As the use of geographical information systems develops apace, a significant strand of research activity is being directed to the fundamental nature of geographic information. This volume contains a collection of essays and discussions on this theme. What is geographic information? What fundamental principles are associated with it? How can it be represented? How does it represent the world? How can geographic information be quantified? How can it be communicated and related to the other information sciences? How does HCI tie in with it? A number of other more specific but relevant issues are considered, such as Spatio-temporal relationships, boundaries, granularity and taxonomy. This book is a revised and updated version of a collection of presentations given by a group of distinguished researchers in the field of Geographic Information Science who gathered in Manchester in July 2001. It should be useful for graduate students as well as researchers and high-level professionals.

The book addresses the problem of accuracy of spatial databases, and comprises of papers drawn from a wide range of physical and human systems, taking approaches which vary from statistical to descriptive. Together they present both a comprehensive review of existing knowledge, techniques and experience, and an analysis of critical research needs in this area of spatial data handling.

As 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 potentially legal liability. Spatial data quality has become an essential research topic within geographical information science. This book covers many of the cutting-edge research issues related to spatial data quality, including measurement in GIS and geostatistics, the modeling of spatial objects that have inherent uncertainty, spatial data quality control, quality management, communicating uncertainty and resolution, reasoning and decision-making, visualization of uncertainty and error metadata. Spatial Data Quality will be of interest to anyone undertaking research using GIS and related technologies.

This book elucidates how cyberGIS (that is, new-generation geographic information science and systems (GIS) based on advanced computing and cyberinfrastructure) transforms computation- and data-intensive geospatial discovery and innovation. It comprehensively addresses opportunities and challenges, roadmaps for research and development, and major progress, trends, and impacts of cyberGIS in the era of big data. The book serves as an authoritative source of information to fill the void of introducing this exciting and growing field. By providing a set of representative applications and science drivers of cyberGIS, this book demonstrates how cyberGIS has been advanced to enable cutting-edge scientific research and innovative geospatial application development. Such cyberGIS advances are contextualized as diverse but interrelated science and technology frontiers. The book also emphasizes several important social dimensions of cyberGIS such as for empowering deliberative civic engagement and enabling collaborative problem solving through structured participation. In sum, this book will be a great resource to students, academics, and geospatial professionals for leaning cutting-edge cyberGIS, geospatial data science, high-performance computing, and related applications and sciences.

As Geographic Information Systems (GIS) have developed and their applications have been extended, the issue of uncertainty has become increasingly recognized. It is highlighted by the need to demystify the inherently complex geographical world to facilitate computerization in GIS, by the inaccuracies that emerge from man-machine interactions in data acquisition, and by error propagation in geoprocessing. Users need to be well aware of the likely impacts of uncertainties in spatial analysis and decision-making. This book discusses theoretical and practical aspects of spatial data processing and uncertainties, and covers a wide range of types of errors and fuzziness and emphasizes description and modeling. High level GIS professionals, researchers and graduate students will find this a constructive book.

As 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 potentially legal liability. Spatial data quality has become an essential research topic within geographical information science.
This book covers many of the cutting-edge research issues related to spatial data quality, including measurement in GIS and geostatistics, the modeling of spatial objects that have inherent uncertainty, spatial data quality control, quality management, communicating uncertainty and resolution, reasoning and decision-making, visualization of uncertainty and error metadata. It will be of interest to anyone undertaking research using GIS and related technologies.

eBook available with sample pages: 0203303245

Now ubiquitous in modern life, spatial data present great opportunities to transform many of the processes on which we base our everyday lives. However, not only do these data depend on the scale of measurement, but also handling these data (e.g., to make suitable maps) requires that we account for the scale of measurement explicitly. Scale in Spatial Information and Analysis describes the scales of measurement and scales of spatial variation that exist in the measured data. It provides you with a series of tools for handling spatial data while accounting for scale. The authors detail a systematic strategy for handling scale issues from geographic reality, through measurements, to resultant spatial data and their analyses. They also explore a process-pattern paradigm in approaching scale issues. This is well reflected, for example, in chapters dealing with terrain analysis, in which scale in terrain derivatives is described in relation to the processing involved in the derivation of specific terrain variables from elevation data, and area classes, which are viewed as driven by class-forming covariates. Lastly, this book provides coverage of some of the issues related to scale that are relatively under-represented in the literature, such as the effects of scale on information content in remotely sensed images, and the interaction between scale and uncertainty that is increasingly important for spatial information and analysis. By taking a rigorous, scientific approach to scale and its various meanings in relation to the geographic world, the book alleviates some of the frustration caused by dealing with issues of scale. While past research has led to an increasing number of journal articles and a few books dedicated to scale modeling and change of scale, this book helps you to develop coherent strategies for scale modeling, highlighting applicability for a variety of fields, from geomatic engineering and geoinformatics to environmental modeling.

This is a selection of the major papers from a meeting on database accuracy which took place in December 1988 in Montecito, USA. They look at errors and accuracy in spatial databases, particularly the problems of modelling uncertainties and reliability, testing accuracy and practical implications. The chapters of the book represent a number of different perspectives on the accuracy problem, from efforts to simulate and model error to techniques for accommodating to it. The 23 chapters are organized into seven sections, and to provide a brief introduction to each. The first and last sections are general overviews. In between, the papers in Section Two through Four look at error in GIS with increasing technical complexity and generality. Section Five groups together four papers on various aspects of error in the spatial analysis of socio-economic data, and Section Six contains four papers on more fundamental approaches to the particular problems of aggreation and reporting zone effects which underlie much modeling in human geography and related disciplines.

This book is a revised and updated version of a collection of presentations given by a group of distinguished researchers in the field of Geographic Information Science who gathered in Manchester in July 2001. It should be useful for graduate students as well as researchers and high-level professionals.

This open access book offers a summary of the development of Digital Earth over the past twenty years. By reviewing the initial vision of Digital Earth, the evolution of that vision, the relevant key technologies, and the role of Digital Earth in helping people respond to global challenges, this publication reveals how and why Digital Earth is becoming vital for acquiring, processing, analysing and mining the rapidly growing volume of global data sets about the Earth. The main aspects of Digital Earth covered here include: Digital Earth platforms, remote sensing and navigation satellites, processing and visualizing geospatial information, geospatial information infrastructures, big data and cloud computing, transformation and zooming, artificial intelligence, Internet of Things, and social media. Moreover, the book covers in detail the multi-layered/multi-faceted roles of Digital Earth in response to sustainable development goals, climate changes, and mitigating disasters, the applications of Digital Earth (such as digital city and digital heritage), the citizen science in support of Digital Earth, the economic value of Digital Earth, and so on. This book also reviews the regional and national development of Digital Earth around the world, and discusses the role and effect of education and ethics. Lastly, it concludes with a summary of the challenges and forecasts the future trends of Digital Earth. By sharing case studies and a broad range of general and scientific insights into the science and technology of Digital Earth, this book offers an essential introduction for an ever-growing international audience.

This book constitutes the refereed proceedings of the 7th International Conference on Geographic Information Science, GIScience 2012, held in Columbus, OH, USA in September 2012. The 26 full papers presented were carefully reviewed and selected from 57 submissions. While the traditional research topics are well reflected in the papers, emerging topics that involve new research hot-spots such as cyber infrastructure, big data, web-based computing also occupy a significant portion of the volume.

Now ubiquitous in modern life, spatial data present great opportunities to transform many of the processes on which we base our everyday lives. However, not only do these data depend on the scale of measurement, but also handling these data (e.g., to make suitable maps) requires that we account for the scale of measurement explicitly. Scale in Spatial Information and Analysis describes the scales of measurement and scales of spatial variation that exist in the measured data. It provides you with a series of tools for handling spatial data while accounting for scale.

The authors detail a systematic strategy for handling scale issues from geographic reality, through measurements, to resultant spatial data and their analyses. They also explore a process-pattern paradigm in approaching scale issues. This is well reflected, for example, in chapters dealing with terrain analysis, in which scale in terrain derivatives is described in relation to the processing involved in the derivation of specific terrain variables from elevation data, and area classes, which are viewed as driven by class-forming covariates. Lastly, this book provides coverage of some of the issues related to scale that are relatively under-represented in the literature, such as the effects of scale on information content in remotely sensed images, and the interaction between scale and uncertainty that is increasingly important for spatial information and analysis.

By taking a rigorous, scientific approach to scale and its various meanings in relation to the geographic world, the book alleviates some of the frustration caused by dealing with issues of scale. While past research has led to an increasing number of journal articles and a few books dedicated to scale modeling and change of scale, this book helps you to develop coherent strategies for scale modeling, highlighting applicability for a variety of fields, from geomatic engineering and geoinformatics to environmental modeling.

This book elucidates how cyberGIS (that is, new-generation geographic information science and systems (GIS) based on advanced computing and cyberinfrastructure) transforms computation- and data-intensive geospatial discovery and innovation. It comprehensively addresses opportunities and challenges, roadmaps for research and development, and major progress, trends, and impacts of cyberGIS in the era of big data. The book serves as an authoritative source of information to fill the void of introducing this exciting and growing field. By providing a set of representative applications and science drivers of cyberGIS, this book demonstrates how cyberGIS has been advanced to enable cutting-edge scientific research and innovative geospatial application development. Such cyberGIS advances are contextualized as diverse but interrelated science and technology frontiers. The book also emphasizes several important social dimensions of cyberGIS such as for empowering deliberative civic engagement and enabling collaborative problem solving through structured participation. In sum, this book will be a great resource to students, academics, and geospatial professionals for leaning cutting-edge cyberGIS, geospatial data science, high-performance computing, and related applications and sciences.

This is the first book to take an ecological perspective on uncertainty in spatial data. It applies principles and techniques from geography and other disciplines to ecological research, bringing the tools of cartography, cognition, spatial statistics, remote sensing and computer sciences by way of spatial data. After describing the uses of such data in ecological research, the authors discuss how to account for the effects of uncertainty in various methods of analysis.

Spatial analysis assists theoretical understanding and empirical testing in the social sciences, and rapidly expanding applications of geographic information technologies have advanced the spatial data-gathering needed for spatial analysis and model making. This much-needed volume covers outstanding examples of spatial thinking in the social sciences, with each chapter showing some aspect of how certain social processes can be understood by analyzing their spatial context. The audience for this work is as trans-disciplinary as its authorship because it contains approaches and methodologies useful to geography, anthropology, history, political science, economics, criminology, sociology, and statistics.

As Geographic Information Systems (GIS) have developed and their applications have been extended, the issue of uncertainty has become increasingly recognised. It is highlighted by the need to demystify the inherently complex geographical world to facilitate computerisation in GIS, by the inaccuracies that emerge from man-machine interactions in data acquisition, and by error propogation in geoprocessing. Users need to be well aware of the likely impacts of uncertainties in spatial analysis and decision-making.
High level GIS professionals, researchers and graduate students will find this a constructive book. It discusses theoretical and practical aspects of spatial data processing and uncertainties, and covers a wide range of types of errors and fuzziness and emphasizes description and modelling.

eBook available with sample pages: 0203471326