Description
Book SynopsisThis 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.
Trade ReviewRemote Sensing and GIS for Ecologists could become an essential undergraduate-level textbook, but it is also a guide to practising ecologists who want to broaden their toolkit.
* Conservation Biology *
We recommend this book not only as an interesting and informative guide to remote sensing concepts, but also as a vehicle to quickly delve into hands-on processing and analysis of remote sensing data to answer many questions relevant to landscape ecologists.
-- Danica Schaffer-Smith and Jennifer J. Swenson * Landscape Ecology *
Table of ContentsIntroduction
1 Spatial Data and Software
2 Introduction to Remote Sensing and GIS
3 Where to Obtain Spatial Data?
4 Spatial Data Analysis for Ecologists: First Steps
5 Pre-Processing Remote Sensing Data
6 Field Data for Remote Sensing Data Analysis
7 From Spectral to Ecological Information
8 Land Cover or Image Classification Approaches
9 Land Cover Change or Change Detection
10 Continuous Land Cover Information
11 Time Series Analysis
12 Spatial Land Cover Pattern Analysis
13 Modelling Species Distributions
14 Introduction to the added value of Animal Movement Analysis and Remote Sensing
Outlook and Acknowledgements
Index
