<P>In the five years since the publication of the first edition of <I><STRONG>Spatial Analysis: Statistics, Visualization, and Computational Methods</I></STRONG>, 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. <B>Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition</B> 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. </P><
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<P>Effective spatial analysis is an essential element of archaeological research; this book is a unique guide to choosing the appropriate technique, applying it correctly and understanding its implications both theoretically and practically. </P><P>Focusing...
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<p>This is a new edition of <em>the</em> accessible and student-friendly ''how to'' for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping....
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Readers will learn the essentials of spatial data handling using the open source software QGIS and be guided through the first steps in using the R programming language. The book includes the fundamentals of spatial data handling and analysis, working...
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