- Table View
- List View
Spatial Analysis with R: Statistics, Visualization, and Computational Methods
by Tonny J. OyanaIn the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes. New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data mining This second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.
Spatial Analytical Perspectives on GIS: Gisdata 4
by Manfred Fischer, Henk J. Scholten and David UnwinThe ability to manipulate spatial data in different forms and to extract additional meaning from them is at the heart of GIS, yet genuine spatial analysis tools are rarely incorporated into commercial software, thus seriously limiting their usefulness. The future of GIS technology wil depend largely on the incorporation of more powerful analytical and modelling functions - and there is agreement within the GIS community of the urgent need to address these issues. This text attempts this task. It presents the latest information on incorporating spatial analysis tools into GIS, and includes concepts and applications from both the environmental and socio-econimc sciences.
Spatial Audio (Music Technology Ser.)
by Francis RumseyExplores the principles and practical considerations of spatial sound recording and reproduction. Particular emphasis is given to the increasing importance of multichannel surround sound and 3D audio, including binaural approaches, without ignoring conventional stereo. The enhancement of spatial quality is arguably the only remaining hurdle to be overcome in pursuit of high quality sound reproduction. The rise of increasingly sophisticated spatial sound systems presents an enormous challenge to audio engineers, many of whom are confused by the possibilities and unfamiliar with standards, formats, track allocations, monitoring configurations and recording techniques. The author provides a comprehensive study of the current state of the art in spatial audio, concentrating on the most widely used approaches and configurations. Anyone wishing to expand their understanding of these cutting-edge technologies will want to own this book.
Spatial Audio Reproduction with Primary Ambient Extraction
by Jianjun HeThis book first introduces the background of spatial audio reproduction, with different types of audio content and for different types of playback systems. A literature study on the classical and emerging Primary Ambient Extraction (PAE) techniques is presented. The emerging techniques aim to improve the extraction performance and also enhance the robustness of PAE approaches in dealing with more complex signals encountered in practice. The in-depth theoretical study helps readers to understand the rationales behind these approaches. Extensive objective and subjective experiments validate the feasibility of applying PAE in spatial audio reproduction systems. These experimental results, together with some representative audio examples and MATLAB codes of the key algorithms, illustrate clearly the differences among various approaches and also help readers gain insights on selecting different approaches for different applications.
Spatial Augmented Reality: Merging Real and Virtual Worlds
by Oliver Bimber Ramesh RaskarLike virtual reality, augmented reality is becoming an emerging platform in new application areas for museums, edutainment, home entertainment, research, industry, and the art communities using novel approaches which have taken augmented reality beyond traditional eye-worn or hand-held displays. In this book, the authors discuss spatial augmented r
Spatial Cloud Computing: A Practical Approach
by Chaowei Yang Qunying HuangAn exploration of the benefits of cloud computing in geoscience research and applications as well as future research directions, Spatial Cloud Computing: A Practical Approach discusses the essential elements of cloud computing and their advantages for geoscience. Using practical examples, it details the geoscience requirements of cloud computing, c
Spatial Contact Problems in Geotechnics
by Sergey AleynikovThis book presents a systematic approach to numerical solution for a wide range of spatial contact problems of geotechnics. On the basis of the boundary element method new techniques and effective computing algorithms are considered. Special attention is given to the formulation and analysis of the spatial contact models for elastic bases. Besides the classical schemes of contact deformation, new contact models are discussed for spatially nonhomogeneous and nonlinearly elastic media properly describing soil properties.
Spatial Context: An Introduction to Fundamental Computer Algorithms for Spatial Analysis (ISPRS Book Series #12)
by Christopher GoldMany disciplines are concerned with manipulating geometric (or spatial) objects in the computer – such as geology, cartography, computer aided design (CAD), etc. – and each of these have developed their own data structures and techniques, often independently. Nevertheless, in many cases the object types and the spatial queries are similar, and this book attempts to find a common theme.
Spatial Data Analysis in Ecology and Agriculture Using R, Second Edition
by Richard E. PlantKey features: Unique in its combination of serving as an introduction to spatial statistics and to modeling agricultural and ecological data using R Provides exercises in each chapter to facilitate the book's use as a course textbook or for self-study Adds new material on generalized additive models, point pattern analysis, and new methods of Bayesian analysis of spatial data. Includes a completely revised chapter on the analysis of spatiotemporal data featuring recently introduced software and methods Updates its coverage of R software including newly introduced packages Spatial Data Analysis in Ecology and Agriculture Using R, 2nd Edition provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology, agriculture, and environmental science. Readers have praised the book's practical coverage of spatial statistics, real-world examples, and user-friendly approach in presenting and explaining R code, aspects maintained in this update. Using data sets from cultivated and uncultivated ecosystems, the book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Additional material to accompany the book, on both analyzing satellite data and on multivariate analysis, can be accessed at https://www.plantsciences.ucdavis.edu/plant/additionaltopics.htm.
Spatial Data Infrastructures in Context: North and South
by Zorica Nedović-Budić Joep Crompvoets Yola GeorgiadouIn the wake of the so-called information technology revolution, many stakeholders from the public and private sectors (including citizens) have indeed grown accustomed to the promise and usability of spatial data infrastructures (SDI) for data access, use, and sharing. With contributions from international experts, this book presents cutting edge Spatial Data Infrastructure (SDI) research on information technology, systems, and infrastructures that is theoretically-based and empirically supported. It examines the complexities involved in the establishments of SDIs in the Northern and Southern hemispheres and use of SDIs in a variety of cultural, societal, and institutional contexts. The focus is on urban and regional levels where socio-economic and environmental sustainability is realized.
Spatial Data Quality
by Wenzhong Shi Peter Fisher Michael F. GoodchildAs research in the geosciences and social sciences becomes increasingly dependent on computers, applications such as geographical information systems are becoming indispensable tools. But the digital representations of phenomena that these systems require are often of poor quality, leading to inaccurate results, uncertainty, error propagation, and
Spatial Data Science: With Applications in R (Chapman & Hall/CRC The R Series)
by Edzer Pebesma Roger BivandSpatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data. These aspects include how geometries are represented, coordinate reference systems (projections, datums), the fact that the Earth is round and its consequences for analysis, and how attributes of geometries can relate to geometries. In the second part of the book, these concepts are illustrated with data science examples using the R language. In the third part, statistical modelling approaches are demonstrated using real world data examples. After reading this book, the reader will be well equipped to avoid a number of major spatial data analysis errors. The book gives a detailed explanation of the core spatial software packages for R: sf for simple feature access, and stars for raster and vector data cubes – array data with spatial and temporal dimensions. It also shows how geometrical operations change when going from a flat space to the surface of a sphere, which is what sf and stars use when coordinates are not projected (degrees longitude/latitude). Separate chapters detail a variety of plotting approaches for spatial maps using R, and different ways of handling very large vector or raster (imagery) datasets, locally, in databases, or in the cloud. The data used and all code examples are freely available online from https://r-spatial.org/book/. The solutions to the exercises can be found here: https://edzer.github.io/sdsr_exercises/.
Spatial Decision Support Systems: Principles and Practices
by Ramanathan Sugumaran John DegrooteThis book provides a comprehensive examination of the various aspects of SDSS evolution, components, architecture, and implementation. Integrating research from a variety of disciplines, it supplies a complete overview of SDSS technologies and their application. This groundbreaking reference provides thorough coverage of the roots of SDSS. It explains the core principles of SDSS, how to use them in various decision making contexts, and how to design and develop them using readily available enabling technologies and commercial tools.
Spatial Econometric Methods in Agricultural Economics Using R
by Paolo PostiglioneModern tools, such as GIS and remote sensing, are increasingly used in the monitoring of agricultural resources. The developments in GIS technology offer growing opportunities to agricultural economics analysts dealing with large and detailed spatial databases, allowing them to combine spatial information from different sources and to produce different models. The availability of these valuable sources of information makes the advanced models suggested in the spatial statistic and econometric literature applicable to agricultural economics. This book aims at supporting stakeholders to design spatial surveys for agricultural data and/or to analyse the geographically collected data. This book attempts to describe the main typology of agricultural data and the most appropriate methods for the analysis, together with a detailed description of the available data sources and their collection methods. Topics such as spatial interpolation, point patterns, spatial autocorrelation, survey data analysis, small area estimation, regional data modelling, and spatial econometrics techniques are covered jointly with issues arising from the integration of several data types. The theory of spatial methods is complemented by real and/or simulated examples implemented through the open-source software R.
Spatial Electric Load Forecasting (Power Engineering (willis) Ser. #Vol. 18)
by H. Lee WillisContaining 12 new chapters, this second edition offers increased coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.
Spatial Epidemiological Approaches in Disease Mapping and Analysis
by Poh-Chin Lai Fun-Mun So Ka-Wing ChanContaining method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries. Describing the wide r
Spatial Filtering for the Control of Smart Structures
by James E. HubbardThis book develops and details rigorous design methodologies and performance measures for the control of modern Smart Structures. The spatially distributed/continuum or distributed parameter nature of such structures makes it difficult to apply modern lumped parameter control philosophy and techniques to such designs. While there exist a substantial amount of technical literature on the Control of Distributed Parameter Systems (DPS), there are still relatively few applications or practical implementations of the theory. The work presented in this textbook address the issue of the design and implementation of distributed parameter control schemes, for Smart Structures, which exploit both spatially distributed sensing and actuation through the use of modern smart material technology. The merging of DPS with distributed parameter transducers leads to simple, physically realizable control system designs. This text provides a significant reference for practicing professionals, students and researchers in the area of transducer design using smart materials for high performance smart structures.
Spatial Grasp as a Model for Space-based Control and Management Systems
by Peter Simon SapatyGovernmental agencies and private companies of different countries are actively moving into space around Earth with the aim to provide smart communication and industry, security, and defense solutions. This often involves massive launches of small, cheap satellites in low earth orbits, which is also contributing to the growth of space debris. The book offers a high-level holistic system philosophy, model, and technology that can effectively organize distributed space-based systems, starting with their planning, creation, and growth. The Spatial Grasp Technology described in the book, based on parallel navigation and pattern-matching of distributed environments with high-level recursive mobile code, can effectively provide any networking protocols and important system applications, by integrating and tasking available terrestrial and celestial equipment. This book contains practical examples of technology-based solutions for tracing hypersonic gliders, continuing observation of certain objects and infrastructures on Earth from space, space-based command and control of large distributed systems, as well as collective removal of increasing amounts of space junk. Earlier versions of this technology were prototyped and used in different countries, with the current version capable of being quickly implemented in traditional industrial or even university environments. This book is oriented toward system scientists, application programmers, industry managers, and university students interested in advanced MSc and PhD projects related to space conquest and distributed system management. Dr Peter Simon Sapaty, Chief Research Scientist, Ukrainian Academy of Sciences, has worked with networked systems for five decades. Outside of Ukraine, he has worked in the former Czechoslovakia (now Czech Republic and Slovakia), Germany, the UK, Canada, and Japan as a group leader, Alexander von Humboldt researcher, and invited and visiting professor. He launched and chaired the Special Interest Group (SIG) on Mobile Cooperative Technologies in Distributed Interactive Simulation project in the United States, and invented a distributed control technology that resulted in a European patent and books with Wiley, Springer, and Emerald. He has published more than 250 papers on distributed systems and has been included in the Marquis Who’s Who in the World and Cambridge Outstanding Intellectuals of the 21st Century. Peter also works with several international scientific journals.
Spatial Health Inequalities: Adapting GIS Tools and Data Analysis
by Esra OzdenerolThe neighborhoods and the biophysical, political, and cultural environments all play a key role in affecting health outcomes of individuals. Unequal spatial distribution of resources such as clinics, hospitals, public transportation, fresh food markets, and schools could make some communities as a whole more vulnerable and less resilient to adverse health effects. This somber reality suggests that it is rather the question of "who you are depends upon where you are" and the fact that health inequality is both a people and a place concern. That is why health inequality needs to be investigated in a spatial setting to deepen our understanding of why and how some geographical areas experience poorer health than others. This book introduces how spatial context shapes health inequalities. Spatial Health Inequalities: Adapting GIS Tools and Data Analysis demonstrates the spatial health inequalities in six most important topics in environmental and public health, including food insecurity, birth health outcomes, infectious diseases, children’s lead poisoning, chronic diseases, and health care access. These are the topics that the author has done extensive research on and provides a detailed description of the topic from a global perspective. Each chapter identifies relevant data and data sources, discusses key literature on appropriate techniques, and then illustrates with real data with mapping and GIS techniques. This is a unique book for students, geographers, clinicians, health and research professionals and community members interested in applying GIS and spatial analysis to the study of health inequalities.
Spatial Inequalities
by Allan G. Hill Justin Stoler John R. WeeksThis book provides a fresh analysis of the demography, health and well-being of a major African city. It brings a range of disciplinary approaches to bear on the pressing topics of urban poverty, urban health inequalities and urban growth. The approach is primarily spatial and includes the integration of environmental information from satellites and other geospatial sources with social science and health survey data. The authors Ghanaians and outsiders, have worked to understand the urban dynamics in this burgeoning West African metropolis, with an emphasis on urban disparities in health and living standards. Few cities in the global South have been examined from so many different perspectives. Our analysis employs a wide range of GIScience methods, including analysis of remotely sensed imagery and spatial statistical analysis, applied to a wide range of data, including census, survey and health clinic data, all of which are supplemented by field work, including systematic social observation, focus groups, and key informant interviews. This book aims to explain and highlight the mix of methods, and the important findings that have been emerging from this research, with the goal of providing guidance and inspiration for others doing similar work in cities of other developing nations.
Spatial Information for Land Use Management
by Michael J. Hill Richard J. AspinallGeographic Information Systems (GIS), Remote Sensing, and environmental modelling are increasingly being used to address land use and land use management issues although much of the development in these applications is based in specific case studies that are not readily accessible to a wide audience. Spatial Information for Land Use Management is d
Spatial Information Technology for Sustainable Development Goals (Sustainable Development Goals Series)
by Dilip Kumar R.B. Singh Ranjeet KaurThis textbook aims to develop a scientific knowledge base on spatial information technology to communicate the United Nations' Sustainable Development Goals (SDGs) among students, researchers, professionals and laymen. The book improves understanding of the spatial database and explains how to extract information from this for planning purposes. To enhance the knowledge of geoscientists and environmentalists, the book describes the basic fundamental concepts to advance techniques for spatial data management and analysis and discusses the methodology. The Geographic Information System (GIS), remote sensing and Global Positioning System (GPS) are presented in an integrated manner for the planning of resources and infrastructure. The management of these systems is discussed in a very lucid way to develop the reader's skills. The proper procedure for map making and spatial analysis are included along with case studies to the reader. Where the first part of the book discusses the conceptual background, the second part deals with case studies using these applications in different disciplines. The presented case studies include land use, agriculture, flood, watershed characterization and infrastructure assessment for the Sustainable Development Goals.
Spatial Information Theory
by Sara Irina Fabrikant Martin Raubal Michela Bertolotto Clare Davies Scott Freundschuh Scott BellThis book constitutes the proceedings of the 12th International Conference on Spatial Information Theory, COSIT 2015, held in Santa Fee, NM, USA, in October 2015. The 22 papers presented in this book were carefully reviewed and selected from 52 full paper submissions. The following topics are addressed: formalizing and modeling space-time, qualitative spatio-temporal reasoning and representation, language and space, signs, images, maps, and other representations of space, navigations by humans and machines.
Spatial Intelligence for a Greener Planet: AI Applications in Environmental Pollution Mapping, Analysis and Mitigation
by Kuldeep Chaurasia Pradeep K. Garg P. V. Arun Yingwei YanWith rapid advancements in AI, this book reveals how AI can be a powerful tool in reducing pollution and fostering sustainability. It highlights the integration of geospatial techniques with AI for enhancing capabilities in mapping, analysis, and mitigation of environmental pollution. Starting with foundational concepts in AI, geospatial technology, and pollution, the book addresses air, water, soil and thermal pollution, emphasizing their harmful impacts. Through real-world case studies and advanced research, it showcases AI and geospatial technology's revolutionary role in pollution mitigation, exploring AI-driven sensors, satellite imagery, and associated networks for precise and efficient pollution monitoring and management.
Spatial Linear Models for Environmental Data (Chapman & Hall/CRC Applied Environmental Statistics)
by Dale L. Zimmerman Jay M. Ver HoefMany applied researchers equate spatial statistics with prediction or mapping, but this book naturally extends linear models, which includes regression and ANOVA as pillars of applied statistics, to achieve a more comprehensive treatment of the analysis of spatially autocorrelated data. Spatial Linear Models for Environmental Data, aimed at students and professionals with a master’s level training in statistics, presents a unique, applied, and thorough treatment of spatial linear models within a statistics framework. Two subfields, one called geostatistics and the other called areal or lattice models, are extensively covered. Zimmerman and Ver Hoef present topics clearly, using many examples and simulation studies to illustrate ideas. By mimicking their examples and R code, readers will be able to fit spatial linear models to their data and draw proper scientific conclusions. Topics covered include: Exploratory methods for spatial data including outlier detection, (semi)variograms, Moran’s I, and Geary’s c. Ordinary and generalized least squares regression methods and their application to spatial data. Suitable parametric models for the mean and covariance structure of geostatistical and areal data. Model-fitting, including inference methods for explanatory variables and likelihood-based methods for covariance parameters. Practical use of spatial linear models including prediction (kriging), spatial sampling, and spatial design of experiments for solving real world problems. All concepts are introduced in a natural order and illustrated throughout the book using four datasets. All analyses, tables, and figures are completely reproducible using open-source R code provided at a GitHub site. Exercises are given at the end of each chapter, with full solutions provided on an instructor’s FTP site supplied by the publisher.