7. The Processing Toolbox | Mastering QGIS

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Table Of Contents

Mastering QGIS

By : Kurt Menke, GISP

4.6 (12)

Mastering QGIS

4.6 (12)

By: Kurt Menke, GISP

Overview of this book

If you are a GIS professional, a consultant, a student, or perhaps a fast learner who wants to go beyond the basics of QGIS, then this book is for you. It will prepare you to realize the full potential of QGIS.

Preface

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Free Chapter

1. A Refreshing Look at QGIS

1. A Refreshing Look at QGIS

QGIS download and installation

Tour of QGIS

Loading data

Working with coordinate reference systems

Working with tables

Editing data

Composing maps

Adding functionality with plugins

Summary

2. Creating Spatial Databases

2. Creating Spatial Databases

Fundamental database concepts

Creating a spatial database

Importing data into a SpatiaLite database

Exporting tables out of SpatiaLite as a shapefile

Managing tables

Creating queries and views

Summary

3. Styling Raster and Vector Data

3. Styling Raster and Vector Data

Choosing and managing colors

Managing color ramps

Styling single band rasters

Styling multiband rasters

Creating a raster composite

Raster color rendering

Raster resampling

Styling vectors

Vector layer rendering

Using diagrams to display thematic data

Saving, loading, and setting default styles

Summary

4. Preparing Vector Data for Processing

4. Preparing Vector Data for Processing

Merging shapefiles

Creating spatial indices

Checking for geometry errors

Converting vector geometries

Using basic vector geoprocessing tools

Defining coordinate reference systems

Advanced field calculations

Complex spatial and aspatial queries

Summary

5. Preparing Raster Data for Processing

5. Preparing Raster Data for Processing

Reclassifying rasters

Rescaling rasters

Creating a raster mosaic

Generating raster overviews (pyramids)

Converting between raster and vector data models

Creating raster surfaces via interpolation

Summary

6. Advanced Data Creation and Editing

6. Advanced Data Creation and Editing

Creating points from coordinate data

Geocoding address-based data

Georeferencing imagery

Checking the topology of vector data

Repairing topological errors via topological editing

Summary

7. The Processing Toolbox

7. The Processing Toolbox

About the processing toolbox

Performing raster analyses with GRASS

SAGA

Exploring hydrologic analyses with TauDEM

R

Summary

8. Automating Workflows with the Graphical Modeler

8. Automating Workflows with the Graphical Modeler

An introduction to the graphical modeler

Opening the graphical modeler

Configuring the modeler and naming a model

Adding inputs

Adding algorithms

Running a model

Editing a model

Documenting a model

Saving, loading, and exporting models

Executing model algorithms iteratively

Nesting models

Using batch processing with models

Converting a model into a Python script

Summary

9. Creating QGIS Plugins with PyQGIS and Problem Solving

9. Creating QGIS Plugins with PyQGIS and Problem Solving

Webography - where to get API information and PyQGIS help

The Python Console

Exploring iface and QGis

Exploring a QGIS API in the Python Console

Creating a plugin structure with Plugin Builder

A simple plugin example

Setting up a debugging environment

Debugging session example

Summary

10. PyQGIS Scripting

10. PyQGIS Scripting

Where to learn Python basics

Loading layers

Vector structure

Iterating over features

Editing features

Running processing toolbox algorithms

Running an external algorithm or command

Interacting with the map canvas

Summary

Index

Index

SAGA

The SAGA (short form for System for Automated Geoscientific Automation) environment contains powerful tools, some of which have very specific applications; for example, geostatistical analyses and fire or erosion modeling. However, we will explore some of the SAGA tools that have broader applications and often dovetail nicely with tools from other providers. Similar to GRASS, integrating the SAGA algorithms within the processing toolbox provides access to powerful tools within a single interface.

To explore some of the SAGA algorithms available through the toolbox, we will work through a hypothetical situation and perform the analysis to evaluate the potential roosting habitat for the Northern Spotted Owl.

We are going to continue using data from the provided ZIP file, and we will need the following files:

Elevation file (dems_10m.dem available in the GRASS data folder)
Hillshade file (hillshade.tif created in the GRASS section)
Boundary file (crlabndyp.shp)
Surface water file (hydp.shp)
Land...

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Programming languages

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