CD-ROM contains: Four Microsoft PowerPoint presentations and interactive mapping exercises, some of which extend the scholarly material and addresses new issues related to historical GIS.

This book collects innovative research presented at the 19th Conference of the Association of Geographic Information Laboratories in Europe (AGILE) on Geographic Information Science, held in Helsinki, Finland in 2016.

This book is an initiative presented by the Commission on Geographical Education of the International Geographical Union. It focuses particularly on what has been learned from geospatial projects and research from the past decades of implementing geospatial technologies (GST) in formal and informal education. The objective of this publication is to inform an international audience of teachers, professionals, scholars, and policymakers about the state of the art and prospects of geospatial practices (GPs) as organized activities that use GST and lessons learned in relation to geographical education. GST make up an advanced body of knowledge developed by practitioners of geographic information systems (GIS), remote sensing (RS), global positioning systems, (GPS), and digital cartography (DC). GST have long been applied in many different sectors; however, their first use in higher education began in the early 1980s and then diffused to secondary schools during the 1990s. Starting with GIS and RS, it evolved into a much broader context, as GST expanded to include GPS and DC with new communication technologies and Internet applications. GST have been used around the world as a combination of tools and special techniques to make research, teaching, and learning more effective.

Modern landscape research uses a panoply of techniques to further our understanding of our changing world, including mathematics, statistics and advanced simulation techniques to combine empirical observations with known theories. This book identifies emerging fields and new challenges that are discussed within the framework of the ‘driving forces’ of Landscape Development. the book addresses all of the ‘hot topics’ in this important area of study and emphasizes major contemporary trends in these fields.

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/. Dr. Robin Lovelace is a University Academic Fellow at the University of Leeds, where he has taught R for geographic research over many years, with a focus on transport systems. Dr. Jakub Nowosad is an Assistant Professor in the Department of Geoinformation at the Adam Mickiewicz University in Poznan, where his focus is on the analysis of large datasets to understand environmental processes. Dr. Jannes Muenchow is a Postdoctoral Researcher in the GIScience Department at the University of Jena, where he develops and teaches a range of geographic methods, with a focus on ecological modeling, statistical geocomputing, and predictive mapping. All three are active developers and work on a number of R packages, including stplanr, sabre, and RQGIS.

The book comprises innovative research presented at the 14th Conference of the Association of Geographic Information Laboratories in Europe (AGILE), held in 2011 in Utrecht, The Netherlands. The scientific papers cover a large variety of fundamental research topics as well as applied research in Geoinformation Science including measuring spatiotemporal phenomena, quality and semantics, spatiotemporal analysis, modeling and decision support as well as spatial information infrastructures. The book is aimed at researchers, practitioners and students who work in various fields and disciplines related to Geoinformation Science and technology.

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

This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data. It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions of how the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary spatial data with contributions introducing into the exciting field of spatial statistics or into uncertain databases. A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data. This would include for example, research in historic map data, road network extraction, damage estimation from remote sensing imagery, or the analysis of spatio-textual collections and social media. This multi-disciplinary approach makes the book unique. This handbook can be used as a reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as practitioners facing big collections of geospatial data.

Earth Observation interacts with space, remote sensing, communication, and information technologies, and plays an increasingly significant role in Earth related scientific studies, resource management, homeland security, topographic mapping, and development of a healthy, sustainable environment and community. Geospatial Technology for Earth Observation provides an in-depth and broad collection of recent progress in Earth observation. Contributed by leading experts in this field, the book covers satellite, airborne and ground remote sensing systems and system integration, sensor orientation, remote sensing physics, image classification and analysis, information extraction, geospatial service, and various application topics, including cadastral mapping, land use change evaluation, water environment monitoring, flood mapping, and decision making support. Geospatial Technology for Earth Observation serves as a valuable training source for researchers, developers, and practitioners in geospatial science and technology industry. It is also suitable as a reference book for upper level college students and graduate students in geospatial technology, geosciences, resource management, and informatics.