Map Data Processing


Book Description

Map Data Processing is a collection of papers from a NATO study on the same subject. This collection deals with the exchange of ideas and setting directions in research, particularly in pattern-recognition-, image-processing-, and computer-related issues. The papers discuss the usefulness of computer systems in geographical data processing, as well as the viability of scan digitization resulting from improvements in line thinning and vectorization. Automated spatial data integration can also be helpful in analyzing spatial data, data collection, capture methods, and data characteristics. Another paper addresses the application of the 8-point chain-encoded lineal map data to define more accurate algorithms found in many geographical and medical imagery. One paper considers how the same data used in monochromatic images can be realized for full colored, textured, realist terrain scenes. This book can be a valuable reference for workers involved in areas of geography, computer imaging, cartography, computer graphics, and remote sensing.




Cartography


Book Description

This Fourth Edition of Cartography: Visualization of Geospatial Data serves as an excellent introduction to general cartographic principles. It is an examination of the best ways to optimize the visualization and use of spatiotemporal data. Fully revised, it incorporates all the changes and new developments in the world of maps, such as OpenStreetMap and GPS (Global Positioning System) based crowdsourcing, and the use of new web mapping technology and adds new case studies and examples. Now printed in colour throughout, this edition provides students with the knowledge and skills needed to read and understand maps and mapping changes and offers professional cartographers an updated reference with the latest developments in cartography. Written by the leading scholars in cartography, this work is a comprehensive resource, perfect for senior undergraduate and graduate students taking courses in GIS (geographic information system) and cartography. New in This Edition: Provides an excellent introduction to general cartographic visualization principles through full-colour figures and images Addresses significant changes in data sources, technologies and methodologies, including the movement towards more open data sources and systems for mapping Includes new case studies and new examples for illustrating current trends in mapping Provides a societal and institutional framework in which future mapmakers are likely to operate, based on UN global development sustainability goals




Hot Working Guide


Book Description

A unique source book with flow stress data for hot working, processing maps with metallurgical interpretation and optimum processing conditions for metals, alloys, intermetallics, and metal matrix composites. The use of this book replaces the expensive and time consuming trial and error methods in process design and product development.




Geocomputation with R


Book Description

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/.




Data Mapping for Data Warehouse Design


Book Description

Data mapping in a data warehouse is the process of creating a link between two distinct data models' (source and target) tables/attributes. Data mapping is required at many stages of DW life-cycle to help save processor overhead; every stage has its own unique requirements and challenges. Therefore, many data warehouse professionals want to learn data mapping in order to move from an ETL (extract, transform, and load data between databases) developer to a data modeler role. Data Mapping for Data Warehouse Design provides basic and advanced knowledge about business intelligence and data warehouse concepts including real life scenarios that apply the standard techniques to projects across various domains. After reading this book, readers will understand the importance of data mapping across the data warehouse life cycle. - Covers all stages of data warehousing and the role of data mapping in each - Includes a data mapping strategy and techniques that can be applied to many situations - Based on the author's years of real-world experience designing solutions




Spatial Data Needs


Book Description




Hot Working Guide: A Compendium of Processing Maps, Second Edition


Book Description

Hot Working Guide: A Compendium of Processing Maps, Second Edition is a unique source book with flow stress data for hot working, processing maps with metallurgical interpretation and optimum processing conditions for metals, alloys, intermetallics, and metal matrix composites. The use of this book replaces the expensive and time consuming trial and error methods in process design and product development.




Data-Intensive Text Processing with MapReduce


Book Description

Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks




ggplot2


Book Description

Provides both rich theory and powerful applications Figures are accompanied by code required to produce them Full color figures




Applied Spatial Data Analysis with R


Book Description

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.