Random Patterns And Structures In Spatial Data
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Random Patterns And Structures In Spatial Data Through Marked Gibbs Point Processes With Interactions
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Author : Radu S. Stoica
language : en
Publisher:
Release Date : 2025
Random Patterns And Structures In Spatial Data Through Marked Gibbs Point Processes With Interactions written by Radu S. Stoica and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Gibbs point processes categories.
"The book presents a general mathematical framework able to detect and to characterize, from a morphological and statistical perspective, patterns hidden in spatial data. The mathematical tool employed is a Gibbs point process with interaction, which permits us to reduce the complexity of the pattern. It presents the framework, step by step, in three major parts: modeling, simulation, and inference. Each of these parts contains a theoretical development followed by applications and examples"--
Spatial Analysis
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Author : Tonny J. Oyana
language : en
Publisher: CRC Press
Release Date : 2015-07-28
Spatial Analysis written by Tonny J. Oyana and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-07-28 with Mathematics categories.
An introductory text for the next generation of geospatial analysts and data scientists, Spatial Analysis: Statistics, Visualization, and Computational Methods focuses on the fundamentals of spatial analysis using traditional, contemporary, and computational methods. Outlining both non-spatial and spatial statistical concepts, the authors present p
Statistical Methods For Geography
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Author : Peter Rogerson
language : en
Publisher: SAGE
Release Date : 2019-12-04
Statistical Methods For Geography written by Peter Rogerson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-04 with Reference categories.
Statistical Methods for Geography is the essential introduction for geography students looking to fully understand and apply key statistical concepts and techniques. Now in its fifth edition, this text is an accessible statistics ‘101’ focused on student learning, and includes definitions, examples, and exercises throughout. Fully integrated with online self-assessment exercises and video overviews, it explains everything required to get full credits for any undergraduate statistics module. The fifth edition of this bestselling text includes: · Coverage of descriptive statistics, probability, inferential statistics, hypothesis testing and sampling, variance, correlation, regression analysis, spatial patterns, spatial data reduction using factor analysis and cluster analysis. · New examples from physical geography and additional real-world examples. · Updated in-text and online exercises along with downloadable datasets. This is the only text you’ll need for undergraduate courses in statistical analysis, statistical methods, and quantitative geography.
Spatial Point Patterns
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Author : Adrian Baddeley
language : en
Publisher: CRC Press
Release Date : 2015-11-11
Spatial Point Patterns written by Adrian Baddeley and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-11 with Mathematics categories.
Modern Statistical Methodology and Software for Analyzing Spatial Point PatternsSpatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on th
Statistical Analysis With Arcview Gis
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Author : Jay Lee
language : en
Publisher: John Wiley & Sons
Release Date : 2001-05-16
Statistical Analysis With Arcview Gis written by Jay Lee and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-05-16 with Science categories.
Statistical analysis of geographic data has been greatly enhanced in recent years with the advent of Geographical Information Systems (GIS) software. Yet GIS users have struggles to synchronize their applications of spatial information with practical, quantitative statistics. ArcView, one of the most powerful GIS-compatible systems, has become the most popular software among geographers precisely because of its capacity for spatial-quantitative synthesis. Now geographers Jay Lee and David Wong have produced the first handbook for applied ArcView use, bringing the theoretical underpinnings of classical statistics into the earth science environment. Employing points, lines, and polygons to model real-world geographic forms, this easy-to-use resource provides geographers with a valuable bridge between theory and the software necessary to apply it. It contains sections on point distribution, point pattern analysis, linear features, network analysis, and spatial autocorrelation analysis. Statistical Analysis with ArcView GIS also features: Examples that show steps of statistical calculations-as well as ways to interpret the results. More than 100 illustrations, including statistical charts, maps, and ArcView screen captures. Helpful end-of-chapter references. Suitable for professionals as well as students of geography, this book is an important tool for anyone involved in the statistical analysis of GIS data.
Handbook Of Environmental And Ecological Statistics
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Author : Alan E. Gelfand
language : en
Publisher: CRC Press
Release Date : 2019-01-15
Handbook Of Environmental And Ecological Statistics written by Alan E. Gelfand and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-15 with Mathematics categories.
This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.
Spatial Data Analysis With R
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Author : Danlin Yu
language : en
Publisher: SAGE Publications
Release Date : 2025-02-27
Spatial Data Analysis With R written by Danlin Yu and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Social Science categories.
This is an introduction for social science students to the growing field of spatial data analysis using the R platform. The text assumes no prior knowledge of either, beyond the contents of an introductory statistics course. It uses the open-source software R, and relevant spatial data analysis packages, to provide practical guidance of how to conduct spatial data analysis with readers′ own data sets. The book first briefly introduces students to R, covers some basic concepts in statistical data analysis, and then focuses on discussing the central ideas of spatial data analysis. All the discussions are supported with R scripts so that students can work on their own and produce results that the book helps interpret. Each chapter ends with review questions to test understanding. The book is suited for upper-level undergraduate social science students and graduate students, and other social scientists who are interested in analyzing their spatial data with R. A companion website for the book at https://edge.sagepub.com/yu includes R code and data for students to replicate the examples in the book. The password-protected instructor side of the site includes exercises and answers which can be set for homework.
Multiple Point Geostatistics
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Author : Professor Gregoire Mariethoz
language : en
Publisher: John Wiley & Sons
Release Date : 2014-12-31
Multiple Point Geostatistics written by Professor Gregoire Mariethoz and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-31 with Science categories.
This book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images. Multiple-point geostatistics aims at bridging the gap between physical modelling/realism and spatio-temporal stochastic modelling. The book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory and stochastic modelling based on training images, where random function theory is not always used. Part II covers in detail various algorithms and methodologies starting from basic building blocks in statistical science and computer science. Concepts such as non-stationary and multi-variate modeling, consistency between data and model, the construction of training images and inverse modelling are treated. Part III covers three example application areas, namely, reservoir modelling, mineral resources modelling and climate model downscaling. This book will be an invaluable reference for students, researchers and practitioners of all areas of the Earth Sciences where forecasting based on spatio-temporal data is performed.
Spatial Uncertainty In Ecology
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Author : Carolyn T. Hunsaker
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-01
Spatial Uncertainty In Ecology written by Carolyn T. Hunsaker and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-01 with Science categories.
The huge growth in the use of geographic information systems, remote sensing platforms and spatial databases have made accurate spatial data more available for ecological and environmental models. Unfortunately, there has been too little analysis of the appropriate use of this data and the role of uncertainty in resulting ecological models. This is the first book to take an ecological perspective on uncertainty in spatial data. It applies principles and techniques from geography and other disciplines to ecological research. It brings the tools of cartography, cognition, spatial statistics, remote sensing and computer sciences to the ecologist using spatial data. After describing the uses of spatial data in ecological research, the authors discuss how to account for the effects of uncertainty in various methods of analysis. Carolyn T. Hunsaker is a research ecologist in the USDA Forest Service in Fresno, California. Michael F. Goodchild is Professor of Geography at the University of California, Santa Barbara. Mark A. Friedl is Assistant Professor in the Department of Geography and the Center for Remote Sensing at Boston University. Ted J. Case is Professor of Biology at the University of California, San Diego.
Machine Learning For Spatial Environmental Data
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Author : Mikhail Kanevski
language : en
Publisher: CRC Press
Release Date : 2009-06-09
Machine Learning For Spatial Environmental Data written by Mikhail Kanevski and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-09 with Computers categories.
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 lea