories: Mathematics

Spatial Statistics and Spatio Temporal Data

Spatial Statistics and Spatio Temporal Data

This book focuses on covariance and variogram functions, their role in prediction, and appropriate choice of these functions in applications.

Author: Michael Sherman

Publisher: John Wiley & Sons

ISBN: 0470974923

Category: Mathematics

Page: 240

View: 860

In the spatial or spatio-temporal context, specifying the correct covariance function is fundamental to obtain efficient predictions, and to understand the underlying physical process of interest. This book focuses on covariance and variogram functions, their role in prediction, and appropriate choice of these functions in applications. Both recent and more established methods are illustrated to assess many common assumptions on these functions, such as, isotropy, separability, symmetry, and intrinsic correlation. After an extensive introduction to spatial methodology, the book details the effects of common covariance assumptions and addresses methods to assess the appropriateness of such assumptions for various data structures. Key features: An extensive introduction to spatial methodology including a survey of spatial covariance functions and their use in spatial prediction (kriging) is given. Explores methodology for assessing the appropriateness of assumptions on covariance functions in the spatial, spatio-temporal, multivariate spatial, and point pattern settings. Provides illustrations of all methods based on data and simulation experiments to demonstrate all methodology and guide to proper usage of all methods. Presents a brief survey of spatial and spatio-temporal models, highlighting the Gaussian case and the binary data setting, along with the different methodologies for estimation and model fitting for these two data structures. Discusses models that allow for anisotropic and nonseparable behaviour in covariance functions in the spatial, spatio-temporal and multivariate settings. Gives an introduction to point pattern models, including testing for randomness, and fitting regular and clustered point patterns. The importance and assessment of isotropy of point patterns is detailed. Statisticians, researchers, and data analysts working with spatial and space-time data will benefit from this book as well as will graduate students with a background in basic statistics following courses in engineering, quantitative ecology or atmospheric science.
Categories: Mathematics

Integrated Intelligent Computing Communication and Security

Integrated Intelligent Computing  Communication and Security

If spatiotemporal co-kriging is used and filtering-based clustering [3] is applied
before kriging, the results can be improved even more. References 1. ... Spatial
and spatio-temporal geostatistical modeling and kriging, vol. 998, 162–267.

Author: A.N. Krishna

Publisher: Springer

ISBN: 9789811087974

Category: Technology & Engineering

Page: 700

View: 119

This book highlights the emerging field of intelligent computing and developing smart systems. It includes chapters discussing the outcome of challenging research related to distributed computing, smart machines and their security related research, and also covers next-generation communication techniques and the networking technologies that have the potential to build the future communication infrastructure. Bringing together computing, communications and other aspects of intelligent and smart computing, it contributes to developing a roadmap for future research on intelligent systems.
Categories: Technology & Engineering

Multiple point Geostatistics

Multiple point Geostatistics

This book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images.

Author: Professor Gregoire Mariethoz

Publisher: John Wiley & Sons

ISBN: 9781118662755

Category: Science

Page: 376

View: 266

Categories: Science

Spatiotemporal Analysis of Extreme Hydrological Events

Spatiotemporal Analysis of Extreme Hydrological Events

Furthermore, spaceetime kriging was used for the design of rainfall networks in
time and space (Rodriguez-Iturbe and Mejia, ... Spatiotemporal Geostatistical
Modeling Spatiotemporal geostatistical models provide a probabilistic Chapter 2
 ...

Author: Gerald Corzo

Publisher: Elsevier

ISBN: 9780128117316

Category: Science

Page: 192

View: 699

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
Categories: Science

Semantic Kriging for Spatio temporal Prediction

Semantic Kriging for Spatio temporal Prediction

This book identifies the need for modeling auxiliary knowledge of the terrain to enhance the prediction accuracy of meteorological parameters.

Author: Shrutilipi Bhattacharjee

Publisher: Springer

ISBN: 9789811386640

Category: Technology & Engineering

Page: 127

View: 772

This book identifies the need for modeling auxiliary knowledge of the terrain to enhance the prediction accuracy of meteorological parameters. The spatial and spatio-temporal prediction of these parameters are important for the scientific community, and the semantic kriging (SemK) and its variants facilitate different types of prediction and forecasting, such as spatial and spatio-temporal, a-priori and a-posterior, univariate and multivariate. As such, the book also covers the process of deriving the meteorological parameters from raw satellite remote sensing imagery, and helps understanding different prediction method categories and the relation between spatial interpolation methods and other prediction methods. The book is a valuable resource for researchers working in the area of prediction of meteorological parameters, semantic analysis (ontology-based reasoning) of the terrain, and improving predictions using auxiliary knowledge of the terrain.
Categories: Technology & Engineering

Spatio temporal Design

Spatio temporal Design

Motivated by the high demand for statistical analysis of data that takes spatial and spatio-temporal information into account, this book incorporates ideas from the areas of time series, spatial statistics and stochastic processes, and ...

Author: Jorge Mateu

Publisher: John Wiley & Sons

ISBN: 9781118441886

Category: Mathematics

Page: 382

View: 942

A state-of-the-art presentation of optimum spatio-temporalsampling design - bridging classic ideas with modern statisticalmodeling concepts and the latest computational methods. Spatio-temporal Design presents a comprehensivestate-of-the-art presentation combining both classical and moderntreatments of network design and planning for spatial andspatio-temporal data acquisition. A common problem set isinterwoven throughout the chapters, providing various perspectivesto illustrate a complete insight to the problem at hand. Motivated by the high demand for statistical analysis of datathat takes spatial and spatio-temporal information into account,this book incorporates ideas from the areas of time series, spatialstatistics and stochastic processes, and combines them to discussoptimum spatio-temporal sampling design. Spatio-temporal Design: Advances in Efficient DataAcquisition: Provides an up-to-date account of how to collect space-timedata for monitoring, with a focus on statistical aspects and thelatest computational methods Discusses basic methods and distinguishes between design andmodel-based approaches to collecting space-time data. Features model-based frequentist design for univariate andmultivariate geostatistics, and second-phase spatial sampling. Integrates common data examples and case studies throughout thebook in order to demonstrate the different approaches and theirintegration. Includes real data sets, data generating mechanisms andsimulation scenarios. Accompanied by a supporting website featuring R code. Spatio-temporal Design presents an excellent book forgraduate level students as well as a valuable reference forresearchers and practitioners in the fields of applied mathematics,engineering, and the environmental and health sciences.
Categories: Mathematics

Spatial and Spatio temporal Bayesian Models with R INLA

Spatial and Spatio temporal Bayesian Models with R   INLA

306 INDEX Disease mapping, 3, 176, 177–184, 186–190,235–236 Spatial
random effects, 178–180, 182,206, 214, 220, ... Dynamic spatio-temporal models,
290, 295 Epidemiology, spatial see Disease mapping Exchangeable random
effects, ... 272, 276 Generalized linear model, 5, 11, 41, 108, 127, 138, 151
Genetic linkage model, 99 Geostatistical models, 173, ... 121–123 Knot, 296–301
Kriging, 2, 11, 13, Kronecker product, 236, 241–244, 286, 291, 302 Laplace
approximation, ...

Author: Marta Blangiardo

Publisher: John Wiley & Sons

ISBN: 9781118950197

Category: Mathematics

Page: 320

View: 209

Spatial and Spatio-Temporal Bayesian Models withR-INLA provides a much needed, practically oriented& innovative presentation of the combination of Bayesianmethodology and spatial statistics. The authors combine anintroduction to Bayesian theory and methodology with a focus on thespatial and spatio­-temporal models used within the Bayesianframework and a series of practical examples which allow the readerto link the statistical theory presented to real data problems. Thenumerous examples from the fields of epidemiology, biostatisticsand social science all are coded in the R package R-INLA, which hasproven to be a valid alternative to the commonly used Markov ChainMonte Carlo simulations
Categories: Mathematics

Machine Learning for Spatial Environmental Data

Machine Learning for Spatial Environmental Data

Some geostatistical models have been modified in order to predict spatio-
temporal data. The present chapter deals with the presentation of the main
hypotheses and basic models used in geostatistics for the analysis and
modelling of spatial environmental data. ... Universal kriging is a geostatistical
model that directly takes into account the spatial nonstationarity by modelling the
trend with low degree ...

Author: Mikhail Kanevski

Publisher: CRC Press

ISBN: 9781439808085

Category: Computers

Page: 400

View: 312

This book discusses machine learning algorithms, such as artificial neural networks of different architectures, statistical learning theory, and Support Vector Machines used for the classification and mapping of spatially distributed data. It presents basic geostatistical algorithms as well. The authors describe new trends in machine learning and their application to spatial data. The text also includes real case studies based on environmental and pollution data. It includes a CD-ROM with software that will allow both students and researchers to put the concepts to practice.
Categories: Computers

GeoENV IV Geostatistics for Environmental Applications

GeoENV IV   Geostatistics for Environmental Applications

SPATIO-TEMPORAL KRIGING OF SOIL SALINITY RESCALED FROM BULK
SOIL ELECTRICAL CONDUCTIVITY A. Douaik'o, ... The residuals of the ordinary
least squares model were tested for the absence of spatial dependence using the
 ...

Author: Xavier Sanchez-Vila

Publisher: Springer Science & Business Media

ISBN: 1402021143

Category: Mathematics

Page: 541

View: 634

This volume contains forty-one selected full-text contributions from the Fourth European Conference on Geostatistics for Environmental Applications, geoENV IV, held in Barcelona, Spain, November 2002. The objective of the editors was to compile a set of papers from which the reader could perceive how geostatistics is applied within the environmental sciences. A few selected theoretical contributions are also included. The papers are organized in the following sections: -Air pollution and satellite images, -Ecology and environment, -Hydrogeology, -Climatology and rainfall, -Oceanography, -Soil science, -Methodology. Applications of geostatistics vary from particle matter analysis, land cover classification, space-time ozone mapping, downscaling of precipitation, contaminant transport in the subsurface, aquifer reclamation, analysis of Iberian hare or phytoplankton abundance, coastal current patterns, to soil pollution by heavy metals or dioxins. At the back of the book nineteen posters presented at the congress are included. The combination of full texts and posters provides a picture of the tendencies that can presently be found in Europe regarding the applications of geostatistics for environmentally related problems. Audience: After four editions the geoENV Congress Series has established itself as a 'must' to all scientists working in the field of geostatistics for environmental applications. Each geoENV congress covers the developments which have occurred during the preceding two years, but always with a highly applied focus. It is precisely this focus on the applications to environmental sciences which makes the geoENV volumes unique and of great interest and practical value to geostatisticians working both in academia and in industry.
Categories: Mathematics

Hierarchical Modeling and Analysis for Spatial Data

Hierarchical Modeling and Analysis for Spatial Data

Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis,

Author: Sudipto Banerjee

Publisher: CRC Press

ISBN: 9781135438081

Category: Mathematics

Page: 472

View: 496

Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis,
Categories: Mathematics

Advances and Challenges in Space time Modelling of Natural Events

Advances and Challenges in Space time Modelling of Natural Events

This book arises as the natural continuation of the International Spring School "Advances and Challenges in Space-Time modelling of Natural Events," which took place in Toledo (Spain) in March 2010.

Author: Emilio Porcu

Publisher: Springer Science & Business Media

ISBN: 9783642170867

Category: Mathematics

Page: 252

View: 261

This book arises as the natural continuation of the International Spring School "Advances and Challenges in Space-Time modelling of Natural Events," which took place in Toledo (Spain) in March 2010. This Spring School above all focused on young researchers (Master students, PhD students and post-doctoral researchers) in academics, extra-university research and the industry who are interested in learning about recent developments, new methods and applications in spatial statistics and related areas, and in exchanging ideas and findings with colleagues.
Categories: Mathematics

Bayesian Statistics 7

Bayesian Statistics 7

... consider hierarchical spatial process models for multivariate survival data sets
which are spatio - temporally arranged . ... limitations and computational
complexity issues , we avoid geostatistical ( kriging ) models , and instead handle
spatial ...

Author: Dennis V. Lindley

Publisher: Oxford University Press

ISBN: 0198526156

Category: Mathematics

Page: 750

View: 777

This volume contains the proceedings of the 7th Valencia International Meeting on Bayesian Statistics. This conference is held every four years and provides the main forum for researchers in the area of Bayesian statistics to come together to present and discuss frontier developments in the field.
Categories: Mathematics

OSU Statistics Technical Report

OSU Statistics Technical Report

Key Words : Attribute error , CP model , FP model , errors - in - variables ,
geographic information systems , geostatistics , GPS , kriging 1 Introduction The
field of spatial ( and spatio - temporal ) statistics is a fertile area for innovations in
data ...

Author: Ohio State University. Department of Statistics

Publisher:

ISBN: OSU:32435069060309

Category: Statistics

Page:

View: 236

Categories: Statistics

Hierarchical Modeling and Analysis for Spatial Data Second Edition

Hierarchical Modeling and Analysis for Spatial Data  Second Edition

New to the Second Edition New chapter on spatial point patterns developed primarily from a modeling perspective New chapter on big data that shows how the predictive process handles reasonably large datasets New chapter on spatial and ...

Author: Sudipto Banerjee

Publisher: CRC Press

ISBN: 9781439819173

Category: Mathematics

Page: 584

View: 804

Keep Up to Date with the Evolving Landscape of Space and Space-Time Data Analysis and Modeling Since the publication of the first edition, the statistical landscape has substantially changed for analyzing space and space-time data. More than twice the size of its predecessor, Hierarchical Modeling and Analysis for Spatial Data, Second Edition reflects the major growth in spatial statistics as both a research area and an area of application. New to the Second Edition New chapter on spatial point patterns developed primarily from a modeling perspective New chapter on big data that shows how the predictive process handles reasonably large datasets New chapter on spatial and spatiotemporal gradient modeling that incorporates recent developments in spatial boundary analysis and wombling New chapter on the theoretical aspects of geostatistical (point-referenced) modeling Greatly expanded chapters on methods for multivariate and spatiotemporal modeling New special topics sections on data fusion/assimilation and spatial analysis for data on extremes Double the number of exercises Many more color figures integrated throughout the text Updated computational aspects, including the latest version of WinBUGS, the new flexible spBayes software, and assorted R packages The Only Comprehensive Treatment of the Theory, Methods, and Software This second edition continues to provide a complete treatment of the theory, methods, and application of hierarchical modeling for spatial and spatiotemporal data. It tackles current challenges in handling this type of data, with increased emphasis on observational data, big data, and the upsurge of associated software tools. The authors also explore important application domains, including environmental science, forestry, public health, and real estate.
Categories: Mathematics

Handbook of Spatial Statistics

Handbook of Spatial Statistics

Time can be considered an additional coordinate and, thus, from a probabilistic
point of view, any spatio-temporal process can be ... all technical results on
spatial covariance functions (Chapter 2) and least-squares prediction or kriging (
Chapters 2 and 3) in Euclidean spaces ... Thereafter, we turn to covariance
structures for Gaussian processes that provide geostatistical models in the spirit
of Chapter 2.

Author: Alan E. Gelfand

Publisher: CRC Press

ISBN: 1420072889

Category: Mathematics

Page: 619

View: 830

Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. It takes a unified, integrated approach to the material, providing cross-references among chapters. The handbook begins with a historical introduction detailing the evolution of the field. It then focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and spatial point patterns. The book also contains a section on space–time work as well as a section on important topics that build upon earlier chapters. By collecting the major work in the field in one source, along with including an extensive bibliography, this handbook will assist future research efforts. It deftly balances theory and application, strongly emphasizes modeling, and introduces many real data analysis examples.
Categories: Mathematics

geoENV III Geostatistics for Environmental Applications

geoENV III     Geostatistics for Environmental Applications

Rainfall is an intermittent phenomenon in both space and time and it displays
large spatio-temporal variability. ... do not account for the digital elevation model
data, such as ordinary kriging, and the two most common techniques applied by ...

Author: Pascal Monestiez

Publisher: Springer Science & Business Media

ISBN: 0792371062

Category: Science

Page: 540

View: 102

This volume contains selected contributions from geoENV III - the Third European Conference on Geostatistics for Environmental Sciences, held in Avignon, France in November 2000. This third book of the geoENV series illustrates the new methodological developments in geostatistics, as applied to environmental sciences, which have occurred during the last two years. It also presents a wide variety of practical environmental applications which will be of interest to both researchers and practitioners. The book starts with two keynote papers on hydrogeology and on climatology and atmospheric pollution, followed by forty contributions. The content of this book is foremost practical. The editors have endeavored to compile a set of papers in which the readers could perceive how geostatistics is applied within environmental sciences. A few selected methodological and theoretical contributions are also included. The papers are organised in the following sections: Air Pollution / Climate; Environment; Health / Ecology; Hydrology; Methods; Soil Science / Site Remediation. presenting applications varying from delineation of hazardous areas, monitoring water quality, space-time modeling of sand beaches, areal rainfall estimation, air pollution monitoring, multivariate conditional simulation, soil texture analysis, fish abundance analysis, tree productivity index estimation, radionuclide migration analysis, wombling procedure, tracer tests modeling, direct sequential co-simulation to stochastic modeling of flow and transport. Audience: This publication will be of great interest and practical value to geostatisticians working both in academia and in industry.
Categories: Science

Temporal GIS

Temporal GIS

The book focuses on the development of advanced functions for field-based temporal geographical information systems (TGIS).

Author: George Christakos

Publisher: Springer Science & Business Media

ISBN: 9783642565403

Category: Mathematics

Page: 219

View: 168

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.
Categories: Mathematics