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Many tips and tricks are taught in the exercise proposed. They are useful to understand how the software work and how to be efficient while working with them. This is important especially when working with a large amount of raster in R or simply on a wide area of interest, such as for time series or land cover patterns analysis, which could require an amount of RAM memory or even disk space, exceeding the ones available. The methodologies explained help to save computational resources, disk space and increase efficiency in terms of time.Satellite remote sensing and GIS were once the preserves of a small number of well-financed groups, but the field has been democratised by open-source software. QGIS and R are covered by this textbook aimed at a practitioners who want to know how to obtain, process and analyse remotely sensed data. It provides excellent guidance on designing studies and recognising both the potential and limitations of remotely sensed data. Later chapters cover common ecological applications, including distribution modelling and land cover pattern analysis. The book is printed in high quality with numerous colour figures. It would make an excellent companion to a workshop.Importantly, this book enables the reader to learn a high-level concept and become familiar with the overall language used in the discipline, and then zoom in to the nuts and bolts of how to actually execute an analysis. Consequently, the book will be a valuable resource to ecological researchers, particularly because of the focus on open source software.From how to begin with spatial data sampling, all the way through to the final creation of publishable maps and graphics, the book is an invaluable one-stop resource for ecologists, who are now increasingly utilising the power of spatial datasets for research, conservation practice and policy.We recommend this book not only as an interesting and informative guide to remote sensing concepts, but also as a vehicle to quickly delve intlăŔ
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