Scenarios and Datasets
Scenarios
These are suggested scenarios to explore, but feel free to create your own!
Story question:
How accessible are key services (e.g. health clinics, parks, libraries, public transport) in your chosen area?
What you might analyse:
- Locations of services (points)
- Population or suburb boundaries (polygons)
- Distance or service catchments (buffers)
Techniques to use:
- Import vector data
- Reproject layers
- Buffer services
- Count services per area
- Style with graduated symbology
Possible outputs:
- Map showing service access
- Statistic: services per suburb or per capita
- Digitised service catchments
Extension:
- Add a population or elevation raster to assess accessibility by terrain or density.
- Try Zonal Statistics to calculate average population or elevation within service catchments.
- Explore Service Area (Network Analysis) for more realistic travel distances.
Story question:
Which areas are most exposed to an environmental risk (e.g. flood, heat, bushfire, erosion)?
What you might analyse:
- Hazard raster or vector data
- Elevation or land cover
- Administrative boundaries
Techniques to use:
- Raster styling
- Clip rasters
- Reclassification
- Choropleth mapping
Possible outputs:
- Risk map
- Population or land area affected
Extension:
- Add population polygons or building footprints as vector data.
- Try Zonal Statistics to calculate average population that may be affected.
- Use Raster Calculator to combine multiple risk layers.
- Try Extract by Mask to isolate high‑risk zones.
Story question:
How is land used in this area, and how does that relate to human activity?
What you might analyse:
- Land use polygons
- Population or infrastructure
- Satellite imagery
Techniques to use:
- Categorised symbology
- Area calculations
- Intersections
- Digitising land use areas
Possible outputs:
- Land use map with legend and labels
- Chart or statistic by land use type
Extension:
- Add a land surface temperature or vegetation raster.
- Use Zonal Statistics to summarise raster values by land use type.
- Try Spatial Join to attach population counts to land use zones.
Story question:
Which parts of the city are most exposed to heat, and where is shade available?
What you might analyse:
- Temperature or vegetation raster
- Tree canopy or parks
- Roads or footpaths
Techniques to use:
- Raster symbology
- Overlay with vector data
- Buffer shade sources
- Zonal statistics
Possible outputs:
- Heat exposure map
- Areas lacking shade
- Digitised shade zones
Extension:
- Add suburb or census polygons as vector data.
- Use Raster Calculator to combine heat and vegetation layers.
- Try Line Density on footpaths to find heavily exposed walking routes.
Story question:
Where do wildlife habitats overlap with urban or agricultural land?
What you might analyse:
- Habitat polygons
- Urban extent or land use
- Roads or population data
Techniques to use:
- Vector intersection
- Field Calculator
- Categorised symbology
Possible outputs:
- Conflict or overlap map
- Area of habitat affected
- Styled map for communication
Extension:
- Add elevation or vegetation raster.
- Use Zonal Statistics to summarise habitat quality by area.
- Try Proximity (Distance to Nearest Hub) to measure distance to roads or towns.
Story question:
Where would be the best location for a new park, school, clinic, or bike path?
What you might analyse:
- Population density
- Existing services
- Slope or elevation
Techniques to use:
- Buffers
- Intersections
- Raster slope or classification
- Digitising candidate sites
Possible outputs:
- Suitability map
- Priority zones
- Digitised proposed locations
Extension:
- Add land value or zoning polygons as vector data.
- Use Raster Calculator to weight suitability factors.
- Try Multi‑criteria Evaluation with reclassified rasters. See for example this tutorial.
Story question:
What spatial patterns exist in a set of events or observations?
What you might analyse:
- Disease cases
- Crime locations
- Wildlife sightings
Techniques to use:
- Heatmaps or density
- Point-in-polygon
- Graduated symbology
- Labelling
Possible outputs:
- Density map
- Counts by area
Extension:
- Add a population or land cover raster.
- Use Kernel Density Estimation for smoother patterns.
- Try Nearest Neighbour Analysis for clustering insight.
Story question:
What can we learn from data you collect yourself?
What you might analyse:
- Tree locations
- Street furniture
- Noise or pollution points
Techniques to use:
- Smartphone data collection (or plot points using satellite data)
- Importing CSV or GeoPackage
- Styling points
- Basic spatial analysis
Possible outputs:
- Map of collected data
- Patterns or clusters
Extension:
- Add a satellite image or vegetation raster.
- Use Spatial Join to link observations to areas.
- Try Point Density to highlight hotspots.
Story question:
How does transport infrastructure shape access or movement?
What you might analyse:
- Roads or public transport
- Population
- Service locations
Techniques to use:
- Buffer analysis
- Intersections
- Thematic symbology
Possible outputs:
- Transport access map
- Underserved areas
Extension:
- Add a slope or elevation raster to model walking difficulty.
- Use Raster Calculator to combine slope and distance.
- Try Network Shortest Path for simple routing.
Story question:
Which areas are more likely to contain Aboriginal archaeological sites, and how might proposed development impact cultural landscapes?
What you might analyse:
- Known site locations (points or polygons)
- Landforms (elevation, slope, aspect)
- Distance to water sources (rivers, wetlands, coast)
- Land use or disturbance layers
- Project or development boundaries
Techniques to use:
- Import vector and raster data from authoritative sources
- Reproject layers to an appropriate Australian projected CRS (e.g. MGA / GDA2020)
- Buffer water sources or landforms
- Try Extract by Mask to limit analysis to the project footprint or study area
- Combine rasters to build a simple predictive surface
- Vector intersection with development footprints
- Apply a custom styling theme or template to ensure consistent symbology across reports.
Possible outputs:
- Archaeological sensitivity or probability surface
- Map of high, medium, and low sensitivity zones
- Areas of potential impact within development boundaries
- Styled map suitable for inclusion in a consulting report
Extension:
- Use the Raster Calculator to reclassify and combine environmental predictors into a single sensitivity surface.
- Use Zonal Statistics to summarise sensitivity values within development parcels or survey areas.
- Explore Proximity (Raster Distance) as an input to a simple predictive model.
Story question:
What spatial story can you tell about a place that matters to you?
What you might analyse:
- Any combination of raster and vector data
- Boundaries, services, environment, or population
Techniques to use:
- Import and reproject data
- Digitise features
- Perform at least one spatial analysis
- Style and label layers
Possible outputs:
- 1–3 maps that could support advocacy and encourage community awareness
- A clear spatial narrative
Extension:
- Add either a DEM or land cover raster if using mostly vector data.
- Try Zonal Statistics or Raster Calculator for deeper analysis.
- Explore Viewshed or Slope for terrain‑based stories.
Datasets
The following datasets are examples on online data that you can use in your project.
Basemaps
QuickMapServices Plugin
Explore the different basemaps available in the QuickMapServices plugin.
Web Mapping Services
Some providers:
Searching online for ArcGIS REST Servers may allow you to find more resources such as this QLD Gov Aerial Basemap
- Scroll down the
Browserpanel until your see XYZ Tiles - Right click XYZ Tiles and select
New Connection... - In
Nametype Voyager (no labels) - In
URLpaste:
https://a.basemaps.cartocdn.com/rastertiles/voyager_nolabels/{z}/{x}/{y}@2x.png - Increase the Max. Zoom Level to 20
- This value depends on what is available from the given service in different parts of the world. Increasing that value beyond 20 for this map in Brisbane will show “Map data not yet available” when you zoom in very close.
- Click
OK - In the
Browserpanel, expandXYZ Tilesand double click onVoyager (no labels)
Raster Data
DEM Repositories
A Digital Elevation Model (DEM) is raster data that shows the elevation of an area. There are a few repositories you can access this kind of data, but ELVIS is great for Australia.
ELVIS - Geoscience Australia’s ELeVation Information System.
- Go to http://www.ga.gov.au/elvis/
- Search for “St Lucia” in the
Location Searchsearch box and select the first result - Click
Order Data - Choose “Draw” and “Box” and then click the
Drawbutton - Click on the map to start drawing a rectangle around your desired area
- Then click
Search - The right panel will show you all the different datasets available in that area
- We want the QLD Government Digital Elevation Model 1 Metre, click the down arrow on the right
- As you hover over the different options, they will highlight a red box on the map, click the tick box and select all that overlap the area you’re interested in (note that there may be data from different years here)
- When you have the data you want, scroll to the bottom of the Order Data window
- Select your industry, enter your email, tick the reCAPTCHA, and click the
Order Datasetsbutton - You should receive an email within 5 minutes, download the files from the link in the email, extract the folder to your project folder, and add them to your map.
- Go to https://earthexplorer.usgs.gov/
- Click the World Features box, and then search for “Brisbane” in the “Feature Name” search box
- Click Show and select the first result
- Zoom onto an area of interest around Brisbane and click “Use Map”
- Click the “Data Sets” button and then
Digital Elevation > SRTM, select “SRTM 1 Arc-Second Global” and click “Results”
“SRTM” stands for “Shuttle Radar Topography Mission”. It provides global elevation data collected in 2000 by the space shuttle Endeavour.
Land, Vegetation, Hazard Rasters
GeoScience have a a varierty of OGC Webservice Data that you can access Earth and Envrionment related rasters in the same way we used WebMapping Services to access Basemaps.
Climate Rasters
The Bureau of Meterology has many types of Grid data of climate data (Rainfall, Temperature, Solar Exposure, etc.) that you can download and import into QGIS.
Population Rasters
The ABS have a lot of useful data, including population data. They provide it in Excel format, as GeoPackages (by SA2 and LGAs), and as population grid raster files.
Aerial Imagery
There are a few places you can aquire aerial photography, some are freely available Government Data, some cost money, but can be accessed with your UQ credentials.
Nearmap (account login required)
As a UQ student or staff member, you have access to very high resoltuion imagery from Nearmap. You can even access an array of imagery going back in time.
- Go to the UQ Nearmap Portal
- Enter your UQ Student (@student.uq.edu.au) or Staff (@uq.edu.au) email address, with the appropriate domain selected. Click “Invite me”.
- You should receive an email soon after, click the “Accept Invitation” button, and go through the account setup process.
- Go to Login and enter your email address, click “Next” and enter your password.
- From the top right select
MapBrowser. - Type “St Lucia, QLD” in the search box, press enter
- You can click the date down the bottom to look at different snapshots in time, and even compare maps side-by-side.
- To save imagery from Nearmap, simply click the “Exports” button on the left handside (it is an image icon)
- From the menu that appears change the “Export type” to “Georeferenced image”
- From “Projection” choose GDA2020 / MGA zone 56
- You can increase and decrease the size of the bounding box by adjusting its corners, a smaller box means you can have a finer resolution, down to 0.075m. If we select all of UQ St Lucia in one go, the highest resolution we can have is 0.299m.
- Once you’re happy with your selection click
Download Files - Move the downloaded zip file to your project folder, and open them in QGIS
You can also use the Nearmap API to bring the data in as a web mapping service.
Historical Aerial Imagery
QImagery (free access government data)
QImagery is a repository of QLD Historical Images.
- Go to QImagery
- Read and tick the “I acknowledge I have read and agree to the Terms & Conditions” box, and click
Get Started - Click the Search button, select ‘locality, town or city’ and search for “St Lucia” in the “Enter search term” search box and select the first result
- It will zoom to your selected location then click the newly appeared
Searchbutton - From here you can select from a wide array of images of QLD over many years.
- Click one of the drop-downs and hover over the options to see where those images are located. Preview the image by clicking View.
- You can then download your desired images by clicking “Download” and selecting TIFF (georeferenced)
- Move the TIFF file(s) to your project folder, and open them in QGIS
Geoscience Australia’s Historical Aerial Photo (HAP) Collection (free access government data)
Geoscience Australia’s Historical Aerial Photo (HAP) Collection is Australia wide, and may have different photos to QImagery.
Vector
ESRI Data
ESRI have a repository of 10000+ Searchable Feature Layers from ArcGIS, which you can use Web Mapping Services to bring in to QGIS. Unlike the basemaps, these will pull in vector data!
For example this User’s Data which has lots of useful QLD layers.
Council Data
Most Councils have a spatial data service. It can be hard to find, but targetted searching and trawling their websites can often yield useful local data.
State Government
You can access a wide variety of QLD Government Data, including Spatial Data such as lot plans and vegetation maps, from QLD Spatial.
For example you could acces the Property boundaries Queensland dataset
There are three ways to access data from QSpatial.
Download all of the data from a layer
Select a portion of a layer for download using the My List function
Live load it into your project using a Mapserver.
Here is an example of extracting property boundaries.
To access data from QLD Spatial go to https://qldspatial.information.qld.gov.au/
Search for “property boundaries”
Scroll down to “Property boundaries Queensland” and click Add to my list
Click My List from the top menu
Click View/extract in map
Under Extractable Data, click the box next to Property boundaries Queensland, it will become green
Click Extract/download
Click Choose an area
Select BRISBANE CITY from the Select LGA option
Choose GeoPackage 1.0 from Select output format
Enter your Email Address
Accept the Terms and Conditions
Click Extract/Download
Another way to access QSpatial Data is using the Queensland Globe portal. Here is an example of extracting property boundaries from Queensland Globe.
- To access data from Queensland Globe go to https://qldglobe.information.qld.gov.au
- Accept the T&Cs.
- Click Search, Select Locality (Suburb) within a Local Government Area, and search for the location you want and select it from the list.
- Click Layers, click Add Layers + here you can scroll through and filter different layer types
- We want to tick the box next to
Planning Cadastre > Land Parcels > Land Parcel(you may need to zoom in to see certain layers) - To export data click the Wrench Icon in the top right, and then click the Identify icon (i)
- Use the triangular Identify Polygon tool to select and area of interest. Double click when you’ve finished selecting your area.
- The Layers menu will now show your selection. You can download all, or sections, of your selection.
- I will choose Land Parcel and then Download as a shp file.
- Note: You may need to disable other layers for this to work correctly. I needed to turn off the Transportation layer to prevent roads from being included in my selection.
Federal Government Data
Data.gov
You can search for data on data.gov, and then filter the formats only for spatial files like SHP, tif, GEOTIFF, GeoJSON, KML, KMZ, GDB, FGDB, GeoPackage, NetCDF, ASC, REST, WCS, ESRI, ArcGIS, WFS, WMS, WMTS, WCM, etc.
Digital Atlas of Australia
Explore data similar to data.gov, but explcitly for spatial data and interactive maps with the Digital Atlas of Australia
Federal Environment Department Spatial Data - Species observation data
The Federal Environment Department has a variety of different spatial datasets that you can browse through.
One example is the Collaborative Australian Protected Areas Database (CAPAD) 2020, which is a compilation of government, Indigenous and privately protected areas for Australia. You can search for “CAPAD” in on the Environment Department website, or by going directly to the data.
Australian Bureau of Statistics
The ABS is a huge source of data, however, it can be a bit difficult to find that data, and use it in a spatial context.
The ABS has a variety of ways that it splits its data up. These Digital Boundary Files are very useful for classifying data. They generally classify all of Australia into discrete Statistical Areas. Level 1 are the smallest, and Level 4 are the coarsest. (Notably, the link above also has non-ABS Structures/boundary files such as Electoral areas and Postcodes.)
Population Data
The ABS have a lot of useful data, including population data. They provide it in Excel format, as GeoPackages (by SA2 and LGAs), and as population grid raster files. SA2 GeoPackages are a convenient format for QGIS. This means we have our digital boundaries, and population in one!
You can also find tabular data separated by state containing information like Crime Data
Online Community Spatial Repositories
Atlas of Living Australia - Species observation data
Species observation data can be downloaded from the Atlas of Living Australia.
This is an Australia Biodiversity occurrence database. It pulls data from a variety of different sources, including government data, individual collectors and community groups. This means that this data will contain sampling bias and will often simply represent encounters, rather than using robust sampling and collection methods. So, while we need to use this data with caution, it’s still a useful dataset!
You need to create an account and request the exact dataset you need.
Global Biodiversity Information Facility (GBIF) - Species observation data
This is another species observation database, but this one is worldwide.
iNaturalist - Species observation data
Community/Citizen Science species observation database.