Most government agencies and private companies are investing significant resources in the production and use of geographical data. The capabilities of Geographical Information Systems (GIS) for data analysis are also improving, to the extent that the potential performance of GIS software and the data available for analysis outstrip the abilities of

The significance of modeling in managing the environment is well recognized from scientific and engineering perspectives as well as in the political arena. Environmental concerns and issues of sustainability have permeated both public and private sectors, particularly the need to predict, assess and mitigate against adverse impacts that arise from continuing development and use of resources. Students need to be made aware of these issues. Practitioners should enrich their knowledge and skills in these areas. This book focuses on the modeling, rather than on data collection or visualization.

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

GIS and Environmental Modeling: Progress and Research Issues Michael F. Goodchild, Louis T. Steyaert, Bradley O. Parks, Carol Johnston, David Maidment, Michael Crane, and Sandi Glendinning, Editors With growing pressure on natural resources and landscapes there is an increasing need to predict the consequences of any changes to the environment. Modelling plays an important role in this by helping our understanding of the environment and by forecasting likely impacts. In recent years moves have been made to link models to Geographical Information Systems to provide a means of analysing changes over an area as well as over time. GIS and Environmental Modeling explores the progress made to date in integrating these two software systems. Approaches to the subject are made from theoretical, technical as well as data stand points. The existing capabilities of current systems are described along with important issues of data availability, accuracy and error. Various case studies illustrate this and highlight the common concepts and issues that exist between researchers in different environmental fields. The future needs and prospects for integrating GIS and environmental models are also explored with developments in both data handling and modelling discussed. The book brings together the knowledge and experience of over 100 researchers from academic, commercial and government backgrounds who work in a wide range of disciplines. The themes followed in the text provide a fund of knowledge and guidance for those involved in environmental modelling and GIS. The book is easily accessible for readers with a basic GIS knowledge and the ideas and results of the research are clearly illustrated with both colour and black and white graphics.

Spatial dimensions need to be properly captured if modelling and engineering techniques are to be successfully applied in addressing environmental problems. The links between the geographical information systems (GIS) that capture this data, simulation modelling, and engineering offer tremendous possibilities for building versatile support systems for managing the environment. GIS, Environmental Modelling and Engineering focuses on using GIS and external models to solve real environmental problems, promoting the critical thinking needed for the effective applications of these systems and their analytical outputs. Divided into three major sections, this textbook first concentrates on defining GIS, identifying how data is structured, and explaining common functionality. The text examines GIS from a technological perspective, exploring the evolution of its scientific basis and its synergies with other technologies within a geocomputational paradigm. The next section explores modelling from a neutral scientific perspective in its role of simulating phenomena, as well as from a more specific perspective in its role within environmental science and engineering. The third and largest section looks at how GIS and simulation modelling are joined. It provides case studies and covers issues such as interoperability, data quality, model validity, space-time dynamics, and decision-support systems. This volume provides seniors and postgraduate students with a structured, coherent text that goes beyond introductory subject matter by enabling readers to think critically about the data acquisition process and the results they get from the technology.

GIS users and professionals are aware that the accuracy of GIS results cannot be naively based on the quality of the graphical output. Data stored in a GIS will have been collected or measured, classified, generalised, interpreted or estimated, and in all cases this allows the introduction of errors.; With the processing of translation of this data into the GIS itself further propagation or amplification or errors also occur. It is essential that GIS professionals understand these issues systematically if they are to build ever more accurate systems.; In this book the authors decade of study into these problems is brought into focus with an account of the development, application and implementation of error propagation techniques for use in environmental modelling with GIS. Its purpose is to provide a methodology for handling error and error propagation.

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.