QGIS Python Programming Cookbook, Second Edition

QGIS Python Programming Cookbook, Second Edition - Second Edition

By : Joel Lawhead

Buy this Book

QGIS Python Programming Cookbook, Second Edition - Second Edition

By: Joel Lawhead

Buy this Book

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.

QGIS Python Programming Cookbook - Second Edition

Credits

About the Author

About the Reviewer

www.PacktPub.com

Customer Feedback

Preface

Free Chapter

Automating QGIS

Introduction

Installing QGIS 2.18 for development

Using the QGIS Python console for interactive control

Automatically starting the Python console

Using the Python's Script Runner plugin

Setting up your QGIS IDE

Debugging QGIS Python scripts

Navigating the PyQGIS API

Creating a traditional QGIS plugin

Creating a Processing Toolbox plugin

Distributing a plugin

Building a standalone application

Storing and reading global preferences

Storing and reading project preferences

Accessing the script path from within your script

Querying Vector Data

Introduction

Loading a vector layer from a file sample

Loading a vector layer from a geodatabase

Examining vector layer features

Examining vector layer attributes

Filtering a layer by geometry

Filtering a layer by attributes

Buffering a feature

Measuring the distance between two points

Measuring distance along a line

Calculating the area of a polygon

Creating a spatial index

Calculating the bearing of a line

Loading data from a spreadsheet

Accessing layer metadata

Editing Vector Data

Introduction

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

Changing vector layer geometry

Changing a vector layer feature's attribute

Removing data from a vector layer

Deleting a vector layer feature's attribute

Reprojecting a vector layer

Converting a shapefile to KML or GeoJSON

Merging shapefiles

Splitting a shapefile

Generalizing a vector layer

Dissolving vector features

Performing a union on vector shapes

Rasterizing a vector layer

Exporting a layer to the GeoPackage format

Using Raster Data

Introduction

Loading a raster layer

Loading a NetCDF file

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 a 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

Introduction

Accessing the map canvas

Changing the map units

Iterating over layers

Symbolizing a vector layer

Setting a transparent layer fill

Using a filled marker symbol

Rendering a single band raster using a color ramp algorithm

Setting a feature's color using a column in a CSV file

Creating a complex vector layer symbol

Using icons as vector layer symbols

Using an outline for font markers

Using arrow symbols

Creating a graduated vector layer symbol renderer

Creating a categorized vector layer symbol

Using live layer effects

Creating inverted polygon shapeburst fills

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 2.5D renderer

Using XYZ tiled map services

Using Esri ArcGIS map services

Labeling a feature

Using null symbols

Change 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

Introduction

Creating the simplest map renderer

Using the Map Composer

Adding labels to a map for printing

Adding a scale bar to a map

Adding a North arrow to the map

Adding a logo to the map

Adding a vertical legend to the map

Adding a horizontal legend

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

Introduction

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

Creating a dock widget

Displaying a message in the status bar

Pushing messages to the message bar

Pushing widgets to the message bar

Creating tabs

Stepping the user through a wizard

Keeping dialogs on top

QGIS Workflows

Introduction

Creating an NDVI

Geocoding addresses

Creating raster footprints

Performing network analysis

Routing along streets

Tracking a GPS

Creating a mapbook

Finding the least cost path

Performing nearest neighbor analysis

Creating a DEM from LIDAR

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

Adjusting imprecise building footprints

Visualizing multitemporal data

Other Tips and Tricks

Introduction

Creating tiles from a QGIS map

Adding a layer to geojson.io

Rendering map layers based on rules

Creating a layer-definition file

Using NULL values in PyQGIS

Using generators for layer queries

Using alpha values to show data density

Using the __geo_interface__ protocol

Getting the output file names from processing algorithms

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 points of interest in QGIS

Changing the QGIS web proxy

Running QGIS scripts as scheduled tasks

Visualizing data in 3D with WebGL

Visualizing data on a globe

Make a globe-like azimuthal orthographic projection

Animating a layer

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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://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...

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

QGIS Python Programming Cookbook, Second Edition - Second Edition

By : Joel Lawhead

QGIS Python Programming Cookbook, Second Edition - Second Edition

By: Joel Lawhead

Overview of this book

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