Michael F. Goodchild

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. Spatial Data Quality will be of interest to anyone undertaking research using GIS and related technologies.

Geospatial Analysis (6th edition) provides a compehensive guide to concepts, methods and tools, with many examples being provided using a variety of software tools such as ArcGIS, Idrisi, Grass, Surfer and many others to clarify the concepts discussed. Topics covered in detail include: Geospatial analysis concepts Analytical methodologies and model building Core components of geospatial analysis, including distance and directional analysis, geometrical processing, map algebra, and grid models Exploratory Spatial and Spatio-temporal Data Analysis (ESDA, ESTDA) and spatial statistics, including spatial autocorrelation and spatial regression Surface analysis, including surface form and flow analysis, gridding and interpolation methods, and visibility analysis Network and locational analysis, including shortest path calculation, travelling salesman problems, facility location and arc routing Geocomputational methods, including agent-based modelling, artifical neural networks and evolutionary computing Big Data - lessons for researchers

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.

Effective use of today’s powerful GIS technology requires an understanding of the science of problem-solving that underpins it. Since the first edition published over a decade ago, this book has led the way, with its focus on the scientific principles that support GIS usage. It has also provided thorough, upto- date coverage of GIS procedures, techniques and public policy applications. This unique combination of science, technology and practical problem solving has made this book a best-seller across a broad spectrum of disciplines. This fully updated 4th edition continues to deliver on these strengths.

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.

An integrated approach that combines essential GIS background with a practical workbook on applying the principles in ArcGIS 10.0 and 10.1 Introducing Geographic Information Systems with ArcGISintegrates a broad introduction to GIS with a software-specific workbook for Esri's ArcGIS. Where most courses make do using two separate texts, one covering GIS and another the software, this book enables students and instructors to use a single text with an integrated approach covering both in one volume with a common vocabulary and instructional style. This revised edition focuses on the latest software updates—ArcGIS 10.0 and 10.1. In addition to its already successful coverage, the book allows students to experience publishing maps on the Internet through new exercises, and introduces the idea of programming in the language Esri has chosen for applications (i.e., Python). A DVD is packaged with the book, as in prior editions, containing data for working out all of the exercises. This complete, user-friendly coursebook: Is updated for the latest ArcGIS releases—ArcGIS 10.0 and 10.1Introduces the central concepts of GIS and topics needed to understand spatial information analysisProvides a considerable ability to operate important tools in ArcGISDemonstrates new capabilities of ArcGIS 10.0 and 10.1Provides a basis for the advanced study of GIS and the study of the newly emerging field of GIScience Introducing Geographic Information Systems with ArcGIS, Third Edition is the ideal guide for undergraduate students taking courses such as Introduction to GIS, Fundamentals of GIS, and Introduction to ArcGIS Desktop. It is also an important guide for professionals looking to update their skills for ArcGIS 10.0 and 10.1.

This book explains the concept of spatial data quality, a key theory for minimizing the risks of data misuse in a specific decision-making context. Drawing together chapters written by authors who are specialists in their particular field, it provides both the data producer and the data user perspectives on how to evaluate the quality of vector or raster data which are both produced and used. It also covers the key concepts in this field, such as: how to describe the quality of vector or raster data; how to enhance this quality; how to evaluate and document it, using methods such as metadata; how to communicate it to users; and how to relate it with the decision-making process. Also included is a Foreword written by Professor Michael F. Goodchild.

A complete and applicable guide to Internet GIS technology and software Internet GIS addresses a suite of emerging new technologies aimed at making GIS more mobile, powerful, and flexible, as well as better able to share and communicate geographic information. This groundbreaking book is the first of its kind to thoroughly cover basic Internet GIS issues–such as state-of-the-art technology, implementation practices, applications, and data, as well as future trends in Internet GIS–in preparation for using and getting the most out of newly available, off-the-shelf Internet GIS software packages. Broad, in-depth coverage of Internet GIS introduces basic network architecture, establishes a practical framework for applications, and demonstrates how the technology functions in the real world. One-of-a-kind material features: *Thirty-three informative case studies illustrating applied techniques *Product reviews of software packages performing in a variety of applications and environments *Web resources and references at the end of each chapter More than a fundamentals book, this progressive text discusses application development, metadata, recent open standard initiatives, and methods for ensuring that current systems will be compatible with future trends. Internet GIS offers professionals and students a peerless guide to navigating both the field and the best technology available.

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.

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.