Preface

The open source geographic information system, QGIS, at version 2.6 now rivals even the most expensive commercial GIS software in both functionality and usability. It is also a showcase of the best geospatial open source technology available. It is not just a project in itself, but the marriage of dozens of open source projects in a single, clean interface.

Geospatial technology is not just the combined application of technology to geography. It is a symphony of geography, mathematics, computer science, statistics, physics, and other fields. The underlying algorithms implemented by QGIS are so complex that only a handful of people in the world can understand all of them. Yet, QGIS packages all this complexity so well that school children, city managers, disease researchers, geologists, and many other professionals wield this powerful software with ease to make decisions that improve life on earth.

However, this book is about another feature of QGIS that makes it the best choice for geospatial work. QGIS has one of the most deeply-integrated and well-designed Python interfaces of any software, period. In the latest version, there is virtually no aspect of the program that is off limits to Python, making it the largest geospatial Python library available. Almost without exception, the Python API, called PyQGIS, is consistent and predictable.

This book exploits the best features of QGIS to demonstrate over 140 reusable recipes, which you can use to automate workflows in QGIS or to build standalone GIS applications. Most recipes are very compact, and even if you can't find the exact solution that you are looking for, you should be able to get close. This book covers a lot of ground and pulls together fragmented ideas and documentation scattered throughout the Internet as well as the results of many hours of experimenting at the edges of the PyQGIS API.