Introduction

This class focuses on techniques for the automation of GIS workflows. You will learn techniques that will help you be more productive, create beautiful visualizations and solve complex spatial analysis problems. This class is ideal for participants who already use QGIS and want to take their skills to the next level.

Below are the topics covered in this class

Before we do the exercises, it will help you to learn a bit more about open-source and how the QGIS project operates.

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Software

This course requires QGIS LTR version 3.22.

Please review QGIS-LTR Installation Guide for step-by-step instructions.

Get the Data Package

The examples in this class use a variety of datasets. All the required layers, project files etc. are supplied to you in the advanced_qgis.zip file along with your class materials. Unzip this file to the Downloads directory.

Not enrolled in our instructor-led class but want to work through the material on your own? Get free access to the data package

Concept: Processing Framework

QGIS 2.0 introduced a new concept called Processing Framework. Previously known as Sextante, the Processing Framework provides an environment within QGIS to run native and third-party algorithms for processing data. It is now the recommended way to run any type of data processing and analysis within QGIS - including tasks such as selecting features, altering attributes, saving layers etc. - that can be accomplished by other means. But leveraging the processing framework allows you to be more productive, fast, and less error-prone.

The Processing Framework consists of the following distinct elements that work together.

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We will learn about each of these through hands-on exercises in the following sections.

1. Using Processing Toolbox

This exercise aims is to show how a multi-step spatial analysis problem can be solved using a purely processing-based workflow. This exercise also shows the richness of available algorithms in QGIS that can do sophisticated operations that previously needed plugins or were more complex.

We will work with roads extracted from OpenStreetMap for the state of Karnataka in India. The admin boundary for the state and the districts come from DataMeet.

1.1 Extract, Transform and Load

We will learn about some useful processing algorithms for basic data processing operations such as Extract, Transform and Load (ETL). Our goal for this section is to read a road layer and a boundary layer from a GeoPackage and calculate what is the total length of the national highways in a state. We will also see how to append the resulting layer to same GeoPackage.

  1. Browse to the data directory and expand karnataka.gpkg. Drag and drop the karnataka, karnataka_districts and karnataka_major_roads layers to the canvas.

  1. The layer karnataka_major_roads contain all major roads, including national highways, state highways, major arterial roads etc. Select the layer and use the keyboard shortcut F6 to open the attribute table.

  1. You will notice that the ref column has information about road designation. As we are interested in only national highways, we can use the information in this column to extract relevant road segments.

  1. You can use tools such as Select by expression, export the selected features as a new layer and continue to work. But the processing toolbox providers a much seamless workflow. Search for the algorithm Extract by expression.

  1. Enter the following expression to extract the features where the value of the ref field starts with the letters NH.

We are using Regular Expression (or RegEx) to match the field value to a specific pattern. Regular expressions are quite powerful and can be used for many complex data filtering operations. Here’s a good tutorial that explains the basics of regular expressions.

regexp_match("ref", '^NH')

  1. You will get a new layer Matching Features in the Layers Panel. Next, we want to calculate the length of each segment. You can use the built-in algorithm Add geometry attributes

  1. The source layer is in the Geographic CRS EPSG:4326. But for the analysis, we want the lengths to be measured in meters/kilometers. The algorithm provides us with a handy option to calculate the distances in Elliposidal math - which is ideal for layers in the geographic CRS.

  1. A new layer with an additional field called length will be added to the Layers panel. The distances in this field are in meters. Let’s convert them to kilometers. You may reach out to the trusty QGIS field calculator to add a new field. That’s a perfectly valid way - but as mentioned earlier, there is a processing way to do things which is the preferred way. Search and open the Field Calculator processing algorithm instead and enter the following expression.
"length"/1000

  1. A new layer with the field length_km will be added to the Layers panel. Now we are ready to find out the answer. We just need to sum up the values in the length_km field. Use the Basic Statistics for Fields algorithm.

  1. In the Basic Statistics for Fields dialog, select Calculated as the Input layer and length_km as the Field to calculate statistics on. Click Run.

  1. The result is a table of different statistics on the column. As the result is not a layer, it will be displayed in the Results Viewer. The panel will contain the link to an HTML file containing the statistics. The Sum contains the total length of national highways in the state.

What do you think of the results? The resulting number may not be perfect because the OpenStreetMap database may have missing roads or are classified differently. But it is close to the number provided in the official statistics.

  1. The final layer is called Calculated and is a temporary memory layer. Let’s save it to the disk so we can use it later. The layer contains many fields which are not relevant to us, so let’s delete some columns before saving them. The classic way to do this is to toggle editing and use the Delete Column button from the Attribute Table. If you wanted to rename/reorder certain fields, that needed a plugin. But now, we have a really easy processing algorithm called Refactor Fields that can add, delete, rename, re-order and change the field types all at once. Delete fields that are not required and save the result as the layer national_highways in the source karnataka.gpkg.

  1. The layer national_highways will be added to the Layers panel.

We have now finish the first part of this exercise. Your output should match the contents of the Processing_Tools_Checkpoint1.qgz file in the solutions folder.

1.1.1 Challenge

There are many features in the national_highways layer where the "name" attribute is NULL. Find an appopriate algorithm from the Processing Toolbox to create a new layer with the features having NULL values removed.

1.2 Spatial Join and Summary Statistics

We achieved the goal of the exercise, but we can explore the results a bit better if we can break down the results into a smaller administrative unit. Let’s try to calculate the length of national highways for each district in the state. This will require us to perform a spatial join and analyze the results using group statistics.

  1. Add the karnataka_districts layer from the karnataka.gpkg file. This layer contains the geometry of each district along with its name in the DISTRICT field.

  1. To add the name of the district to the roads layer, we need to perform a spatial-join. This is done using the Join attributes by Location algorithm. Search and locate the tool in the toolbox. Double-click to open it. Select the national_highways as the input layer and do a one-to-one join with the karnataka_districts layer. Select only the DISTRICT field to be added to the output.

  1. The new layer Joined layer now has the intersecting district name in the DISTRICT field. We can now sum the road lengths and group them for each district. You may recall that in earlier versions of QGIS, you needed a plugin called Group Stats to do this. But now we can do this via the built-in Statistic by Categories algorithm. Select the Joined layer as the Input vector layer, length_km as the Field to calculate statistics on. Select the DISTRICT field as the Field(s) with Categories.

  1. Save the layer to the karnataka.gpkg as a layer named national_highways_by_districts. Click Run.

  1. The output of the algorithm is a table containing various statistics on the length_km column for each district. The values in the Sum column is the total length of national highways in the district.

Note that we did data processing, spatial analysis and statistical analysis - all using just processing algorithms in a fast, reproducible and intuitive workflow. We have now finish the first part of this exercise. Your output should match the contents of the Processing_Tools_Checkpoint2.qgz file in the solutions folder.

1.2.1 Challenge

Apply the following formatting changes on the national_highways_by_districts layer and save it to karnataka.gpkg as a new layer national_highways_by_districts_formatted.

  • Rename the DISTRICT field to district.
  • Rename the sum field to total_length.
  • Round the lengths in the total_length field to nearest integer using the round() function.
  • Delete all remaining fields.

Hint: You can apply an expression on a field in the Refactor Fields algorithm by entering it in the Source Expression column.

Learn more

Did you know there are over 1000 tools in the Processing Toolbox that can help you do many different tasks? Click on the image to see my video where I share a few of my favorites tools.

Video

2. Batch Processing

So far we have run the algorithm on 1 layer at a time. But each processing algorithm can also be run in a Batch mode on multiple inputs. This provides an easy way to process large amounts of data and automate repetitive tasks.

The batch processing interface can be invoked by right-clicking any processing algorithm and choosing Execute as Batch Process.

2.1 Clip Multiple Layers

We will take multiple country-level data layers and use the batch processing operation to clip them to a state polygon in a single operation.

  1. Open the batch_processing project.

  1. Next, right-click on the state boundary layer, and click Zoom to Layer.

  1. Now that we have centered on our area of interest, under the Processing menu and select toolbox. Now in Processing Toolbox, search for clip, under Vector overlay → Clip right-click and select Execute as Batch Process...

  1. In the Batch processing - Clip dialog box, click the Autofill… under the Input layer column and choose Select from Open Layers...

  1. Select all data layers except state_boundary and click OK.

  1. Under Overlay Layer select the state_boundary layer. Then click the drop-down button near Autofill… and choose to Fill Down. This will auto-populate all the Overlay Layer with the state_boundary layer.

  1. Under Clipped, select … button to add the output filenames.

  1. In the Save File dialog box, enter the File name as clipped_. This is just the prefix of the name that you will auto-complete in the next step. Select GPKG files (.gpkg) in Save as type. Click Save.

  1. Next, you will be prompted to choose the Autofill settings. Select to Fill with parameter values as the Autofill mode, and Input layer as the Parameter to use. Click OK.

  1. Note that each row has a different file name now. The output file name is the result of the chosen prefix and the autofill settings. Make sure the Load layers on completion box is checked and click Run.

  1. The resulting clipped layers will be added to the Layers panel. Turn off all previous layers in the Layers panel to see the results clearly. We can now combine all the clipped layers into a single geopackage file for ease of sharing. Now in the Processing Toolbox, search and select the Package Layers.

  1. In the Package Layers dialog box, in Input layers choose all the clipped layers and in Destination GeoPackage click … and select Save to File…. Then save the file as clipped.gpkg. Click Run

  1. Now a new clipped.gpkg geopackage layer will be created with all the clipped layers in it.

Your output should match the contents of the Batch_Processing_Checkpoint1.qgz file in the solutions folder.

2.1.1 Challenge

Reprojected all the clipped layers to a UTM projection. You can reproject all the layers to the CRS WGS84 / UTM zone 43N EPSG:32643. Save the reprojected layers to the same GeoPackage clipped.gpkg

3. Graphical Modeler

GIS Workflows typically involve many steps - with each step generating intermediate output that is used by the next step. If you change the input data or want to tweak a parameter, you will need to run through the entire process again manually. Fortunately, Processing Framework provides a graphical modeler that can help you define your workflow and run it with a single invocation. You can also run these workflows as a batch over a large number of inputs.

3.1 Workflow Automation

National Geospatial-Intelligence Agency’s Maritime Safety Information portal provides a shapefile of all incidents of maritime piracy in the form of Anti-shipping Activity Messages. We can create a density map by aggregating the incident points over a global hexagonal grid.

The steps needed to create a hex-bin layer suitable for visualization is as follows:

  • Reproject the input to an equal-area projection
  • Create a global hexagonal grid layer
  • Select all grids that intersect with at least 1 point
  • Count points within each grid

We will now learn how to build a model that runs the above processing steps in a single workflow.

  1. Open the maritime_piracy project.

  1. Launch the modeler from Processing → Graphical Modeler

  1. In the Processing Modeler dialog, locate the Model Properties panel. Enter piracy_hexbin as the Name of the model and projects as the Groups. Note that there is a History panel in the bottom left, which keeps track of all the work done in Model Builder. Click the Save button.

  1. Save the model as piracy_hexbin.model3. Also, check the folder in which it is being saved. Processing → models, from this location QGIS will read the model by default.

  1. Now, we can start building a graphical model of our processing pipeline. The Processing modeler dialog contains a left-hand panel and the main canvas. On the left-hand panel, locate the Inputs panel listing various types of input data types. Scroll down and select the + Vector Layer input. Drag it to the canvas.

  1. Enter Input Points as the Description and Point as the Geometry type. This input represents the piracy incidents point layer.

  1. Next, drag another + Vector Layer input to the canvas. Enter Base Layer as the Description and Polygon as the Geometry type. This input represents the natural earth global land layer in which we will use as the extent of the grid layer.

  1. As we are generating a global hexagonal grid, we can ask the user to supply us with the grid size as an input instead of hard-coding it as part of our model. This way, the user can quickly experiment with different grid sizes without changing the model at all. Select a + Number input and drag it to the canvas. Enter Grid Size as the Parameter name, Integer as the Number Type, 200000 as Default Value, and click OK.

  1. Now that we have our user inputs defined, we are ready to add processing steps. All of the processing algorithms are available to you under the Algorithms tab. The first step in our pipeline will be to reproject the base layer to the Project CRS. Search for the Reproject layer algorithm and drag it to the canvas.

  1. In the Reproject layer dialog, select Base Layer, by clicking the button under the Input Layer and select Model Input as the Input layer. Check the Use project CRS as the Target CRS. Click OK.

  1. In the Processing Modeler canvas, you will notice a connection appear between the + Base Layer input and the Reproject layer algorithm. This connection indicates the flow of our processing pipeline. The next step is to create a hexagonal grid. Now search for the Create grid algorithm and drag it to the canvas.

  1. In the Create grid dialog, choose Hexagon (polygon) as the Grid type. Select Algorithm Output by clicking the button under Grid extent and choose ‘Reprojected’ from the algorithm ‘Reproject Layer’ as the Grid extent.

  1. Select Model input by clicking the button under Horizontal Spacing and choose Grid Size as the Horizontal Spacing. Click OK.

  1. Select Model input by clicking the button under Vertical Spacing and choose Grid Size as the Vertical Spacing. Click OK.

  1. At this point, we have a global hexagonal grid. The grid spans the full extent of the base layer, including land areas and places where there are no points. Let us filter out those grid polygons where there are no input points. Search for Extract by location algorithm and drag it to the canvas.

  1. Select Algorithm Output from the icon below Extract features from. Now choose ‘Grid’ from the algorithm ‘Generate Grid’. Click … at the right end.

  1. Select Intersect by clicking the button, as Where the features(geometric predicate). And click the triangle button to go back to the previous window. Now click OK.

  1. Select Model input by clicking the button under By comparing to the features from and choose Input Points as By comparing to the features from. Click OK.

  1. Now, we have only those grid polygons that contain some input points. To aggregate these points, we will use Count points in polygon algorithm. Search and drag it to the canvas.

  1. Select Algorithm Output by clicking the button under Polygons and choose ‘Extracted (location)’ from algorithm ‘Extract by location’ for Polygons. Now, Select Model Input by clicking the button under Points and choose Input Points for Points. Type NUMPOINTS in Count field name. At the bottom, name the Count output layer as Aggregated. Click OK.

  1. The model is now complete. Click the Save button. If the model is saved, then a green notification will pop on the screen.

  1. Switch to the main QGIS window. You can find your newly created model in the Processing Toolbox under Models → projects → piracy_hexbin. Double-click to run the model.

  1. Our Base Layer is the ne_10m_land and the Input Points layer is ASAM_events. The Grid Size needs to be specified in the units of the selected CRS. Enter 100000 as the Grid Size. Grid size is in the unit of the current CRS, which is meters. Click Run to start the processing pipeline. Once the process finishes, click Close.

  1. You will see a new layer Aggregated loaded as the result of the model. As you explore, you will notice the layer contains an attribute called NUMPOINTS containing the number of piracy incidents points contained within that grid feature.

  1. To ensure that you are always able to reproduce your results, it is recommended to bundle the model in your project. The modeler interface has a button Save model in project. Click on it to embed the model in your QGIS project file.

  1. Once the model is embedded, Whenever you open the project, the model will be available to the user under the Project models in the Processing Toolbox.

Your output should match the contents of the Modeler_Checkpoint1.qgz file in the solutions folder.

3.1.1 Challenge

Add a step to extract the grid with the highest piracy incidents.

Hint: The expression maximum("NUMPOINTS") will give you the highest value contained in the "NUMPOINTS" field. Use it to build your complete expression.

Concept: Spatial Indexing

When you ran your model, you may have noticed a warning message No spatial index exists for the input layer, performance will be severely degraded. This is because certain spatial queries make use of a spatial index and QGIS warns you when having a spatial index can speed up your operations. PostGIS documentation has a good overview of spatial indexes and why they are important.

You can compare a spatial index to a book index. When you want to search for a particular term, rather than scanning each page sequentially, you can speed up your search by looking up the index and directly going to the pages where the word appears. Spatial indexes work in similarly. You spent the effort once to create the index and all subsequent operations can make use of it. When you create a spatial index, each feature’s bounding box is used to establish its relationship with other features. This is stored alongside the dataset and can be used by algorithms. When trying to determine spatial relationships, the algorithms speed-up the look-up using the following two-pass method:

  • Step 1: Use the spatial index to determine which target features’ bounding boxes intersect with the source feature’s bounding box. Since the spatial index already has computed this - this is very fast. The result is a list of candidate features.
  • Step 2: Now that there is a small subset of candidate features, iterate over them and use their full geometry to evaluate exact intersections.

For large datasets, this approach helps reduce the processing time significantly.

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3.2 Using Spatial Index

QGIS has built-in tools to create and use spatial indexes. Let’s see how we can create a spatial index for a layer and use it in our model.

  1. Double click on the piracy_hexbin model from Processing Toolbox, select ne_10m_land as Base Layer, 200000 as Grid size and ASAM_events as Inputs Points. Click Run.

  1. Switch to Log, and note down the execution time of the model. In this instance we got 34.80 seconds (The exact time will vary depending on your computer configuration). Also note that it prompts a warning No spatial index exists for input layer, performance will be severely degraded.

  1. To create spatial index right-click the Aggregated layer and select Properties.

  1. In the Layer Properties dialog, switch to the Source tab. You will see the Create Spatial Index button. This button indicates that this layer does not currently have a spatial index. Click that button to create a spatial index. But we will use a better and more scalable way. Click OK and close the Layer Properties dialog.

  1. Go to Processing → Toolbox. Search for the algorithm Vector general → Create spatial index and double-click to launch it.

  1. Select Aggregated layer as the Input layer and click Run.

  1. Creating a spatial index is usually a fast operation. Once the algorithm finishes, right-click on the Aggregated layer and select Properties. Switch to the Source tab and you will see that the button has now changed to Spatial Index Exists - indicating that the layer now has a spatial index.

  1. While creating a spatial index on a layer like this is useful, it is even more powerful to have the spatial index created during the execution of our model. We will see how to add the spatial index creation step in our model. Right-click the piracy_hexbin model and select Edit Model…. Search Create spatial index in Algorithms tab and drag it to the model canvas.

  1. Choose Algorithm output from the button below Input Layer, and select “Grid” from algorithm “Create Grid”. Click OK.

  1. You will see that the newly added Create spatial index algorithm is connected to the Create grid algorithm. But the workflow should be, Create grid → Create spatial index → Extract from location.

  1. Right-click the Extract by location layer and select Edit. In Extract features from select “Indexed Layer” from algorithm “Create spatial index”.

  1. Now you will see the model diagram updated and the connection changed between the Create Grid and Extract by location layer. Click Save model.

  1. Now return to the main canvas and select piracy_hexbin model.

  1. Select ne_10m_land as Base Layer, 200000 as Grid size and ASAM_events as Inputs Points. Click Run.

  1. In this instance we got 3.39 seconds (The exact time will vary depending on your computer configuration). Also, note that it has executed 5 algorithms which is including creating the spatial index.

Your output should match the contents of the Modeler_Checkpoint2.qgz file in the solutions folder.

3.2.1 Challenge

Can you change the model so that instead of entering the grid size in meters, the user can enter the size in kilometers?

Hint: The Create Grid algorithm expects the size in meters, so you will have to convert the input to meters. Instead of using Model Input, use Pre-calculated Value to enter an expression.

3.3 Enabling Reproducible Workflows

GeoPackage is an open and flexible data format that makes data management simple. We saw how you can package multiple layers in a GeoPackage. We will now learn how to embed QGIS projects inside of a goepackage.

QGIS projects contain information of layer configuration, symbology, label positions and even models. We can make the reproducing your workflow even easier by embedding the QGIS Project in the same geopackage containing the source layers.

  1. Now, lets save this project in martime_piracy.gpkg geopackage. Click Project → Save To → GeoPackage….

  1. In the Save project to GeoPackage dialog box, click … to browse to martime_piracy geopackage.

  1. Enter project name as martime_piracy and click OK.

  1. Now in Browser, under martime_piracy.gpkg the project is saved. You now have just 1 GeoPackage file that contains all your input layers, styles, project and models. Sharing this 1 file will enable anyone to reproduce your output using the embedded model and layers.

Your can load the Modeler_Checkpoint3.qgz project contained in the maritime_piracy.gpkg in the solutions folder. (check the martime_piracy.gpkg)

4. 2D Animations

Time is an important component of many spatial datasets. Along with location information, time providers another dimension for analysis and visualization of data. If you are working with a dataset that contains timestamps or have observations recorded at multiple time-steps, you can easily visualize it using the Temporal Controller in QGIS 3.14 or above.

4.1 Animated Temporal Navigation

We will continue to work with the maritime piracy dataset. First, we will create a heatmap visualization and then animate the heatmap to show how the piracy hot-spots have changed over the past 2 decades.

  1. Open the maritime_piracy project from the data package. There are thousands of incidents and it is difficult to determine with more piracy. Rather than individual points, a better way to visualize this data is through a heatmap. Select the ASAM_events layers and click the Open the layer Styling Panel button in the Layers panel. Click the Single symbol drop-down.

  1. In the renderer selection drop-down, select Heatmap renderer. Next, select the Viridis color ramp from the Color ramp selector. Adjust the Radius value to 5.0. At the bottom, expand the Layer Rendering section and adjust the opacity to 75.0%. This gives a nice visual effect of the hotspots with the land layer below.

  1. Now let’s animate this data to show the yearly map of piracy incidents. Right click on ASAM_event layer, and choose Properties.

  1. In the layer properties dialog box, select the Temporal tab and enable it by clicking the checkbox.

  1. The source data contains an attribute dateofocc - representing the date on which the incident took place. This is the field that will be used to determine the points that are rendered for each time period. Select Single Field with Data/Time in Configuration Drop down menu, dateofocc as Field. Click OK.

  1. Now a Clock symbol will appear next to the layer name. Click on the Temporal Control Panel (Clock icon) from Map Navigation Toolbar.

  1. Click on the Animated Temporal Navigation (play icon).

  1. By default, the date range is set to the current date. Click Set to Full Range button to set the date range from the dataset.

  1. Now the data will be set to 2000-01-02 to 2018-01-01. Update the start date to 2000-01-01 and set the Step to years. Click play button to start rendering.

  1. It will be useful to add a label to the animation showing the date of the animation frame being displayed. We can use the Title Decoration to place that label. Go to View → Decorations → Title Label Decorations. Click the checkbox to enable it and then the Insert an Expression button.

  1. Enter the following expression to display the year and click OK.

format_date(@map_start_time, 'yyyy-MM-dd')

  1. Select font size as 25, set background color as white. In placement choose Top Center. Now click OK.

Your output should match the contents of the 2DAnimation_Checkpoint2.qg1 file in the solutions folder.

4.2 Exporting Animation

  1. To export these as images and convert them as GIF select the Export Animation (save icon) in the Temporal controller window.

  1. Choose the directory to save the images and select the ne_10_land for map extent.

  1. Once the export finishes, you will see PNG images for each year in the output directory. Now let’s create an animated GIF from these images. There are many options for creating animations from individual image frames. We like [ezgif.com] for an easy and online tool. Visit the site and click Choose Files and select all the .png files. You may want to sort the images by Type to allow easy bulk selection of only .png files. Once selected, click the Upload and make a GIF! button.

Your output should match the contents of the 2DAnimation_Checkpoint1.qgz file in the solutions folder.

5. 3D Animations

Recent versions of QGIS include native support for 3D data. Using this feature, you can easily view, explore and animate 3D elevation data. Note that your computer must have a supported graphics card for this feature to work.

5.1 Create a 3D Visualization

We will work with a 5m Digital Elevation Model (DEM) of Denali peak in Alaska and create a 3D visualization of the dataset.

  1. Open the denali project from the data package. The data contains the raw DEM layer and a hillshade layer created from the DEM.

  1. Let’s create a colorized hillshade. It is possible to drape an image or colorized DEM to a hillshade layer using QGIS’s Layer Blending Modes. Click on the Open the Layer Styling Panel icon. In the Layer styling panel, choose denali_hillshade and under Layer Rendering choose Multiply as Blending mode. The selected layer will be blended with the bottom layer. This is a great way to visualize your elevation dataset.

  1. Let’s view this data in 3D. Go to View → New 3D Map View.

  1. A new map window will open containing the rendered map layers from the main canvas. Click the Configure button.

  1. In the Terrain section, select DEM (Raster Layer) as the Type. Select denali_dem layer as the Elevation. Click OK.

  1. In the 3D view, you can hold the Shift key and drag your mouse to tilt the top-down view. You will see the map in 3D. You can also use the controls on the right-hand panel to tilt, zoom and pan the view.

Your output should match the contents of the 3DAnimation_Checkpoint1.qgz file in the solutions folder.

5.2 Create a 3D Fly-through

  1. Now we will create an animation. Click the Animations button in the toolbar. To animate the view, we must define certain keyframes. Once you define a specific view for keyframes at different times, the system will try to smoothly animate the views between them. You can use the slider to go to a specific time, use the controls to set a specific view and click the + button to add a keyframe. Click the Play button to see the animation in action.

  1. Once you are satisfied, click the Export Animation Frames button. Choose an output directory on your computer and click OK. Individual frames will be rendered and saved as separate files.

5.2.1 Challenge

As we did in the previous section, you can use a service such as ezgif.com to create a GIF/Video from these frames.

View Animated GIF ↗

6. Summary Aggregate Expressions

QGIS expression engine has a powerful function called ‘summary aggregates’ that allows evaluating a feature’s geometry and attributes with those of another layer. Expressions can be used for static calculations as well as on-the-fly computations, such as labels, virtual fields, symbology etc. This enables some powerful use cases.

The summary aggregate function operates on all the values from a different layer, returning a single summary value. The syntax of the aggregate function is as follows

aggregate(
  layer:='layer name or id',
  aggregate:='aggegate type',
  expression:='expression to aggregate',
  filter:='optional filter expression,
  concatenator:='optional string to use to join values',
  order_by:='optional expression to order the features'
  )

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6.1 Auto-populate Field Values

We will work with a land parcels data layer provided by the City of San Francisco. The goal of this exercise is to demonstrate the use of aggregate expression for on-the-fly computation when digitizing new features.

  1. Open the parcels project from the data package. Select the boundary layer and click the Open Field Calculator button.

  1. Add a new field named count with the following expression. The expression is reading the features from the parcels layer and giving an aggregate count of the features. You will notice that the the result will be displayed at the bottom of the window.
aggregate(
 layer:= 'parcels',
 aggregate:='count',
 expression:=fid
 )

  1. Now we can apply the same concept in a dynamic calculation. Back in the main QGIS window, select the polygons layer and right-click it. Select Properties.

  1. Switch to the Attributes Form tab. Select the field count and choose Text Edit as the Widget Type. At the Default Value field at the bottom, enter the following expression. Note that additional filter value. Here the $geometry refers to the geometry of the parcels layer and geometry(@parent) refers to the geometry of feature from the polygons layer. Click OK.
aggregate(
 layer:= 'parcels',
 aggregate:='count',
 expression:=fid,
 filter:=intersects($geometry, geometry(@parent))
 )

  1. Back in QGIS, click the Toggle Editing button and draw a polygon using the Add Polygon Feature button. Right-click to finish the drawing. As soon as you finish, the count of intersecting features will be calculated by the aggregate expression and displayed in the count field.

View Animated GIF ↗

  1. There are many different types of aggregates available. We can use an aggregate called concatenate to compute a comma-separated text of all feature ids. Go to the Attribute Form properties again and select the parcels field. Enter the following expression as the Default Value.
aggregate(
 layer:= 'parcels',
 aggregate:='concatenate',
 concatenator:=',',
 expression:=to_string(fid),
 filter:=intersects($geometry, geometry(@parent))
 )

  1. Now when to add a new feature, all the intersecting feature ids will be displayed along with the count.

View Animated GIF ↗ Your output should match the contents of the Expressions_Checkpoint1.qgz file in the solutions folder.

6.1.1 Challenge

Add a new field in the parcels layer called neighbors with the count of neighboring polygons.

Hint: You can use the aggregate() function on the same layer to compare each feature against all other features in the layer. The @layer variable contains the name of the current layer, so you can use the below expression

aggregate(
    layer:=@layer,
    aggregate:='count',
    expression:="fid",
    filter:=touches($geometry, geometry(@parent)))

6.2 Learn more

Apart from aggregate(), there are other advanced functions such as array_foreach() and eval() that are very powerful. Learn about them in the following video where I explain some use cases.

Video

Supplement

Using Conditions in Modeler

A key feature introduced in QGIS 3.14 was the ability for models to have a conditional branch. This allows models to check for a condition and execute a different part of the model based on the output of the condition. This is equivalent to If/Else statements in a programming language.

Let us develop a Conditional branch in the piracy_hexbin model covered in the previous section. We will add a new check-box input Use Spatial Index - that allows the user to specify whether to use a spatial index in the model. We will add a conditional branch that takes the following actions:

  • If the Use Spatial Index option is selected, the model will create a spatial index for the grid layer and use it in the subsequent steps.
  • If the option is not selected, the model will proceed without generating a spatial index.
  1. Right-click the piracy_hexbin model and select Edit Model….

  1. Search for +Boolean in Inputs tab and drag to canvas.

  1. Give Description as Use Spatial Index, leave Checked unticked. Click OK.

  1. Now, search for Conditional branch in Algorithms tabs and drag to canvas.

  1. Click the Add button and select the Expression Dialog button.

6. All the model output and intermediate layers will be displayed in Bold characters, double click in usespatialindex. It will add the variable @usespatialindex as the expression. Click OK.

  1. Now, in Branch Name type Use Spatial Index. We will add another branch now. Click the Add button and enter the Branch Name as Don’t Use Spatial Index. Since this is the opposite condition, we can use the expression NOT @usespatialindex Click OK.

Make sure to hit the Enter key after typing the Branch Name. The input may not be saved if you forget to do so.

  1. We have 2 branches in the model. Let’s connect them to appropriate algorithms. Double click on Create spatial index algorithm in model canvas and click … next to Dependencies.

  1. Choose Condition “Use Spatial Index” from algorithm “Conditional branch” and click OK. The Use Spatial Index branch is now ready. Let’s build the other branch.

  1. Search for Extract by location in Algorithms tab and drag to canvas.

  1. In the Description type Extract by location (No Spatial Index). Choose Algorithm Output in Extract features from and select “Grid” from algorithm “Create grid”. Click … next to Dependencies.

  1. Choose Condition “Dont use Spatial Index” from algorithm “Conditional branch”. Click OK.

  1. Similarly in Extract by location using Spatial Index change the description to Extract by location (Spatial Index). Both the branches will be executed according to the user selection whether to use the spatial index or not. The next step is to update the the Count points in polygon algorithm to use the appropriate output. Double-click on the algorithm box.

  1. Under Polygons change Algorithm output to Pre-calculated Value, then press the Expression button.

  1. In the Expression Dialog, we need to select output from any one of the Extract by location algorithms based on the user condition of @usespatialindex. We can use the if condition to return a layer based on user input. Use the expression below. Remember to pick the variables from the list and double-click them to enter them in your expression. If you had named the algorithms or input differently, the variable names will be different for you. Click OK.
if( @usespatialindex ,  
    @Extract_by_location__Spatial_Index__OUTPUT ,
    @Extract_by_location__No_Spatial_Index__OUTPUT)

  1. Now click … in Dependencies.

  1. Check Extract by location (Spatial Index) and Extract by location (No Spatial Index) and click OK.

  1. Now that the model is completed, click Zoom full button to view the model. Let us save the model click Save model button.

  1. Now in the Processing toolbox, under that Models → projects → piracy_hexbin model will be available. Double click to execute it.

  1. In the Base Layer select ne_10m_land, Grid size as 100000, and Input points as ASAM_events, check Use Spatial Index and click Run.

  1. Switch to Log, we can notice the Create spatial index algorithm is activated, and the total time of execution is 7.41 seconds.

  1. Now switch to Parameters, un-check the Use Spatial Index and click Run. tab.

  1. Switch to the Log, we can notice the No spatial index exists for input layer, performance will be severely degraded warning get displayed, and the execution took 78.897 seconds.

Running Processing Algorithms from the Locator Bar

To take your processing experience to the next-level, you can use the built-in Locator Bar. At the bottom-left of QGIS main window, there is a universal search bar that can do keyword-search across layers, settings, processing algorithms and more. You can open the locator bar using the keyboard shortcut Ctrl+K.

I find that rather than clicking-around the processing toolbox, you can just use the locator bar to search and open the algorithms. Type Ctrl+K, followed by a (to restrict search to algorithms), followed by a space and a few characters. Use the arrow keys to select and press Enter to open the algorithm.

View Animated GIF ↗

In-place Editing

Processing algorithms are designed to take inputs and produce outputs. The default behavior is to create a new layer after each operation. This is useful for many workflows, especially in an enterprise setting, where you may not have the ability to edit the source data. If your algorithms are altering the source data, that also means that the workflows cannot be reproduced easily. So you would want a setup where the algorithms read from source data and create modified outputs.

An exception to this workflow is when you are doing data editing. When your workflow involves creating new features or editing them - creating a new layer for every edit is undesirable. A recent QGIS crowd-funding campaign added the ability for processing algorithms to modify the features in-place and this functionality is available out-of-the-box in QGIS now.

  1. Load the basic_network_analysis project from the data package. This project contains a street network for Washington DC from DCGISopendata where the arrows display the digitizing direction of the line segments. You can click the Edit Features In-Place button in the processing toolbox to use algorithms that support this functionality. Once this mode is activated, processing algorithms will modify the selected features in the chosen layer instead of creating a new layer.

  1. Select a line segment and run the Reverse line direction algorithm. The algorithm will enable editing on the layer, perform the operation and overwrite the existing feature with a segment in the reverse direction. You will see that the arrow rendering is now in the opposite direction.

View Animated GIF ↗

Data Credits

License

This course material is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0). You are free to re-use and adapt the material but are required to give appropriate credit to the original author as below:

Advanced QGIS Course by Ujaval Gandhi www.spatialthoughts.com

This course is offered as an instructor-led online class. Visit Spatial Thoughts to know details of upcoming sessions.

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