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Geographical Data Science and Spatial Data Analysis
We are in an age of big data where all of our everyday interactions and transactions generate data. Much of this data is spatial – it is collected some-where – and identifying analytical insight from trends and patterns in these increasing rich digital footprints presents a number of challenges. Whilst other books describe different flavours of Data Analytics in R and other programming languages, there are none that consider Spatial Data (i.e. the location attached to data), or that consider issues of inference, linking Big Data, Geography, GIS, Mapping and Spatial Analytics. This is a ‘learning by doing’ textbook, building on the previous book by the same authors, An Introduction to R for Spatial Analysis and Mapping. It details the theoretical issues in analyses of Big Spatial Data and developing practical skills in the reader for addressing these with confidence.
Spatial Analytics with ArcGIS
Pattern Analysis and cluster mapping made easy About This Book Analyze patterns, clusters, and spatial relationships using ArcGIS tools Get up to speed in R programming to create custom tools for analysis Sift through tons of crime and real estate data and analyze it using the tools built in the book Who This Book Is For This book is for ArcGIS developers who want to perform complex geographic analysis through the use of spatial statistics tools including ArcGIS and R. No knowledge of R is assumed. What You Will Learn Get to know how to measure geographic distributions Perform clustering analysis including hot spot and outlier analysis Conduct data conversion tasks using the Utilities toolse...
GIS for Science
GIS for Science presents a collection of real-world stories about modern science and a cadre of scientists who use mapping and spatial analytics to expand their understanding of the world. The accounts in this book are written for a broad audience including professional scientists, the swelling ranks of citizen scientists, and people generally interested in science and geography. Scientific data are brought to life with GIS technology to study a range of issues relevant to the functioning of planet Earth in a natural sense as well as the impacts of human activity. In a race against the clock, the scientists profiled in this volume are using remote sensing, web maps within a geospatial cloud,...
An Introduction to R for Spatial Analysis and Mapping
This is a new edition of the accessible and student-friendly ′how to′ for anyone using R for the first time, for use in spatial statistical analysis, geocomputation and digital mapping. The authors, once again, take readers from ‘zero to hero’, updating the now standard text to further enable practical R applications in GIS, spatial analyses, spatial statistics, web-scraping and more. Revised and updated, each chapter includes: example data and commands to explore hands-on; scripts and coding to exemplify specific functionality; self-contained exercises for students to work through; embedded code within the descriptive text. The new edition includes detailed discussion of new and emerging packages within R like sf, ggplot, tmap, making it the go to introduction for all researchers collecting and using data with location attached. This is the introduction to the use of R for spatial statistical analysis, geocomputation, and GIS for all researchers - regardless of discipline - collecting and using data with location attached.
Spatial Analysis
Spatial Analysis: Modelling in a GIS Environment Edited by PaulLongley and Michael Batty Digital data and information are usedincreasingly by academics, professionals, local authorities, andgovernment departments. Powerful new technologies, such asgeographic information systems (GIS), are being developed toanalyse such data, and GIS technologies are rapidly becoming partof the emergent world digital infrastructure. This book shows howcomputer methods of analysis and modelling, built around GIS, canbe used to identify ways in which our cities and regions might bebetter planned and understood. The contributors to this book areall actively involved in research using geographic informationsystem...
An Introduction to Spatial Data Analysis
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 an...
Geospatial Analysis
Addresses a range of analytical techniques that are provided within modern Geographic Information Systems and related geospatial software products. This guide covers: the principal concepts of geospatial analysis; core components of geospatial analysis; and, surface analysis, including surface form analysis, gridding and interpolation methods.
GIS, Spatial Analysis, and Modeling
A guide for geographic analysts, modelers, software engineers, and GIS professionals, this book discusses agent-based modeling, dynamic feedback and simulation modeling, as well as links between models and GIS software. This collection also presents a state-of-the-art understanding of applications based on environmental, atmospheric, hydrological, urban, social, health, and economic models.
Urban Analytics
The economic and political situation of cities has shifted in recent years in light of rapid growth amidst infrastructure decline, the suburbanization of poverty and inner city revitalization. At the same time, the way that data are used to understand urban systems has changed dramatically. Urban Analytics offers a field-defining look at the challenges and opportunities of using new and emerging data to study contemporary and future cities through methods including GIS, Remote Sensing, Big Data and Geodemographics. Written in an accessible style and packed with illustrations and interviews from key urban analysts, this is a groundbreaking new textbook for students of urban planning, urban design, geography, and the information sciences.
Perspectives on Spatial Data Analysis
Spatial data analysis has seen explosive growth in recent years. Both in mainstream statistics and econometrics as well as in many applied ?elds, the attention to space, location, and interaction has become an important feature of scholarly work. The methodsdevelopedto dealwith problemsofspatialpatternrecognition,spatialau- correlation, and spatial heterogeneity have seen greatly increased adoption, in part due to the availability of user friendlydesktopsoftware. Throughhis theoretical and appliedwork,ArthurGetishasbeena majorcontributing?gureinthisdevelopment. In this volume, we take both a retrospective and a prospective view of the ?eld. We use the occasion of the retirement and move to e...
