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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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Converting a map coordinate to a pixel location


When you receive a map coordinate as user input or from some other source, you must be able to convert it back to the appropriate pixel location on a raster.

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...

Similar to the previous recipe, we will define a function, extract the GDAL GeoTransform object from our raster, and use it for the conversion.

  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 coordinate to pixel conversion. We get the GDAL GeoTransform object containing the raster georeferencing information and the map x, y coordinates:

            def world2Pixel(geoMatrix, x, y): 
                ulX = geoMatrix[0] 
                ulY = geoMatrix[3] 
                xDist = geoMatrix...

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