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This book explores the concept of a map as a fundamental data type. It defines maps at three levels. The first is an abstract level, in which mathematic concepts are leveraged to precisely explain maps and operational semantics. The second is at a discrete level, in which graph theory is used to create a data model with the goal of implementation in computer systems. Finally, maps are examined at an implementation level, in which the authors discuss the implementation of a fundamental map data type in database systems. The map data type presented in this book creates new mechanisms for the storage, analysis, and computation of map data objects in any field that represents data in a map form. The authors develop a model that includes a map data type capable of representing thematic and geometric attributes in a single data object. The book provides a complete example of mathematically defining a data type, ensuring closure properties of those operations, and then translating that type into a state that is suited for implementation in a particular context. The book is designed for researchers and professionals working in geography or computer science in a range of fields including navigation, reasoning, robotics, geospatial analysis, data management, and information retrieval.
First published in 2004. This text is an essential guide to current research approaches in human geography, covering all aspects of undertaking a geography research project, from the selection of an appropriate topic through to the organisation and writing of the final report. Covering a wide range of contemporary research methods, the authors provide practical advice on how to actually undertake a project.
As political, economic, and environmental issues increasingly spread across the globe, the science of geography is being rediscovered by scientists, policymakers, and educators alike. Geography has been made a core subject in U.S. schools, and scientists from a variety of disciplines are using analytical tools originally developed by geographers. Rediscovering Geography presents a broad overview of geography's renewed importance in a changing world. Through discussions and highlighted case studies, this book illustrates geography's impact on international trade, environmental change, population growth, information infrastructure, the condition of cities, the spread of AIDS, and much more. The committee examines some of the more significant tools for data collection, storage, analysis, and display, with examples of major contributions made by geographers. Rediscovering Geography provides a blueprint for the future of the discipline, recommending how to strengthen its intellectual and institutional foundation and meet the demand for geographic expertise among professionals and the public.
Recent years in North America have seen a rapid development in the area of crime analysis and mapping using Geographic Information Systems (GIS) technology. In 1996, the US National Institute of Justice (NIJ) established the crime mapping research center (CMRC), to promote research, evaluation, development, and dissemination of GIS technology. The long-term goal is to develop a fully functional Crime Analysis System (CAS) with standardized data collection and reporting mechanisms, tools for spatial and temporal analysis, visualization of data and much more. Among the drawbacks of current crime analysis systems is their lack of tools for spatial analysis. For this reason, spatial analysts should research which current analysis techniques (or variations of such techniques) that have been already successfully applied to other areas (e.g., epidemiology, location-allocation analysis, etc.) can also be employed to the spatial analysis of crime data. This book presents a few of those cases.
Geographic data models are digital frameworks that describe the location and characteristics of things in the world around us. With a geographic information system, we can use these models as lenses to see, interpret, and analyze the infinite complexity of our natural and man-made environments. With the geodatabase, a new geographic data model introduced with ArcInfo 8, you can extend significantly the level of detail and range of accuracy with which you can model geographic reality in a database environment.
Today, we believe that the map is a copy of the Earth, without realizing that the opposite is true: in our culture the Earth has assumed the form of a map. In Blinding Polyphemus, Franco Farinelli elucidates the philosophical correlation between cultural evolution and shifting cartographies of modern society, giving readers an interdisciplinary study that attempts to understand and redefine the fundamental structures of cartography, architecture, and the notion of "space." Following the lessons of nineteenth-century critical German geography, this is a manual of geography without any map. To indicate where things are means already responding, in implicit and unreflective ways, to prior questions about their nature. Blinding Polyphemus not only takes account of the present state of the Earth and of human geography, it redefines the principal models we possess for the description of the world: the map, above all, as well as the landscape, subject, place, city, and space.
Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of applications in Earth and Environmental Science, a clear link between GIS and open source software is essential for the study of spatial objects or phenomena that occur in the real world and facilitate problem-solving. Organized into clear sections on applications and using case studies, the book helps researchers to more quickly understand GIS data and formulate more complex conclusions. The book is the first reference to provide methods and applications for combining the use of R and GIS in modeling spatial processes. It is an essential tool for students and researchers in earth and environmental science, especially those looking to better utilize GIS and spatial modeling. - Offers a clear, interdisciplinary guide to serve researchers in a variety of fields, including hazards, land surveying, remote sensing, cartography, geophysics, geology, natural resources, environment and geography - Provides an overview, methods and case studies for each application - Expresses concepts and methods at an appropriate level for both students and new users to learn by example
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/.