Book Image

Mastering Geospatial Analysis with Python

By : Silas Toms, Paul Crickard, Eric van Rees
Book Image

Mastering Geospatial Analysis with Python

By: Silas Toms, Paul Crickard, Eric van Rees

Overview of this book

Python comes with a host of open source libraries and tools that help you work on professional geoprocessing tasks without investing in expensive tools. This book will introduce Python developers, both new and experienced, to a variety of new code libraries that have been developed to perform geospatial analysis, statistical analysis, and data management. This book will use examples and code snippets that will help explain how Python 3 differs from Python 2, and how these new code libraries can be used to solve age-old problems in geospatial analysis. You will begin by understanding what geoprocessing is and explore the tools and libraries that Python 3 offers. You will then learn to use Python code libraries to read and write geospatial data. You will then learn to perform geospatial queries within databases and learn PyQGIS to automate analysis within the QGIS mapping suite. Moving forward, you will explore the newly released ArcGIS API for Python and ArcGIS Online to perform geospatial analysis and create ArcGIS Online web maps. Further, you will deep dive into Python Geospatial web frameworks and learn to create a geospatial REST API.
Table of Contents (23 chapters)
Title Page
Copyright and Credits
Packt Upsell
Geoprocessing with Geodatabases

Chapter 8. Automating QGIS Analysis

This book has introduced you to using Python from the command line, in a Jupyter Notebook, and in an IDE to perform geospatial tasks. While these three tools will allow you to accomplish your tasks, there are many times when work needs to be done using desktop GIS software.

QGIS, a popular open source GIS application, provides desktop GIS functionality with the ability to work in a Python console and the ability to write toolboxes and plugins using Python. In this chapter, you will learn how to manipulate desktop GIS data using Python and how to automate these tasks using toolboxes and plugins.

In this chapter, you will learn how to:

  • Load and save layers
  • Create layers from API data sources
  • Add, edit, and delete features
  • Select specific features
  • Call geoprocessing functions
  • Write geoprocessing toolboxes
  • Write plugins