Automated GIS Workflows with PyQGIS [Video]

More Information
Learn
  • Create dynamic maps to control QGIS
  • Access external web services
  • Create interactive input widgets for scripts
  • Create printed maps 
  • Control QGIS GUI elements
  • Automatically generate PDF map books 
  • Build dynamic forms for field input
  • Create, import, and edit geospatial data on disk or in-memory
About

QGIS is a desktop geographic information system that facilitates data viewing, editing, and analysis. Paired with the most efficient scripting language—Python, we can write effective scripts that extend the core functionality of QGIS.

Based on version QGIS 2.18, this video 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 Creating Dynamic Maps.

You will also learn to compose static maps, interact with users.

Following this, you will work through recipes that will help you compose static maps, create heavily customized maps, and add specialized labels and annotations. As well as this, we’ll also share a few tips and tricks based on different aspects of QGIS.

Style and Approach

This video follows a recipe-based problem-solution approach to address and dispel challenges faced when implementing and using QGIS on a regular basis. The short, reusable recipes make concepts easy to understand and combine so you can build larger applications that are easy to maintain.

Features
  • Delve into the undocumented features of the QGIS API
  • Get a set of user-friendly recipes that can automate entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes
  • This video course has a complete code upgrade to QGIS 2.18
Course Length 3 hours 12 minutes
ISBN 9781788399685
Date Of Publication 29 May 2017

Authors

Joel Lawhead

Joel Lawhead is a PMI-certified Project Management Professional, a certified GIS Professional, and the Chief Information Officer of NVision Solutions Inc., an award-winning firm specializing in geospatial technology integration and sensor engineering for NASA, FEMA, NOAA, the US Navy, and many other commercial and non-profit organizations. Joel began using Python in 1997 and started combining it with geospatial software development in 2000. He has authored multiple editions of Learning Geospatial Analysis with Python and QGIS Python Programming Cookbook, both from Packt. He is also the developer of the open source Python Shapefile Library (PyShp) and maintains a geospatial technical blog, GeospatialPython, and Twitter feed, @SpatialPython.