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.

Particularly about forests in the USA.

In an age of unprecedented proliferation of data from disparate sources the urgency is to create efficient methodologies that can optimise data combinations and at the same time solve increasingly complex application problems. Integration of GIS and Remote Sensing explores the tremendous potential that lies along the interface between GIS and remote sensing for activating interoperable databases and instigating information interchange. It concentrates on the rigorous and meticulous aspects of analytical data matching and thematic compatibility - the true roots of all branches of GIS/remote sensing applications. However closer harmonization is tempered by numerous technical and institutional issues, including scale incompatibility, measurement disparities, and the inescapable notion that data from GIS and remote sensing essentially represent diametrically opposing conceptual views of reality. The first part of the book defines and characterises GIS and remote sensing and presents the reader with an awareness of the many scale, taxonomical and analytical problems when attempting integration. The second part of the book moves on to demonstrate the benefits and costs of integration across a number of human and environmental applications. This book is an invaluable reference for students and professionals dealing not only with GIS and remote sensing, but also computer science, civil engineering, environmental science and urban planning within the academic, governmental and commercial/business sectors.

The ability to anticipate the impacts of global environmental changes on natural resources is fundamental to designing appropriate and optimised adaptation and mitigation strategies. However, this requires the scientific community to have access to reliable, large-scale information onspatio-temporal changes in the distribution of abiotic conditions and on the distribution, structure, composition, and functioning of ecosystems. Satellite remote sensing can provide access to some of this fundamental data by offering repeatable, standardised, and verifiable information that is directly relevant to the monitoring and management of our natural capital. This book demonstrates how ecological knowledge and satellite-basedinformation can be effectively combined to address a wide array of current natural resource management needs. By focusing on concrete applied examples in both the marine and terrestrial realms, it will help pave the way for developing enhanced levels of collaboration between the ecological andremote sensing communities, as well as shaping their future research directions. Satellite Remote Sensing and the Management of Natural Resources is primarily aimed at ecologists and remote sensing specialists, as well as policy makers and practitioners in the fields of conservation biology, biodiversity monitoring, and natural resource management.

An authoritative and state-of-the-art book bringing together some of the most recent developments in remote sensing and GIS analysis with a particular emphasis on mathematical techniques and their applications. With contributions from academia, industry and research institutes, all with a high standing, this book covers a range of techniques including: fuzzy classification, artificial neural networks, geostatistical techniques (such as kriging, cokriging, stochastic simulation and regularization, texture classification, fractals, per-parcel classification, raster and vector data integration and process modelling. The range of applications includes land cover and land use mapping, cloud tracking, snow cover mapping and air temperature monitoring, topographic mapping, geological classification and soil erosion modelling. This book will be valuable to both researchers and advanced students of remote sensing and GIS. It contains several new approaches, recent developments, and novel applications of existing techniques. Most chapters report the results of experiment and investigation. Some chapters form broad reviews of recent developments in the field. In all cases, the mathematical basis is fully explained.

Landscape ecology is a rapidly growing science of quantifying the ways in which ecosystems interact - of establishing a link between activities in one region and repercussions in another region. Remote sensing is a fast, inexpensive tool for conducting the landscape inventories that are essential to this branch of science. However, anyone who has conducted studies in the field has already found that traditional landscape ecology metrics are not always reliable with remote images. Landscape Ecology: New Metric Indicators for Monitoring, Modeling, and Assessment of Ecosystems with Remote Sensing presents a new set of metrics that allows remotely sensed data to be used effectively in landscape ecology. This groundbreaking new work is the first to present new metrics for remote sensing of landscapes and demonstrate how they can be used to yield more accurate analyses for GIS studies. The new metrics expand the capabilities of GIS, reduce interference and incorrect readings, help ecologists better understand ecosystem relationships, and reduce study costs. This set of metrics should be adopted by the EPA and will be the standard measure for future landscape analysis. This authoritative guide assesses the current state of the field and how remote sensing and landscape metrics have been used to date. It also explains how some of the traditional metrics were developed and how they can fail in landscape studies. Once this background has been established, the new metrics are introduced and their benefits and uses explained. The information in this book has previously been available only in scattered journal articles; this is the first single source for complete background information and instructions on using the new metrics.

Following the successful publication of the 1st edition in 2009, the 2nd edition maintains its aim to provide an application-driven package of essential techniques in image processing and GIS, together with case studies for demonstration and guidance in remote sensing applications. The book therefore has a “3 in 1” structure which pinpoints the intersection between these three individual disciplines and successfully draws them together in a balanced and comprehensive manner. The book conveys in-depth knowledge of image processing and GIS techniques in an accessible and comprehensive manner, with clear explanations and conceptual illustrations used throughout to enhance student learning. The understanding of key concepts is always emphasised with minimal assumption of prior mathematical experience. The book is heavily based on the authors’ own research. Many of the author-designed image processing techniques are popular around the world. For instance, the SFIM technique has long been adopted by ASTRIUM for mass-production of their standard “Pan-sharpen” imagery data. The new edition also includes a completely new chapter on subpixel technology and new case studies, based on their recent research.