Thoroughly updated with material related to the GRASS6, the third edition includes new sections on attribute database management and SQL support, vector networks analysis, lidar data processing and new graphical user interfaces. All chapters were updated with numerous practical examples using the first release of a comprehensive, state-of-the-art geospatial data set.
Since the first edition of Open Source GIS: A GRASS GIS Approach was published in 2002, GRASS has undergone major improvements. This second edition includes numerous updates related to the new development; its text is based on the GRASS 5.3 version from December 2003. Besides changes related to GRASS 5.3 enhancements, the introductory chapters have been re-organized, providing more extensive information on import of external data. Most of the improvements in technical accuracy and clarity were based on valuable feedback from readers. Open Source GIS: A GRASS GIS Approach, Second Edition, provides updated information about the use of GRASS, including geospatial modeling with raster, vector, and site data, image processing, visualization, and coupling with other open source tools for geostatistical analysis and web applications. A brief introduction to programming within GRASS encourages new development. The sample data set used throughout the book has been updated and is available on the GRASS web site. This book also includes links to sites where the GRASS software and on-line reference manuals can be downloaded and additional applications can be viewed.
Open Source GIS: A GRASS GIS Approach was written for experienced GIS users, who want to learn GRASS, as well as for the Open Source software users who are GIS newcomers. Following the Open Source model of GRASS, the book includes links to sites where the GRASS system and on-line reference manuals can be downloaded and additional applications can be viewed. The project's website can be reached at http://grass.itc.it and a number of mirror sites worldwide. Open Source GIS: A GRASS GIS Approach, provides basic information about the use of GRASS from setting up the spatial database, through working with raster, vector and site data, to image processing and hands-on applications. This book also contains a brief introduction to programming within GRASS encouraging the new GRASS development. The power of computing within Open Source environment is illustrated by examples of the GRASS usage with other Open Source software tools, such as GSTAT, R statistical language, and linking GRASS to MapServer. Open Source GIS: A GRASS GIS Approach is designed to meet the needs of a professional audience composed of researchers and practitioners in industry and graduate level students in Computer Science and Geoscience.
The authors are all prominent experts in Open Source GIS in Italy and, in many cases, the international community. They are all professionals with involvement in training and scientific research and are highly motivated by their common goal of supporting Free Software. This is, therefore, an innovative undertaking in that it provides the user with immediate access to the software tools and to the numerous resources and documents described in the text and available via the Internet.The first part of the book, which is divided into nine chapters, deals with describing reference systems and helping the user install the software packages on Microsoft, Apple, GNU/Linux operating systems.Subsequent chapters present the most important functionalities of well-known software, such as QGIS and GRASS GIS, and describe ways of managing geographic data using relational database engines (SpatiaLite). Next, a few examples and applications in landscaping, geomorphology, hydrology and geology are presented and the various online resources where users may obtain free help and support are described.The book closes with a few remarks on advanced functionalities.
This book presents a new type of modeling environment where users interact with geospatial simulations using 3D physical models of studied landscapes. Multiple users can alter the physical model by hand during scanning, thereby providing input for simulation of geophysical processes in this setting. The authors have developed innovative techniques and software that couple this hardware with open source GRASS GIS, making the system instantly applicable to a wide range of modeling and design problems. Since no other literature on this topic is available, this Book fills a gap for this new technology that continues to grow. Tangible Modeling with Open Source GIS will appeal to advanced-level students studying geospatial science, computer science and earth science such as landscape architecture and natural resources. It will also benefit researchers and professionals working in geospatial modeling applications, computer graphics, hazard risk management, hydrology, solar energy, coastal and fluvial flooding, fire spread, landscape, park design and computer games.
This book contains papers presented at the first Open Source Geospatial Research Symposium held in Nantes City, France, 8-10 July, 2009. It brings together insights and ideas in the fields of Geospatial Information and Geoinformatics. It demonstrates the scientific community dynamism related to open source and free software as well as in defining new concepts, standards or tools.
"Desktop GIS" explores the world of Open Source GIS software and provides a guide to navigate the many options available. Strategies for choosing a platform, selecting the right tools, integration, managing change, and getting support are presented.
This is a book about how ecologists can integrate remote sensing and GIS in their daily work. It will allow ecologists to get started with the application of remote sensing and to understand its potential and limitations. Using practical examples, the book covers all necessary steps from planning field campaigns to deriving ecologically relevant information through remote sensing and modelling of species distributions. All practical examples in this book rely on OpenSource software and freely available data sets. Quantum GIS (QGIS) is introduced for basic GIS data handling, and in-depth spatial analytics and statistics are conducted with the software packages R and GRASS. Readers will learn how to apply remote sensing within ecological research projects, how to approach spatial data sampling and how to interpret remote sensing derived products. The authors discuss a wide range of statistical analyses with regard to satellite data as well as specialised topics such as time-series analysis. Extended scripts on how to create professional looking maps and graphics are also provided. This book is a valuable resource for students and scientists in the fields of conservation and ecology interested in learning how to get started in applying remote sensing in ecological research and conservation planning.
Open Source Archaeology: Ethics and Practice' brings together authors and researchers in the field of open-source archaeology, defined as encompassing the ethical imperative for open public access to the results of publicly-funded research; practical solutions to open-data projects; open-source software applications in archaeology; public information sharing projects in archaeology; open-GIS; and the open-context system of data management and sharing. This edited volume is designed to discuss important issues around open access to data and software in academic and commercial archaeology, as well as to summarise both the current state of theoretical engagement, and technological development in the field of open-archaeology. Ben Edwards Ben Edwards was trained in archaeology at the University of Durham, achieving his BA, MA and PhD. His first commercial work was for Archaeological Services, Durham University, before moving on to become a Lecturer in Archaeological Practice at the University of Liverpool, where he taught for three years. During this time Ben began his project management work, undertaking both commercial and research excavations, and survey projects. His teaching (archaeological practice and heritage management) proved to be an excellent basis from which to develop his professional expertise. Ben now lectures at Manchester Metropolitan University in Archaeology and Heritage. He currently researches open source software and hardware for use in the field, and advanced 3D surveying techniques. Andrew Wilson Andrew Wilson was trained in archaeology at the University of Liverpool. Upon achieving his BA at the University, Andrew moved south to study Computer Applied Archaeology at the University of Southampton, where he was awarded an MSc. Andrew returned to the University of Liverpool where he has recently completed a PhD. During this time Andrew coordinated a number of projects both in the UK and Middle East, specialising in advanced surveying techniques of archaeological remains. Working in the the School of Computer Science, Bangor University Andrew has developed his keen interest in Open data policies and ethics. This interest was the starting point for this volume.
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/.
