This engaging text provides a solid introduction to mapmaking in the era of cloud computing. It takes students through both the concepts and technology of modern cartography, geographic information systems (GIS), and Web-based mapping. Conceptual chapters delve into the meaning of maps and how they are developed, covering such topics as map layers, GIS tools, mobile mapping, and map animation. Methods chapters take a learn-by-doing approach to help students master application programming interfaces and build other technical skills for creating maps and making them available on the Internet. The companion website offers invaluable supplementary materials for instructors and students.˜ ˜ Pedagogical features:˜ End-of-chapter summaries, review questions, and exercises.˜ Extensive graphics illustrating the concepts and procedures. Downloadable PowerPoints for each chapter. Downloadable code files (where applicable) for the exercises.

Mapping by Design: A Guide to ArcGIS Maps for Adobe Creative Cloud serves as a practical guide for all mapmakers who want to create compelling maps using Adobe(R) Illustrator(R).

Thematic Mapping: 101 Inspiring Ways to Visualise Empirical Data explores the rich diversity of thematic mapping using a single dataset from the 2016 US presidential election.

The Internet of Things offers massive societal and economic opportunities while at the same time significant challenges, not least the delivery and management of the technical infrastructure underpinning it, the deluge of data generated from it, ensuring privacy and security, and capturing value from it. This Open Access Pivot explores these challenges, presenting the state of the art and future directions for research but also frameworks for making sense of this complex area. This book provides a variety of perspectives on how technology innovations such as fog, edge and dew computing, 5G networks, and distributed intelligence are making us rethink conventional cloud computing to support the Internet of Things. Much of this book focuses on technical aspects of the Internet of Things, however, clear methodologies for mapping the business value of the Internet of Things are still missing. We provide a value mapping framework for the Internet of Things to address this gap. While there is much hype about theInternet of Things, we have yet to reach the tipping point. As such, this book provides a timely entrée for higher education educators, researchers and students, industry and policy makers on the technologies that promise to reshape how society interacts and operates.

The militarized legacy of the digital cloud: how the cloud grew out of older network technologies and politics. We may imagine the digital cloud as placeless, mute, ethereal, and unmediated. Yet the reality of the cloud is embodied in thousands of massive data centers, any one of which can use as much electricity as a midsized town. Even all these data centers are only one small part of the cloud. Behind that cloud-shaped icon on our screens is a whole universe of technologies and cultural norms, all working to keep us from noticing their existence. In this book, Tung-Hui Hu examines the gap between the real and the virtual in our understanding of the cloud. Hu shows that the cloud grew out of such older networks as railroad tracks, sewer lines, and television circuits. He describes key moments in the prehistory of the cloud, from the game “Spacewar” as exemplar of time-sharing computers to Cold War bunkers that were later reused as data centers. Countering the popular perception of a new “cloudlike” political power that is dispersed and immaterial, Hu argues that the cloud grafts digital technologies onto older ways of exerting power over a population. But because we invest the cloud with cultural fantasies about security and participation, we fail to recognize its militarized origins and ideology. Moving between the materiality of the technology itself and its cultural rhetoric, Hu's account offers a set of new tools for rethinking the contemporary digital environment.

Improve your Azure architecture practice and set out on a cloud and cloud-native journey with this Azure cloud native architecture guide Key FeaturesDiscover the key drivers of successful Azure architectureImplement architecture maps as a compass to tackle any challengeUnderstand architecture maps in detail with the help of practical use casesBook Description Azure offers a wide range of services that enable a million ways to architect your solutions. Complete with original maps and expert analysis, this book will help you to explore Azure and choose the best solutions for your unique requirements. Starting with the key aspects of architecture, this book shows you how to map different architectural perspectives and covers a variety of use cases for each architectural discipline. You'll get acquainted with the basic cloud vocabulary and learn which strategic aspects to consider for a successful cloud journey. As you advance through the chapters, you'll understand technical considerations from the perspective of a solutions architect. You'll then explore infrastructure aspects, such as network, disaster recovery, and high availability, and leverage Infrastructure as Code (IaC) through ARM templates, Bicep, and Terraform. The book also guides you through cloud design patterns, distributed architecture, and ecosystem solutions, such as Dapr, from an application architect's perspective. You'll work with both traditional (ETL and OLAP) and modern data practices (big data and advanced analytics) in the cloud and finally get to grips with cloud native security. By the end of this book, you'll have picked up best practices and more rounded knowledge of the different architectural perspectives. What you will learnGain overarching architectural knowledge of the Microsoft Azure cloud platformExplore the possibilities of building a full Azure solution by considering different architectural perspectivesImplement best practices for architecting and deploying Azure infrastructureReview different patterns for building a distributed application with ecosystem frameworks and solutionsGet to grips with cloud-native concepts using containerized workloadsWork with AKS (Azure Kubernetes Service) and use it with service mesh technologies to design a microservices hosting platformWho this book is for This book is for aspiring Azure Architects or anyone who specializes in security, infrastructure, data, and application architecture. If you are a developer or infrastructure engineer looking to enhance your Azure knowledge, you'll find this book useful.

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/.