Over 140 recipes to help you turn QGIS from a desktop GIS tool into a powerful automated geospatial framework
Key Features
- Use Python and QGIS to create and transform data, produce appealing GIS visualizations, and build complex map layouts
- Learn undocumented features of the new QGIS processing module
- A set of user-friendly recipes that can automate the entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes
Book Description
QGIS Python Programming will teach you how to write Python code that works with spatial data to automate geoprocessing tasks in QGIS. It will cover topics such as querying and editing vector data and using raster data. You will also learn to create, edit, and optimize a vector layer for faster queries, reproject a vector layer, reduce the number of vertices in a vector layer without losing critical data, and convert a raster to a vector. Following this, you will come across recipes that will help you to compose static maps, create heavily customized maps, and add specialized labels and annotations. Apart from this, the book will also share a few tips and tricks based on different aspects of this powerful tool.
What you will learn
- Build a library of reusable scripts with ScriptRunner
- Create, import, and edit geospatial data on disk or in memory
- Get to know more about dynamic mapping
- Create and add features to static maps
- Create a mapbook
- Reproject a vector layer
- Geolocate photos on a map
- Combine multiple rasters into one image
Joel Lawhead is a PMI-certified Project Management Professional (PMP) and the Chief Information Officer (CIO) of NVisionSolutions Inc., an award-winning firm that specializes in geospatial technology integration and sensor engineering. Joel began using Python in 1997 and began combining it with geospatial software development in 2000. He is the author of Learning Geospatial Analysis with Python, Packt Publishing. His Python cookbook recipes were featured in two editions of Python Cookbook, O'Reilly Media. He is also the developer of the widely used, open source Python Shapefile Library (PyShp) and maintains the geospatial technical blog GeospatialPython.com and the Twitter feed @SpatialPython, which discuss the use of the Python programming language within the geospatial industry. In 2011, Joel reverse engineered and published the undocumented shapefile spatial indexing format and assisted fellow geospatial Python developer, Marc Pfister, in reversing the algorithm used, allowing developers around the world to create better-integrated and more robust geospatial applications involving shapefiles. Joel served as the lead architect, project manager, and co-developer for geospatial applications used by US government agencies, including NASA, FEMA, NOAA, the US Navy, and many other commercial and non-profit organizations. In 2002, he received the international Esri Special Achievement in GIS award for his work on the Real-Time Emergency Action Coordination Tool (REACT), for emergency management using geospatial analysis.
