QGIS Python Programming Cookbook

Book Image

QGIS Python Programming Cookbook

Book Image

QGIS Python Programming Cookbook

Overview of this book

QGIS Python Programming Cookbook

QGIS Python Programming Cookbook

Credits

About the Author

About the Author

About the Reviewers

About the Reviewers

www.PacktPub.com

www.PacktPub.com

Preface

Free Chapter

Automating QGIS

Automating QGIS

Installing QGIS for development

Using the QGIS Python console for interactive control

Using the Python ScriptRunner plugin

Setting up your QGIS IDE

Debugging QGIS Python scripts

Navigating the PyQGIS API

Creating a QGIS plugin

Distributing a plugin

Creating a standalone application

Storing and reading global preferences

Storing and reading project preferences

Accessing the script path from within your script

Querying Vector Data

Querying Vector Data

Loading a vector layer from a file sample

Loading a vector layer from a spatial database

Examining vector layer features

Examining vector layer attributes

Filtering a layer by geometry

Filtering a layer by attributes

Buffering a feature intermediate

Measuring the distance between two points

Measuring the distance along a line sample

Calculating the area of a polygon

Creating a spatial index

Calculating the bearing of a line

Loading data from a spreadsheet

Editing Vector Data

Editing Vector Data

Creating a vector layer in memory

Adding a point feature to a vector layer

Adding a line feature to a vector layer

Adding a polygon feature to a vector layer

Adding a set of attributes to a vector layer

Adding a field to a vector layer

Joining a shapefile attribute table to a CSV file

Moving vector layer geometry

Changing a vector layer feature's attribute

Deleting a vector layer feature

Deleting a vector layer attribute

Reprojecting a vector layer

Converting a shapefile to KML

Merging shapefiles

Splitting a shapefile

Generalizing a vector layer

Dissolving vector shapes

Performing a union on vector shapes

Rasterizing a vector layer

Using Raster Data

Using Raster Data

Loading a raster layer

Getting the cell size of a raster layer

Obtaining the width and height of a raster

Counting raster bands

Swapping raster bands

Querying the value of a raster at a specified point

Reprojecting a raster

Creating an elevation hillshade

Creating vector contours from elevation data

Sampling a raster dataset using a regular grid

Adding elevation data to line vertices using a digital elevation model

Creating a common extent for rasters

Resampling raster resolution

Counting the unique values in a raster

Mosaicing rasters

Converting a TIFF image to a JPEG image

Creating pyramids for a raster

Converting a pixel location to a map coordinate

Converting a map coordinate to a pixel location

Creating a KML image overlay for a raster

Classifying a raster

Converting a raster to a vector

Georeferencing a raster from control points

Clipping a raster using a shapefile

Creating Dynamic Maps

Creating Dynamic Maps

Accessing the map canvas

Changing the map units

Iterating over layers

Symbolizing a vector layer

Rendering a single band raster using a color ramp algorithm

Creating a complex vector layer symbol

Using icons as vector layer symbols

Creating a graduated vector layer symbol renderer

Creating a categorized vector layer symbol

Creating a map bookmark

Navigating to a map bookmark

Setting scale-based visibility for a layer

Using SVG for layer symbols

Using pie charts for symbols

Using the OpenStreetMap service

Using the Bing aerial image service

Adding real-time weather data from OpenWeatherMap

Labeling features

Changing map layer transparency

Adding standard map tools to the canvas

Using a map tool to draw points on the canvas

Using a map tool to draw polygons or lines on the canvas

Building a custom selection tool

Creating a mouse coordinate tracking tool

Composing Static Maps

Composing Static Maps

Creating the simplest map renderer

Using the map composer

Adding labels to a map for printing

Adding a scale bar to the map

Adding a north arrow to the map

Adding a logo to the map

Adding a legend to the map

Adding a custom shape to the map

Adding a grid to the map

Adding a table to the map

Adding a world file to a map image

Saving a map to a project

Loading a map from a project

Interacting with the User

Interacting with the User

Using log files

Creating a simple message dialog

Creating a warning dialog

Creating an error dialog

Displaying a progress bar

Creating a simple text input dialog

Creating a file input dialog

Creating a combobox

Creating radio buttons

Creating checkboxes

Stepping the user through a wizard

Keeping dialogs on top

QGIS Workflows

Creating an NDVI

Geocoding addresses

Creating raster footprints

Performing network analysis

Routing along streets

Creating a mapbook

Finding the least cost path

Performing nearest neighbor analysis

Creating a heat map

Creating a dot density map

Collecting field data

Computing road slope using elevation data

Geolocating photos on the map

Image change detection

Other Tips and Tricks

Other Tips and Tricks

Creating tiles from a QGIS map

Adding a layer to geojson.io

Rendering map layers based on rules

Creating a layer style file

Using NULL values in PyQGIS

Using generators for layer queries

Using alpha values to show data density

Using the __geo_interface__ protocol

Generating points along a line

Using expression-based labels

Creating dynamic forms in QGIS

Calculating length for all selected lines

Using a different status bar CRS than the map

Creating HTML labels in QGIS

Using OpenStreetMap's points of interest in QGIS

Visualizing data in 3D with WebGL

Visualizing data on a globe

Index

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Classifying a raster

Image classification is one of the most complex aspects of remote sensing. While QGIS is able to color pixels based on values for visualization, it stops short of doing much classification. It does provide a Raster Calculator tool where you can perform arbitrary math formulas on an image, however it does not attempt to implement any common algorithms. The Orfeo Toolbox is dedicated purely to remote sensing and includes an automated classification algorithm called K-means clustering, which groups pixels into an arbitrary number of similar classes to create a new image. We can do a nice demonstration of image classification using this algorithm.

Getting ready

For this recipe, we will use a false color image which you can download here:

https://geospatialpython.googlecode.com/files/FalseColor.zip

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

How to do it...

All we need to do is run the algorithm on our input image. The important parameters are the...