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Geographic Information Analysis provides up-to-date coverage of the foundations of spatial data analysis through visualization and maps. This book covers key spatial concepts, including point pattern, line objects and networks, area objects, and continuous fields, as well as such new subjects as local statistics. With crucial methods for analyzing geographical information, this is an essential reference for professionals as well as a useful text for the classroom.
Providing a solid foundation for twenty-first-century scientists and engineers, Data Analysis and Statistics for Geography, Environmental Science, and Engineering guides readers in learning quantitative methodology, including how to implement data analysis methods using open-source software. Given the importance of interdisciplinary work in sustain
This book focuses on a range of geospatial applications for environmental health research, including environmental justice issues, environmental health disparities, air and water contamination, and infectious diseases. Environmental health research is at an exciting point in its use of geotechnologies, and many researchers are working on innovative approaches. This book is a timely scholarly contribution in updating the key concepts and applications of using GIS and other geospatial methods for environmental health research. Each chapter contains original research which utilizes a geotechnical tool (Geographic Information Systems (GIS), remote sensing, GPS, etc.) to address an environmental health problem. The book is divided into three sections organized around the following themes: issues in GIS and environmental health research; using GIS to assess environmental health impacts; and geospatial methods for environmental health. Representing diverse case studies and geospatial methods, the book is likely to be of interest to researchers, practitioners and students across the geographic and environmental health sciences. The authors are leading researchers and practitioners in the field of GIS and environmental health.
Currently, spatial analysis is becoming more important than ever because enormous volumes of spatial data are available from different sources, such as GPS, Remote Sensing, and others. This book deals with spatial analysis and modelling. It provides a comprehensive discussion of spatial analysis, methods, and approaches related to human settlements and associated environment. Key contributions with empirical case studies from Iran, Philippines, Vietnam, Thailand, Nepal, and Japan that apply spatial analysis including autocorrelation, fuzzy, voronoi, cellular automata, analytic hierarchy process, artificial neural network, spatial metrics, spatial statistics, regression, and remote sensing mapping techniques are compiled comprehensively. The core value of this book is a wide variety of results with state of the art discussion including empirical case studies. It provides a milestone reference to students, researchers, planners, and other practitioners dealing the spatial problems on urban and regional issues. We are pleased to announce that this book has been presented with the 2011 publishing award from the GIS Association of Japan. We would like to congratulate the authors!
Floods and flash floods with hydro-meteorological and tropical cyclones are the some of the most devastating natural disasters causing massive damages to natural and man-made features. Flood hazards are a major threat to human life, properties (agricultural area, yield production, building and homes) and infrastructures (bridges, roads, railways, urban infrastructures, etc). Flood hazards susceptibility mapping (risk assessment) and modelling is an essential step for early warning systems, emergency services, prevention and mitigation of future environmental and social hazards and implementation of risk management strategies. Due to the lack of proper information, technology-based policies and strategies, mapping and modelling can often not be implemented to the best possible level. Geo-spatial techniques have enjoyed rising interest in recent decades among the earth environmental and social sciences research communities for their powerful ability to solve and understand various complex problems and develop novel approaches toward sustainable earth and human society. By linking geo-spatial computational intelligence techniques with societal and environmental-oriented problems, this book demonstrates geospatial technology approaches to data mining techniques, data analysis, modelling, risk assessment and visualization and management strategies in different aspects of flood hazards. We believe that a diverse group of academics, scientists, geographers, hydrologist, remote sensing and GIS expertise, environmentalists, meteorologists and computing experts with a common interest in geospatial sciences within the earth environmental sciences and humanistic and social sciences will find this book to be of great value.
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.
An introductory overview of spatial analysis and statistics through GIS, including worked examples and critical analysis of results.
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 purpose of this volume is to provide a review and analysis of the theory, research, and practice related to geospatial technologies in social studies education. In the first section, the history of geospatial technologies in education, the influence of the standards movement, and the growth of an international geospatial education community are explored. The second section consists of examples and discussion of the use of geospatial technologies for teaching and learning history, geography, civics, economics, and environmental science. In the third section, theoretical perspectives are proposed that could guide research and practice in this field. This section also includes reviews and critiques of recent research relevant to geospatial technologies in education. The final section examines the theory, research, and practice associated with teacher preparation for using geospatial technologies in education.
This textbook is a step-by-step tutorial on the applications of Geographic Information Systems (GIS) in environmental and water resource issues. It provides information about GIS and its applications, specifically using the most advanced ESRI GIS technology and its extensions. Eighteen chapters cover GIS applications in the field of earth sciences and water resources in detail from the ground up. Author William Bajjali explains what a GIS is and what it is used for, the basics of map classification, data acquisition, coordinate systems and projections, vectorization, geodatabase and relational database, data editing, geoprocessing, suitability modeling, working with raster, watershed delineation, mathematical and statistical interpolation, and more advanced techniques, tools and extensions such as ArcScan, Topology, Geocoding, Hydrology, Geostatistical Analyst, Spatial Analyst, Network Analyst, 3-D Analyst. ArcPad, ESRI’s cutting-edge mobile GIS software, is covered in detail as well. Each chapter contains concrete case studies and exercises – many from the author’s own work in the United States and Middle East. This volume is targeted toward advanced undergraduates, but could also be useful for professionals and for anyone who utilizes GIS or practices spatial analysis in relation to geology, hydrology, ecology, and environmental sciences. Exercises and supplementary material can be downloaded by chapter here: https://link.springer.com/book/10.1007%2F978-3-319-61158-7