Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements. Modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Foundation of the Spatial Data Infrastructure offers a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This groundbreaking spatial model incorporates both a functional model and a stochastic model to connect the physical world to the ECEF rectangular system. Combining horizontal and vertical data into a single, three-dimensional database, this authoritative monograph provides a logical development of theoretical concepts and practical tools that can be used to handle spatial data more efficiently. The book clearly describes procedures that can be used to handle both ECEF and flat-Earth rectangular components in the context of a rigorous global environment.
Traditional methods for handling spatial data are encumbered by the assumption of separate origins for horizontal and vertical measurements, but modern measurement systems operate in a 3-D spatial environment. The 3-D Global Spatial Data Model: Principles and Applications, Second Edition maintains a new model for handling digital spatial data, the global spatial data model or GSDM. The GSDM preserves the integrity of three-dimensional spatial data while also providing additional benefits such as simpler equations, worldwide standardization, and the ability to track spatial data accuracy with greater specificity and convenience. This second edition expands to new topics that satisfy a growing need in the GIS, professional surveyor, machine control, and Big Data communities while continuing to embrace the earth center fixed coordinate system as the fundamental point of origin of one, two, and three-dimensional data sets. Ideal for both beginner and advanced levels, this book also provides guidance and insight on how to link to the data collected and stored in legacy systems.
This book covers fundamental aspects of spatial data modelling specifically on the aspect of three-dimensional (3D) modelling and structuring. Realisation of "true" 3D GIS spatial system needs a lot of effort, and the process is taking place in various research centres and universities in some countries. The development of spatial data modelling for 3D objects is the focus of this book.
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/. 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.
Book Review Index provides quick access to reviews of books, periodicals, books on tape and electronic media representing a wide range of popular, academic and professional interests. The up-to-date coverage, wide scope and inclusion of citations for both newly published and older materials make Book Review Index an exceptionally useful reference tool. More than 600 publications are indexed, including journals and national general interest publications and newspapers. Book Review Index is available in a three-issue subscription covering the current year or as an annual cumulation covering the past year.
