Spatial Analysis in Geology Using R

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Publisher : CRC Press
ISBN 13 : 1040041507
Total Pages : 452 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Spatial Analysis in Geology Using R by : Pedro M. Nogueira

Download or read book Spatial Analysis in Geology Using R written by Pedro M. Nogueira and published by CRC Press. This book was released on 2024-07-01 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: The integration of geology with data science disciplines, such as spatial statistics, remote sensing, and geographic information systems (GIS), has given rise to a shift in many natural sciences schools, pushing the boundaries of knowledge and enabling new discoveries in geological processes and earth systems. Spatial analysis of geological data can be used to identify patterns and trends in data, to map spatial relationships, and to model spatial processes. R is a consolidated and yet growing statistical programming language with increasing value in spatial analysis often replacing, with advantage, GIS tools. By providing a comprehensive guide for geologists to harness the power of spatial analysis in R, Spatial Analysis in Geology Using R serves as a tool in addressing real-world problems, such as natural resource management, environmental conservation, and hazard prediction and mitigation. Features: Provides a practical and accessible overview of spatial analysis in geology using R Organised in three independent and complementary parts: Introduction to R, Spatial Analysis with R, and Spatial Statistics and Modelling Applied approach with many detailed examples and case studies using real geological data Presents a collection of R packages that are useful in many geological situations Does not assume any prior knowledge of R; all code are explained in detail Supplemented by a website with all data, code, and examples Spatial Analysis in Geology Using R will be useful to any geological researcher who has acquired basic spatial analysis skills, often using GIS, and is interested in deepening those skills through the use of R. It could be used as a reference by applied researchers and analysts in public, private, or third-sector industries. It could also be used to teach a course on the topic to graduate students or for self-study.

Applied Spatial Data Analysis with R

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Publisher : Springer Science & Business Media
ISBN 13 : 1461476186
Total Pages : 414 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Applied Spatial Data Analysis with R by : Roger S. Bivand

Download or read book Applied Spatial Data Analysis with R written by Roger S. Bivand and published by Springer Science & Business Media. This book was released on 2013-06-21 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.

Spatial Modeling in GIS and R for Earth and Environmental Sciences

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Author :
Publisher : Elsevier
ISBN 13 : 0128156953
Total Pages : 800 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Spatial Modeling in GIS and R for Earth and Environmental Sciences by : Hamid Reza Pourghasemi

Download or read book Spatial Modeling in GIS and R for Earth and Environmental Sciences written by Hamid Reza Pourghasemi and published by Elsevier. This book was released on 2019-01-18 with total page 800 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Spatial Analysis with R

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Publisher : CRC Press
ISBN 13 : 100017347X
Total Pages : 304 pages
Book Rating : 4.0/5 (1 download)

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Book Synopsis Spatial Analysis with R by : Tonny J. Oyana

Download or read book Spatial Analysis with R written by Tonny J. Oyana and published by CRC Press. This book was released on 2020-08-31 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes. New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data mining This second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.

Geocomputation with R

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Publisher : CRC Press
ISBN 13 : 1351396900
Total Pages : 354 pages
Book Rating : 4.3/5 (513 download)

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Book Synopsis Geocomputation with R by : Robin Lovelace

Download or read book Geocomputation with R written by Robin Lovelace and published by CRC Press. This book was released on 2019-03-22 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geocomputation with R is for people who want to analyze, visualize and model geographic data with open source software. It is based on R, a statistical programming language that has powerful data processing, visualization, and geospatial capabilities. The book equips you with the knowledge and skills to tackle a wide range of issues manifested in geographic data, including those with scientific, societal, and environmental implications. This book will interest people from many backgrounds, especially Geographic Information Systems (GIS) users interested in applying their domain-specific knowledge in a powerful open source language for data science, and R users interested in extending their skills to handle spatial data. The book is divided into three parts: (I) Foundations, aimed at getting you up-to-speed with geographic data in R, (II) extensions, which covers advanced techniques, and (III) applications to real-world problems. The chapters cover progressively more advanced topics, with early chapters providing strong foundations on which the later chapters build. Part I describes the nature of spatial datasets in R and methods for manipulating them. It also covers geographic data import/export and transforming coordinate reference systems. Part II represents methods that build on these foundations. It covers advanced map making (including web mapping), "bridges" to GIS, sharing reproducible code, and how to do cross-validation in the presence of spatial autocorrelation. Part III applies the knowledge gained to tackle real-world problems, including representing and modeling transport systems, finding optimal locations for stores or services, and ecological modeling. Exercises at the end of each chapter give you the skills needed to tackle a range of geospatial problems. Solutions for each chapter and supplementary materials providing extended examples are available at https://geocompr.github.io/geocompkg/articles/.

An Introduction to Spatial Data Analysis

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Publisher : Pelagic Publishing Ltd
ISBN 13 : 1784272140
Total Pages : 372 pages
Book Rating : 4.7/5 (842 download)

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Book Synopsis An Introduction to Spatial Data Analysis by : Martin Wegmann

Download or read book An Introduction to Spatial Data Analysis written by Martin Wegmann and published by Pelagic Publishing Ltd. This book was released on 2020-09-14 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a book about how ecologists can integrate remote sensing and GIS in their research. It will allow readers to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. An Introduction to Spatial Data Analysis introduces spatial data handling using the open source software Quantum GIS (QGIS). In addition, readers will be guided through their first steps in the R programming language. The authors explain the fundamentals of spatial data handling and analysis, empowering the reader to turn data acquired in the field into actual spatial data. Readers will learn to process and analyse spatial data of different types and interpret the data and results. After finishing this book, readers will be able to address questions such as “What is the distance to the border of the protected area?”, “Which points are located close to a road?”, “Which fraction of land cover types exist in my study area?” using different software and techniques. This book is for novice spatial data users and does not assume any prior knowledge of spatial data itself or practical experience working with such data sets. Readers will likely include student and professional ecologists, geographers and any environmental scientists or practitioners who need to collect, visualize and analyse spatial data. The software used is the widely applied open source scientific programs QGIS and R. All scripts and data sets used in the book will be provided online at book.ecosens.org. This book covers specific methods including: what to consider before collecting in situ data how to work with spatial data collected in situ the difference between raster and vector data how to acquire further vector and raster data how to create relevant environmental information how to combine and analyse in situ and remote sensing data how to create useful maps for field work and presentations how to use QGIS and R for spatial analysis how to develop analysis scripts

Spatial Analysis

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Publisher : CRC Press
ISBN 13 : 1498707645
Total Pages : 316 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Spatial Analysis by : Tonny J. Oyana

Download or read book Spatial Analysis written by Tonny J. Oyana and published by CRC Press. This book was released on 2015-07-28 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Geographic Data Analysis Using R

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Author :
Publisher : Springer Nature
ISBN 13 : 9819740223
Total Pages : 238 pages
Book Rating : 4.8/5 (197 download)

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Book Synopsis Geographic Data Analysis Using R by : Xindong He

Download or read book Geographic Data Analysis Using R written by Xindong He and published by Springer Nature. This book was released on with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Spatial Microsimulation with R

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Publisher : CRC Press
ISBN 13 : 131536316X
Total Pages : 260 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Spatial Microsimulation with R by : Robin Lovelace

Download or read book Spatial Microsimulation with R written by Robin Lovelace and published by CRC Press. This book was released on 2017-09-07 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generate and Analyze Multi-Level Data Spatial microsimulation involves the generation, analysis, and modeling of individual-level data allocated to geographical zones. Spatial Microsimulation with R is the first practical book to illustrate this approach in a modern statistical programming language. Get Insight into Complex Behaviors The book progresses from the principles underlying population synthesis toward more complex issues such as household allocation and using the results of spatial microsimulation for agent-based modeling. This equips you with the skills needed to apply the techniques to real-world situations. The book demonstrates methods for population synthesis by combining individual and geographically aggregated datasets using the recent R packages ipfp and mipfp. This approach represents the "best of both worlds" in terms of spatial resolution and person-level detail, overcoming issues of data confidentiality and reproducibility. Implement the Methods on Your Own Data Full of reproducible examples using code and data, the book is suitable for students and applied researchers in health, economics, transport, geography, and other fields that require individual-level data allocated to small geographic zones. By explaining how to use tools for modeling phenomena that vary over space, the book enhances your knowledge of complex systems and empowers you to provide evidence-based policy guidance.

Analyzing Baseball Data with R

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Publisher : CRC Press
ISBN 13 : 104009712X
Total Pages : 418 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Analyzing Baseball Data with R by : Jim Albert

Download or read book Analyzing Baseball Data with R written by Jim Albert and published by CRC Press. This book was released on 2024-08-01 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Our community has continued to grow exponentially, thanks to those who inspire the next generation. And inspiring the next generation is what the authors of Analyzing Baseball Data with R are doing. They are setting the career path for still thousands more. We all need some sort of kickstart to take that first or second step. You may be a beginner R coder, but you need access to baseball data. How do you access this data, how do you manipulate it, how do you analyze it? This is what this book does for you. But it does more, by doing what sabermetrics does best: it asks baseball questions. Throughout the book, baseball questions are asked, some straightforward, and others more thought-provoking.” From the Foreword by Tom Tango Analyzing Baseball Data with R Third Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the analysis steps, from importing the data to transforming them into an appropriate format to visualizing the data via graphs to performing a statistical analysis. The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the ggplot2 graphics functions and employ a tidyverse-friendly workflow throughout. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, catcher framing, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and launch angles and exit velocities. All the datasets and R code used in the text are available for download online. New to the third edition is the revised R code to make use of new functions made available through the tidyverse. The third edition introduces three chapters of new material, focusing on communicating results via presentations using the Quarto publishing system, web applications using the Shiny package, and working with large data files. An online version of this book is hosted at https://beanumber.github.io/abdwr3e/.

Statistical Methods for Spatial Data Analysis

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Publisher : CRC Press
ISBN 13 : 020349198X
Total Pages : 584 pages
Book Rating : 4.2/5 (34 download)

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Book Synopsis Statistical Methods for Spatial Data Analysis by : Oliver Schabenberger

Download or read book Statistical Methods for Spatial Data Analysis written by Oliver Schabenberger and published by CRC Press. This book was released on 2004-12-20 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes. Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.

Spatial Relationships Between Two Georeferenced Variables

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Publisher : Springer Nature
ISBN 13 : 3030566811
Total Pages : 194 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Spatial Relationships Between Two Georeferenced Variables by : Ronny Vallejos

Download or read book Spatial Relationships Between Two Georeferenced Variables written by Ronny Vallejos and published by Springer Nature. This book was released on 2020-09-22 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Geostatistics for Compositional Data with R

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Publisher : Springer Nature
ISBN 13 : 303082568X
Total Pages : 275 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Geostatistics for Compositional Data with R by : Raimon Tolosana-Delgado

Download or read book Geostatistics for Compositional Data with R written by Raimon Tolosana-Delgado and published by Springer Nature. This book was released on 2021-11-19 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a guided approach to the geostatistical modelling of compositional spatial data. These data are data in proportions, percentages or concentrations distributed in space which exhibit spatial correlation. The book can be divided into four blocks. The first block sets the framework and provides some background on compositional data analysis. Block two introduces compositional exploratory tools for both non-spatial and spatial aspects. Block three covers all necessary facets of multivariate spatial prediction for compositional data: variogram modelling, cokriging and validation. Finally, block four details strategies for simulation of compositional data, including transformations to multivariate normality, Gaussian cosimulation, multipoint simulation of compositional data, and common postprocessing techniques, valid for both Gaussian and multipoint methods. All methods are illustrated via applications to two types of data sets: one a large-scale geochemical survey, comprised of a full suite of geochemical variables, and the other from a mining context, where only the elements of greatest importance are considered. R codes are included for all aspects of the methodology, encapsulated in the R package "gmGeostats", available in CRAN.

Local Models for Spatial Analysis

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Publisher : CRC Press
ISBN 13 : 0203022823
Total Pages : 260 pages
Book Rating : 4.2/5 (3 download)

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Book Synopsis Local Models for Spatial Analysis by : Christopher D. Lloyd

Download or read book Local Models for Spatial Analysis written by Christopher D. Lloyd and published by CRC Press. This book was released on 2006-10-25 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: In both the physical and social sciences, there are now available large spatial data sets with detailed local information. Global models for analyzing these data are not suitable for investigating local variations; consequently, local models are the subject of much recent research. Collecting a variety of models into a single reference, Local Models for Spatial Analysis explains in detail a variety of approaches for analyzing univariate and multivariate spatial data. Different models make use of data in unique ways, and this book offers perspectives on various definitions of what constitutes “local,” varying spatial scales, and nonstationary models. The author discusses analyses of single variables on grids, multiple variables, deterministic approaches to spatial prediction, geostatistical prediction, and point patterns. He uses numerous worked examples, illustrations, and case studies to shed light on issues involved in implementing the concepts in practice, and makes use of physical and social science data sets. In each chapter, the book follows a consistent format that introduces global approaches followed by corresponding local approaches, providing an assessment of the suitability of various methods in particular situations. Combining a valuable array of tools for GIScience and GISystems, Local Models for Spatial Analysis guides you in selecting and applying the most appropriate model for a given purpose and set of data.

Spatial Point Patterns

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Publisher : CRC Press
ISBN 13 : 1482210215
Total Pages : 830 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Spatial Point Patterns by : Adrian Baddeley

Download or read book Spatial Point Patterns written by Adrian Baddeley and published by CRC Press. This book was released on 2015-11-11 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Exploring Spatial Scale in Geography

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Publisher : John Wiley & Sons
ISBN 13 : 1119971357
Total Pages : 274 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Exploring Spatial Scale in Geography by : Christopher D. Lloyd

Download or read book Exploring Spatial Scale in Geography written by Christopher D. Lloyd and published by John Wiley & Sons. This book was released on 2014-05-12 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring Spatial Scale in Geography provides a conceptual and practical guide to issues of spatial scale in all areas of the physical and social sciences. Scale is at the heart of geography and other spatial sciences. Whether dealing with geomorphological processes, population movements or meteorology, a consideration of spatial scale is vital. Exploring Spatial Scale in Geography takes a practical approach with a core focus on real world problems and potential solutions. Links are made to appropriate software environments with an associated website providing access to guidance material which outlines how particular problems can be approached using popular GIS and spatial data analysis software. This book offers alternative definitions of spatial scale, presents approaches for exploring spatial scale and makes use of a wide variety of case studies in the physical and social sciences to demonstrate key concepts, making it a key resource for anyone who makes use of geographical information.

Spatial Analysis Using Big Data

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Publisher : Academic Press
ISBN 13 : 0128131322
Total Pages : 304 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Spatial Analysis Using Big Data by : Yoshiki Yamagata

Download or read book Spatial Analysis Using Big Data written by Yoshiki Yamagata and published by Academic Press. This book was released on 2019-11-03 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others. - Reviews some of the most powerful and challenging modern methods to study big data problems in spatial science - Provides computer codes written in R, MATLAB and Python to help implement methods - Applies these methods to common problems observed in urban and regional economics