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QGIS Python Programming Cookbook, Second Edition

QGIS Python Programming Cookbook, Second Edition

By : Joel Lawhead
1.5 (2)
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QGIS Python Programming Cookbook, Second Edition

QGIS Python Programming Cookbook, Second Edition

1.5 (2)
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 (10 chapters)
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Creating pyramids for a raster


Pyramids, or overview images, sacrifice the disk space for map rendering speed by storing resampled, lower-resolution versions of images in the file alongside the full resolution image. Once you have finalized a raster, building pyramid overviews is a good idea.

Getting ready

For this recipe, we will use a false-color image, which you can download from https://github.com/GeospatialPython/Learn/raw/master/FalseColor.zip.

Unzip this .tif file and place it in your /qgis_data/rasters directory.

How to do it...

The Processing Toolbox has a dedicated algorithm for building pyramid images. Perform the following steps to create pyramids for a raster:

  1. Start QGIS.

  2. From the Plugins menu, select Python Console.

  3. Import the processing module:

            import processing 
    
  4. Run the gdalogr:overviews algorithm, specifying the process name, input image, overview levels, the option to remove existing overviews, resampling method (0 is the nearest neighbor), and overview format (1 is internal...

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