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Author: Boris Kovalerchuk
Publisher: Springer Science & Business Media
ISBN: 1402029586
Category : Computers
Languages : en
Pages : 582
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Book Description
Advanced visual analysis and problem solving has been conducted successfully for millennia. The Pythagorean Theorem was proven using visual means more than 2000 years ago. In the 19th century, John Snow stopped a cholera epidemic in London by proposing that a specific water pump be shut down. He discovered that pump by visually correlating data on a city map. The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making. This is the first book to focus on visual decision making and problem solving in general with specific applications in the geospatial domain - combining theory with real-world practice. The book is unique in its integration of modern symbolic and visual approaches to decision making and problem solving. As such, it ties together much of the monograph and textbook literature in these emerging areas. This book contains 21 chapters that have been grouped into five parts: (1) visual problem solving and decision making, (2) visual and heterogeneous reasoning, (3) visual correlation, (4) visual and spatial data mining, and (5) visual and spatial problem solving in geospatial domains. Each chapter ends with a summary and exercises. The book is intended for professionals and graduate students in computer science, applied mathematics, imaging science and Geospatial Information Systems (GIS). In addition to being a state-of-the-art research compilation, this book can be used a text for advanced courses on the subjects such as modeling, computer graphics, visualization, image processing, data mining, GIS, and algorithm analysis.
Author: Boris Kovalerchuk
Publisher: Springer Science & Business Media
ISBN: 1402029586
Category : Computers
Languages : en
Pages : 582
Get Book
Book Description
Advanced visual analysis and problem solving has been conducted successfully for millennia. The Pythagorean Theorem was proven using visual means more than 2000 years ago. In the 19th century, John Snow stopped a cholera epidemic in London by proposing that a specific water pump be shut down. He discovered that pump by visually correlating data on a city map. The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making. This is the first book to focus on visual decision making and problem solving in general with specific applications in the geospatial domain - combining theory with real-world practice. The book is unique in its integration of modern symbolic and visual approaches to decision making and problem solving. As such, it ties together much of the monograph and textbook literature in these emerging areas. This book contains 21 chapters that have been grouped into five parts: (1) visual problem solving and decision making, (2) visual and heterogeneous reasoning, (3) visual correlation, (4) visual and spatial data mining, and (5) visual and spatial problem solving in geospatial domains. Each chapter ends with a summary and exercises. The book is intended for professionals and graduate students in computer science, applied mathematics, imaging science and Geospatial Information Systems (GIS). In addition to being a state-of-the-art research compilation, this book can be used a text for advanced courses on the subjects such as modeling, computer graphics, visualization, image processing, data mining, GIS, and algorithm analysis.
Author: Tonny J. Oyana
Publisher: CRC Press
ISBN: 100017347X
Category : Mathematics
Languages : en
Pages : 281
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Book Description
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.
Author: Chris Brunsdon
Publisher: SAGE
ISBN: 1473911192
Category : Social Science
Languages : en
Pages : 475
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Book Description
"In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using ′out of the box′ software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical ′how to′ guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R.
Author: S Fotheringham
Publisher: CRC Press
ISBN: 9780203221563
Category : Technology & Engineering
Languages : en
Pages : 298
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Book Description
Geographic information systems represent an exciting and rapidly expanding technology via which spatial data may be captured, stored, retrieved, displayed, manipulated and analysed. Applications of this technology include detailed inventories of land use parcels. Spatial patterns of disease, geodemographics, environmental management and macroscale inventories of global resources. The impetus for this book is the relative lack of research into the integration of spatial analysis and GIS, and the potential benefits in developing such an integration. From a GIS perspective, there is an increasing demand for systems that do something other than display and organize data. From a spatial analytical perspective, there are advantages to linking statistical methods and mathematical models to the database and display capabilities of a GIS. Although the GIS may not be absolutely necessary for spatial analysis, it can facilitate such an analysis and moreover provide insights that might otherwise have been missed. The contributions to the book tell us where we are and where we ought to be going. It suggests that the integration of spatial analysis and GIS will stimulate interest in quantitative spatial science, particularly exploratory and visual types of analysis and represents a unique statement of the state-of-the-art issues in integration and interface.
Author: Menno-Jan Kraak
Publisher: Routledge
ISBN: 1317903110
Category : Technology & Engineering
Languages : en
Pages : 211
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Book Description
This revised and updated edition integrates the latest in modern technology with traditional cartographic principles. While providing a solid conceptual foundation in cartographic methodology, the text also introduces the very latest advances that have greatly influenced cartographic techniques. The new edition reflects the increasing importance of cartography as the basis for further geographical study, the text has been updated throughout and chapters on the latest developments in cartography have been integrated. There is also a more widespread emphasis on multimedia and the web.
Author: Boris Kovalerchuk
Publisher: Springer Science & Business Media
ISBN: 1402029586
Category : Computers
Languages : en
Pages : 576
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Book Description
Advanced visual analysis and problem solving has been conducted successfully for millennia. The Pythagorean Theorem was proven using visual means more than 2000 years ago. In the 19th century, John Snow stopped a cholera epidemic in London by proposing that a specific water pump be shut down. He discovered that pump by visually correlating data on a city map. The goal of this book is to present the current trends in visual and spatial analysis for data mining, reasoning, problem solving and decision-making. This is the first book to focus on visual decision making and problem solving in general with specific applications in the geospatial domain - combining theory with real-world practice. The book is unique in its integration of modern symbolic and visual approaches to decision making and problem solving. As such, it ties together much of the monograph and textbook literature in these emerging areas. This book contains 21 chapters that have been grouped into five parts: (1) visual problem solving and decision making, (2) visual and heterogeneous reasoning, (3) visual correlation, (4) visual and spatial data mining, and (5) visual and spatial problem solving in geospatial domains. Each chapter ends with a summary and exercises. The book is intended for professionals and graduate students in computer science, applied mathematics, imaging science and Geospatial Information Systems (GIS). In addition to being a state-of-the-art research compilation, this book can be used a text for advanced courses on the subjects such as modeling, computer graphics, visualization, image processing, data mining, GIS, and algorithm analysis.
Author: Tonny J. Oyana
Publisher: CRC Press
ISBN: 1498707645
Category : Mathematics
Languages : en
Pages : 316
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Book Description
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
Author: Paula Moraga
Publisher: CRC Press
ISBN: 1000732150
Category : Medical
Languages : en
Pages : 217
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Book Description
Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulate and transform point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fit and interpret spatial and spatio-temporal models with the Integrated Nested Laplace Approximations (INLA) and the Stochastic Partial Differential Equation (SPDE) approaches, Create interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policy makers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modeling and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.
Author: Marie-Josée Fortin
Publisher: Cambridge University Press
ISBN: 9780521804349
Category : Mathematics
Languages : en
Pages : 386
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Book Description
An overview of the wide range of spatial statistics available to analyse ecological data.
Author: Ian Hodder
Publisher: Cambridge University Press
ISBN: 9780521210805
Category : Social Science
Languages : en
Pages : 292
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Book Description
This 1976 text is a pioneering study in the applications to archaeology of modern statistical and quantitative techniques. The authors show how these techniques, when sensitively employed, can dramatically extend and refine the information presented in distribution maps and other analyses of spatial relationships. Techniques of interpretation 'by inspection' can now be made more powerful and rigorous; at the same time interest has turned from the examination of such sites and artefacts as 'things' to the spatial relationships between such things, their relationships to one another and to landscape features, soils and other resources. This book was the first to apply the available techniques systematically to the special problems and interests of archaeologists. It also demonstrates to geographers and other social scientists who may be familiar with analogous applications in their own fields the exciting interdisciplinary developments this facilitates, for example in studies of exchange networks, trade and settlement patterns, and cultural history.
