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Geospatial Power Tools
Tool Up! Become a data management superstar with tools from the Geospatial Data Abstraction Library (GDAL). This book is a reference guide for quickly finding the right syntax and example usage of all GDAL/OGR commands. Used behind most of the open source geospatial applications, as well as leading proprietary GIS applications, GDAL is the preeminent spatial data access library. GDAL comes with several powerful command line utilities including tools for examining, converting, transforming, building and analyzing raster and vector data. Included within is substantial new content, supplementing the GDAL documentation which makes up the rest of the book. Look up a workflow concept like "Translate Vectors" and quickly find examples designed to get you going right away. Digital versions of the book are fully linked with bookmarks between topics and command names, making it easier than ever to follow from an example to more detailed documentation. Tooling up your skills with this book will allow you to confidently tackle future raster and vector data management challenges!
358 pages, Paperback
First published November 4, 2014
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November 14, 2021
+ This showed me how powerful GDAL OGR is, and how desktop GIS users can start using command line tools in their work. Most geospatial tools are made with the said library so it's nice to know what happens "under the hood.".
+ I think that learning from an old (and maybe outdated) book is better than learning from a new one. The "DIY and learn the hard way" approach works.
- Most of the needed datasets are gone or moved elsewhere online. Fortunately, the author was fast to provide a copy of all the datasets needed.
- I wish there were more "recipes" that referenced these datasets. Past Chapter II, the needed datasets aren't referenced anymore so you need to test each utility on your own.
- The layouting, editing, and overall writing can be better.
+ I think that learning from an old (and maybe outdated) book is better than learning from a new one. The "DIY and learn the hard way" approach works.
- Most of the needed datasets are gone or moved elsewhere online. Fortunately, the author was fast to provide a copy of all the datasets needed.
- I wish there were more "recipes" that referenced these datasets. Past Chapter II, the needed datasets aren't referenced anymore so you need to test each utility on your own.
- The layouting, editing, and overall writing can be better.
Displaying 1 of 1 review