-PDF Download- Spatial Choices And Processes EBOOK

Spatial Choices and Processes

Author: M.M. Fischer

Publisher: Elsevier

Published: 2013-10-22

Total Pages: 392

ISBN-13: 1483290883

Spatial decisions and processes are fundamental to the understanding of spatial structure. In the earlier stages of spatial analysis proposed explanations were typically on the aggregate, phenomenological level. Now a new field has evolved and matured which calls for a deeper understanding of spatial structure with a particular emphasis on spatial decisions and processes. The present volume serves as a guide and as an anthology by discussing a wide variety of new modelling approaches, techniques and issues related to spatial decision and processes and drawing these seemingly disparate, but interlocking parts together.

Stochastic Geometry, Spatial Statistics and Random Fields

Author: Volker Schmidt

Publisher: Springer

Published: 2014-10-24

Total Pages: 484

ISBN-13: 3319100645

DOWNLOAD EBOOK →

This volume is an attempt to provide a graduate level introduction to various aspects of stochastic geometry, spatial statistics and random fields, with special emphasis placed on fundamental classes of models and algorithms as well as on their applications, e.g. in materials science, biology and genetics. This book has a strong focus on simulations and includes extensive codes in Matlab and R which are widely used in the mathematical community. It can be seen as a continuation of the recent volume 2068 of Lecture Notes in Mathematics, where other issues of stochastic geometry, spatial statistics and random fields were considered with a focus on asymptotic methods.

Spatial Interaction Processes

Author: Elizabeth Ann Janes

Publisher:

Published: 1974

Total Pages: 232

ISBN-13:

DOWNLOAD EBOOK →

Case Studies in Spatial Point Process Modeling

Author: Adrian Baddeley

Publisher: Springer Science & Business Media

Published: 2006-03-03

Total Pages: 312

ISBN-13: 0387311440

DOWNLOAD EBOOK →

Point process statistics is successfully used in fields such as material science, human epidemiology, social sciences, animal epidemiology, biology, and seismology. Its further application depends greatly on good software and instructive case studies that show the way to successful work. This book satisfies this need by a presentation of the spatstat package and many statistical examples. Researchers, spatial statisticians and scientists from biology, geosciences, materials sciences and other fields will use this book as a helpful guide to the application of point process statistics. No other book presents so many well-founded point process case studies. From the reviews: "For those interested in analyzing their spatial data, the wide variatey of examples and approaches here give a good idea of the possibilities and suggest reasonable paths to explore." Michael Sherman for the Journal of the American Statistical Association, December 2006

Spatial Relationships Between Two Georeferenced Variables

Author: Ronny Vallejos

Publisher: Springer Nature

Published: 2020-09-22

Total Pages: 194

ISBN-13: 3030566811

DOWNLOAD EBOOK →

This book offers essential, systematic information on the assessment of the spatial association between two processes from a statistical standpoint. Divided into eight chapters, the book begins with preliminary concepts, mainly concerning spatial statistics. The following seven chapters focus on the methodologies needed to assess the correlation between two or more processes; from theory introduced 35 years ago, to techniques that have only recently been published. Furthermore, each chapter contains a section on R computations to explore how the methodology works with real data. References and a list of exercises are included at the end of each chapter. The assessment of the correlation between two spatial processes has been tackled from several different perspectives in a variety of applications fields. In particular, the problem of testing for the existence of spatial association between two georeferenced variables is relevant for posterior modeling and inference. One evident application in this context is the quantification of the spatial correlation between two images (processes defined on a rectangular grid in a two-dimensional space). From a statistical perspective, this problem can be handled via hypothesis testing, or by using extensions of the correlation coefficient. In an image-processing framework, these extensions can also be used to define similarity indices between images.

Stochastic Geometry

Author: W. Weil

Publisher: Springer

Published: 2006-10-26

Total Pages: 302

ISBN-13: 3540381759

DOWNLOAD EBOOK →

Stochastic Geometry is the mathematical discipline which studies mathematical models for random geometric structures. This book collects lectures presented at the CIME summer school in Martina Franca in September 2004. The main lecturers covered Spatial Statistics, Random Points, Integral Geometry and Random Sets. These are complemented by two additional contributions on Random Mosaics and Crystallization Processes. The book presents a comprehensive and up-to-date description of important aspects of Stochastic Geometry.

Spatial Modeling in GIS and R for Earth and Environmental Sciences

Author: Hamid Reza Pourghasemi

Publisher: Elsevier

Published: 2019-01-18

Total Pages: 798

ISBN-13: 0128156953

DOWNLOAD EBOOK →

Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography Provides an overview, methods and case studies for each application Expresses concepts and methods at an appropriate level for both students and new users to learn by example

Classical and Spatial Stochastic Processes

Author: Rinaldo B. Schinazi

Publisher: Springer

Published: 2014-09-27

Total Pages: 271

ISBN-13: 1493918699

DOWNLOAD EBOOK →

The revised and expanded edition of this textbook presents the concepts and applications of random processes with the same illuminating simplicity as its first edition, but with the notable addition of substantial modern material on biological modeling. While still treating many important problems in fields such as engineering and mathematical physics, the book also focuses on the highly relevant topics of cancerous mutations, influenza evolution, drug resistance, and immune response. The models used elegantly apply various classical stochastic models presented earlier in the text, and exercises are included throughout to reinforce essential concepts. The second edition of Classical and Spatial Stochastic Processes is suitable as a textbook for courses in stochastic processes at the advanced-undergraduate and graduate levels, or as a self-study resource for researchers and practitioners in mathematics, engineering, physics, and mathematical biology. Reviews of the first edition: An appetizing textbook for a first course in stochastic processes. It guides the reader in a very clever manner from classical ideas to some of the most interesting modern results. ... All essential facts are presented with clear proofs, illustrated by beautiful examples. ... The book is well organized, has informative chapter summaries, and presents interesting exercises. The clear proofs are concentrated at the ends of the chapters making it easy to find the results. The style is a good balance of mathematical rigorosity and user-friendly explanation. —Biometric Journal This small book is well-written and well-organized. ... Only simple results are treated ... but at the same time many ideas needed for more complicated cases are hidden and in fact very close. The second part is a really elementary introduction to the area of spatial processes. ... All sections are easily readable and it is rather tentative for the reviewer to learn them more deeply by organizing a course based on this book. The reader can be really surprised seeing how simple the lectures on these complicated topics can be. At the same time such important questions as phase transitions and their properties for some models and the estimates for certain critical values are discussed rigorously. ... This is indeed a first course on stochastic processes and also a masterful introduction to some modern chapters of the theory. —Zentralblatt Math

Spatial Econometrics: Methods and Models

Author: L. Anselin

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 295

ISBN-13: 9401577994

DOWNLOAD EBOOK →

Spatial econometrics deals with spatial dependence and spatial heterogeneity, critical aspects of the data used by regional scientists. These characteristics may cause standard econometric techniques to become inappropriate. In this book, I combine several recent research results to construct a comprehensive approach to the incorporation of spatial effects in econometrics. My primary focus is to demonstrate how these spatial effects can be considered as special cases of general frameworks in standard econometrics, and to outline how they necessitate a separate set of methods and techniques, encompassed within the field of spatial econometrics. My viewpoint differs from that taken in the discussion of spatial autocorrelation in spatial statistics - e.g., most recently by Cliff and Ord (1981) and Upton and Fingleton (1985) - in that I am mostly concerned with the relevance of spatial effects on model specification, estimation and other inference, in what I caIl a model-driven approach, as opposed to a data-driven approach in spatial statistics. I attempt to combine a rigorous econometric perspective with a comprehensive treatment of methodological issues in spatial analysis.

Models of Spatial Processes

Author: Arthur Getis

Publisher: Cambridge University Press

Published: 2008-12-11

Total Pages: 0

ISBN-13: 9780521103541

DOWNLOAD EBOOK →

This book approaches the study of patterns by emphasising the processes responsible for them; it emphasises the logical format of process-to-pattern rather than the more wasteful pattern-to-process approach. The concern is primarily with two-dimensional surfaces, which is the way most maps are used for analysis. The material is organised into sections on process models responsible for point patterns, for line patterns and then for area patterns. It represents a synthesis of the work done on patterns in a number of fields and a large literature is reviewed in the process of the synthesis. In many respects this book represents a translation of complex mathematical materials into a readable and relatively simple verbal approach to the subject and thus brings the more sophisticated aspects to a larger number of students than has been done before. The reader need only have an elementary background in statistics. The basic probability theory required by the text is given in an appendix.