Book Image

QGIS Python Programming Cookbook, Second Edition - Second Edition

By : Joel Lawhead
Book Image

QGIS Python Programming Cookbook, Second Edition - Second Edition

By: Joel Lawhead

Overview of this book

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 book 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 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.
Table of Contents (16 chapters)
QGIS Python Programming Cookbook - Second Edition
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Converting a pixel location to a map coordinate


The ability to view rasters in a geospatial context relies on the conversion of pixel locations to coordinates on the ground. Sooner or later, when you use Python to write geospatial programs, you'll have to perform this conversion yourself.

Getting ready

We will use the SatImage raster available at https://github.com/GeospatialPython/Learn/raw/master/SatImage.zip

Place this raster in your /qgis_data/rasters directory.

How to do it...

We will use GDAL to extract the information needed to convert pixels to coordinates and then use pure Python to perform the calculation. We'll use the center pixel of the image as the location to convert.

  1. Start QGIS.

  2. From the Plugins menu, select Python Console.

  3. We need to import the gdal module:

            from osgeo import gdal 
    
  4. Then, we need to define the reusable function that does the conversion as accepting a GDAL GeoTransform object, containing the raster georeferencing information and the pixel's x, y values:

       ...