a great review has been published in Conservation Biology. It is nicely addressing the scope of the book while also outlining what is missing – we are working on it to include also non-multispectral data – updates soon.
see here for the review and other interesting book reviews:
Remote Sensing and GIS for Ecologists Using Open Source Software. Wegmann, M., B. Leutner, and S. Dech. 2016. Pelagic Publishing, Exeter, U.K. 316 pp. $43.33 (paperback). ISBN 978-1-78427-022-3.
This book to open methods created by the ongoing geospatial revolution to ecologists, who could then use remote-sensing data more widely for local- or global-scale research. It is a textbook, not a scientific review, and, as is clearly stated, aims to be a primer. The authors only assume basic computer skills but no theoretical knowledge of geographic information systems (GIS), and the context is platform independent. This sounds like a dream for many scientists, but it does come with a limitation. From the vast opportunities offered by remote sensing and GIS, this book discusses only analysis of multispectral satellite remote-sensing data at regional scale, and even that at an introductory level. Within this scope, however, it is a rather comprehensive guide and includes not only image handling, processing, and classification but also collection of reference data, accuracy analyses, and more ecology-focused applications such as species distribution modeling and animal-movement analysis. As a textbook, it does not focus on the current state of the art or the most recent developments; rather, it introduces the tools and methods that are routinely applied nowadays. The book relies on open-source software. For ecologists who are usually not programmers, the main advantage of this is that (at least) the software is free. The book also points the user toward freely available data sets and describes workflows that are uncomplicated and robust. The brave step this textbook takes is to introduce R and command-line or script-based GIS processing. Although working without a graphical user interface may involve a steep learning curve, it is clearly worth the investment because it allows an iterative approach and processing of large data sets. The authors successfully balance usefulness to a novice and theoretical correctness and introduce what may be called remote-sensing common sense through many practical tips and do’s and don’ts. Still, this book will not save one from experimenting on a trial and error basis. The authors stress there is no single method that can be recommended and that many have to be tested to find the appropriate fit. All the examples are demonstrated on the same data set, which tempts the reader to use the online resources provided. Despite its challenging scope, it is not too long, and the chapters are concise enough to work as self-contained exercises. Remote Sensing and GIS for Ecologists could become an essential undergraduate-level textbook, but it is also a guide to practicing ecologists who want to broaden their toolkit, especially ecologists who work in interdisciplinary teams.