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
About the Author
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Counting the unique values in a raster

Remotely-sensed images are not just pictures; they are data. The value of the pixels has a meaning that can be automatically analyzed by a computer. The ability to run statistical algorithms on a dataset is the key to remote sensing. This recipe counts the number of unique combinations of pixels across multiple bands. A use case for this recipe will be to assess the results of image classification, which is a recipe that we'll cover later in this chapter. This recipe is in contrast to the typical histogram function, which totals the unique values and the frequency of each value per band.

Getting ready

We will use the SatImage raster available at

Place this raster in your /qgis_data/rasters directory.

How to do it...

This algorithm relies completely on the numpy module. Numpy can be accessed through the GDAL package's gdalnumeric module. To do this, we need to perform the following steps:

  1. Start...