Online Course Qgis – This is an introductory course that covers QGIS from the basics. You will learn to use QGIS for mapping, spatial data processing and spatial analysis. This class is ideal for participants with a basic knowledge of GIS and who want to learn how to use QGIS to perform everyday GIS tasks.

The exercises and challenges in this course4 use a variety of data sets. All required datasets are supplied in the

Table of Contents

Online Course Qgis

We will use several toolbars in this course. To make sure you have the necessary tools for the exercises, go to

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This section is designed to help you become familiar with the basic workflow of importing data layers, applying symbology, adding labels, and designing layouts for maps. We will take a text file containing historical records of earthquakes and turn it into an informative visualization like the one below.

Note: Windows users may need to change the File Type to All in the Select Delimited Text File to Open dialog to view the TSV file.

We have now finished the first part of this exercise. Your output should match the content of the

The symbology of a layer is its visual appearance on the map. We will now learn different techniques to style each layer to convey the information visually.

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The default Scaling method used by QGIS is Flannery. This method applies non-linear scaling to compensate for human perception of areas. Learn more. ↗

We have now finished the second part of this exercise. Your output should match the content of the

, etc., to each symbol. This takes your symbol to the next level and helps highlight certain features. Select the

Tags are a useful way to convey additional information about certain functions. Labels are associated with each feature and can be configured to display information from the attributes. We will now add labels to each of the large earthquake hotspots to show the name of the location as well as the deaths caused by that earthquake.

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Note: Changing the Project CRS does not change the CRS of the layers, but reprojects them on the fly to the selected CRS for display.

We have now finished the third part of this exercise. Your output should match the content of the

The numbers displayed in the labels can be difficult to read because they are not formatted. We can make them readable by adding a mil separator. So a number like for example

. Update the expression for the labels so the numbers are formatted. To achieve this, you can use the

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QGIS comes with a rich set of tools for creating map layouts that allow you to add elements such as labels, images, legends, scale bar, north arrow, etc., to your map. It also allows you to export the map layout as an image or PDF. We will now take the visualization created in the QGIS map canvas and create a print layout. 1. Go to

Below Although useful, this can have an unexpected effect on the output. Uncheck it during the export.

In this section, we will learn basic data processing and visualization techniques. We will use geographic boundaries and population count data for the City of New York and create a population density map. This requires doing a table join and using a graduated symbol to create a choropleth map.

We have now finished the first part of this exercise. Your output should match the content of the

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Georeferencing is the process of assigning real-world coordinates to each pixel of the raster. This is an important step in preparing your data for further analysis. Many projects, especially machine learning projects – need continuous historical records to build a model. Many of the older datasets may come in the form of scanned maps or aerial photographs that must be georeferenced. Similarly, some organizations may only share a PDF or static map image of the dataset, which will need to be converted into a GIS-ready format using a georeferencing process.

Georeferencing process involves collecting GCPs (Ground Control Points) or Tie-Points. These GCPs are easily identifiable features in the image or map whose real-world coordinates are obtained from a field survey using a GPS device or identified from already georeferenced sources within a GIS.

In this exercise, you will georeference an old scanned map of Bangalore, India created in 1924. This map may be hand-drawn and has no coordinate markers, so we will use a tiled basemap layer to locate the features and get the GCPs.

You will see a warning against using contributed services. Some of these services may have restrictions on their usage and/or attribution requirements that you must follow. Please review them before using them in your project.

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Load the Stamen Watercolor basemap by Stamen. This is an award-winning basemap that presents OpenStreetMap data in hand-painted watercolor.

In this section, you will learn how to load a scanned image, collect GCPs (ground control points) and warp the image to create a GeoTiff file.

We have now completed all the steps and you should have a georeferenced image. Your output should match the content of the

File in the solutions directory. We have also provided the stored GCPs in the solutions folder. To load them, you can go to

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In this exercise we used the Polynomial 2 technique. For datasets that require more aggressive transformation, you can use the Thin Plate Spline algorithm. This method is also known as

. Change the transform setting to use Thin Plate Split and run the georeferencer again. Compare the output with the previous result.

Many GIS tasks require editing existing data layers or creating new data sets. Often a large amount of GIS time is spent digitizing raster data to create vector layers that you use in your analysis. Many machine learning projects also require creating a labeled dataset, which must be done by digitizing features from satellite images or historical maps. QGIS has powerful on-screen digitizing and editing capabilities that we will explore in this tutorial.

In this exercise, you will create a vector layer of historic lakes in the city of Bangalore, India. This city experienced rapid urbanization. Due to this, many water bodies were lost. We will use the georeferenced scanned map from the previous exercise to digitize polygons for all water bodies in 1924 and label their current state. Finally, we will create a vector layer and assign them attributes, indicating whether they are healthy, lost or partially lost.

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We will first create a new layer and set the attribute shape to capture the data about the features.

The fid column contains an auto-incrementing unique identifier for each feature. The GeoPackage format requires this integer field to maintain data integrity. Manually overwriting this identifier to a different value may cause data corruption. Edit the attribute form for the trust field so that it is not user editable.

Geoprocessing refers to the set of operations used to transform the input data to create a new dataset. This section will learn about some essential vector and raster geoprocessing tools for solving a complex spatial analysis problem.

In this analysis, we will learn how to download vector data from OpenStreetMap and use it to determine the number of people who live within 1 km of a metro station.

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Note use of IS NOT operator instead of !=. The reason is that these columns contain NULL records. NULL is not a value that cannot be equal or not equal to another value. The IS NOT operator will match all records that do not match the value, including NULL records.

We have now completed the data download and pre-processing steps. Your output should match the content of the

A layer has many columns. Open the attribute table and delete all columns except the fid and osm_id columns. Hint: Use the

With the location of all bars within the city. Select all pubs from the layer within 1 km of a metro station. Tip: Use the Select by Location tool from the Processing Toolbox.

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We will now use a population grid and overlay the buffer polygon to calculate the number of people who live within the buffer zone.

Layer to calculate the total population of the city. Determine what percentage of the city’s population lives within 1 km of a metro station.

This course material is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. You are free to reuse and adapt the material, but you must give proper credit to the original author as below:

This course is offered as an instructor-led online class. Visit Spatial Thoughts to know details of upcoming sessions. We recently took our entire Environmental Quantum GIS (QGIS) training course and offered it free to the internet as Youtube videos for anyone who wants to learn to use this free and open source desktop mapping program. . This also includes the data and training manuals that can be made available to you if you call us at training@. Just click on the image below to go to the Youtube channel and get started!

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You can start with our prerequisite videos that cover how to install the software (version 2.18 is the recommended Long Term Release (LTR) for a while yet) and use

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