Harnessing The Power Of Qgis Geometry Expressions

What are Geometry Expressions and Why Learn Them?

Geometry expressions in QGIS provide a powerful set of tools for performing spatial analysis and manipulating geographic data directly within the QGIS interface. They allow users to calculate geometric properties like area and length, test spatial relationships between features, construct new geometries from existing ones, and filter datasets based on location – all without leaving the comfort of the QGIS environment.

Learning to construct and apply geometry expressions opens up many new workflow possibilities that can save substantial time and effort compared to relying solely on geoprocessing tools. Common real-world uses cases include:

  • Automatically calculating the area or perimeter of parcels for land management
  • Spatially querying datasets to isolate features meeting certain location-based criteria
  • Generating buffer zones around points for proximity analysis
  • Assigning zoning categories to parcels based on spatial relationships
  • Constructing drive-time zones using distance measurements from road networks

The ability to accomplish these tasks directly and efficiently within QGIS makes geometry expressions an essential skill for GIS analysts and geospatial professionals.

Accessing Geometry Expression Builder

The interface for constructing and testing geometry expressions in QGIS is the Expression Builder/Dialog. This can be quickly accessed in most contexts by clicking the sigma Expression button located at the right side of the attribute table, feature filtering tools, field calculator, label tool, and anywhere attributes can be formulated.

The Expression Dialog consists of a large text box for inputting expressions using standard JavaScript syntax. A helpful tree listing of expression functions and parameters is available alongside for lookup. Buttons across the top run validation checks, provide help documentation links, and allow loading/saving for re-use. The output preview panel shows dynamically-updated results from test runs.

Key Functions for Geometry Operations

Some of the most frequently utilized and valuable geometry functions are:

  • $geometry – returns the actual geometry of the current feature, allowing location-based constructs like buffers and intersections.
  • $area – calculates and returns the area size of the current feature’s geometry. Units will match project CRS.
  • $length – determines the length/perimeter measurement of linestring and polygon geometries.
  • intersects() – tests if the geometry of the current feature spatially intersects another supplied geometry, useful for spatial queries.

Constructing Expressions for Spatial Queries

Geometry expressions come in handy when formulating attribute filters to isolate features meeting certain spatial criteria. For example, to select only parcels that fall within a defined reservoir watershed polygon:

intersects( $geometry, geometry( get_feature( 'watershed', 'objectid', 315) ) )

The intersects() test checks each feature against the geometry of the watershed feature. Applying this as a filter on parcels would select those intersecting the watershed.

We can also leverage area and length functions in expressions to filter, for instance finding large commercial parcels over 5000 sq meters:

$area > 5000 and "LANDUSE" = 'Commercial'

This filters both spatially and by attribute data, demonstrating the versatility of geometry expressions.

Applying Geometry Expressions in the Attribute Table

In addition to querying features, we can utilize the Field Calculator within the attribute table to write outputs of geometry expressions to new or existing fields. For example, to populate an “AREA” field with the $area value for each polygon feature:

  
$area

The field calculator runs this expression row-by-row to derive areas dynamically and populate the output field with results. This avoids a lengthy manual calculation process!

We could also leverage the field calculator to assign zoning categories based on spatial relationships. Here we tag parcels as “OUTSIDE_ZONE” if they fall outside certain limit boundaries:

  
if( intersects( $geometry, geometry( get_feature( 'zone_limits', 'objectid', 2) ) ), 'INSIDE', 'OUTSIDE' )

The expression checks intersecting geometry per row and assigns the appropriate zone code string.

Example Workflow for Spatial Analysis

To illustrate the real-world value of geometry expressions for streamlining analysis, consider this workflow to model new well buffer zones meeting certain criteria for available land:

  1. Start by creating 1000 foot buffers around current wells using the Buffer tool with dissolve enabled to create a single multipolygon entity
  2. The National Land Cover Database polygons (NLCD) represent land use categories
  3. Spatially join the dissolved well buffer layer to assign land types to buffer area with one-to-one cardinality
  4. Open the attribute table of the joined layer and add a new “ALLOWED_ZONE” text field
  5. Use field calculator with this expression on the new field:
  6.  
    if( "LC_Type" IN ( 'Grassland', 'Shrub', 'Pasture'), 'Yes', 'No' )  
    
  7. This will tag each buffer segment as allowed or restricted for new well citing based on land type falling inside
  8. Select and extract buffer segments tagged ‘Yes’ to a separate layer representing viable zones

By leveraging spatial operations like buffering and joining through geometry expressions, the task of siting is condensed into an efficient workflow in pure QGIS. Code snippets implement the key steps:

# Step 1
Buffer( wells_layer, dissolved=true, distance=1000)

# Step 3
Join attributes by location( buffer_layer, NLCD_layer, predicate='intersects')

# Step 5 
Field calculator on ALLOWED_ZONE field:  
if( "LC_Type" IN ( 'Grassland', 'Shrub', 'Pasture'), 'Yes', 'No' )

# Step 7
Select by attribute on ALLOWED_ZONE = 'Yes'

Common Errors and Troubleshooting

When authoring geometry expressions, syntax errors can often halt execution or output unexpected results. Some common mistakes include:

  • Misspelled function names like $geomtry instead of $geometry
  • Unmatched parentheses or quotes
  • Wrong case like Intersects() rather than intersects()
  • Trying to perform unsupported operations like directly updating geometries

Carefully proofreading expressions and taking advantage of the identifier highlighting and validation checks within the Expression Dialog can help avoid basic issues. Testing expressions step-by-step during construction is also wise to isolate any areas causing unintended results.

For invalid geometries or attempts to operate on NULL values, incorporating conditional checks with IS NULL or IS NOT NULL prevents unexpected outputs. Defensive coding practices help make geometry expressions more robust and stable.

Next Steps for Learning Geometry Expressions

For those seeking to further build proficiency with QGIS geometry expressions, excellent resources exist:

  • The detailed User Guide and Training Manuals cover geometry expressions in-depth with examples.
  • GeoNet forum and GIS StackExchange provide venues to post questions and discuss with experts.
  • Many video tutorials and blog posts demonstrate expressions workflows for common tasks.
  • Real-world use cases with spatial data are invaluable learning exercises.

As comfort level grows, operators can explore more advanced constructs like aggregates, variable assignment, and recursion to greatly expand analysis capabilities.

Key Takeaways

QGIS geometry expressions place simple yet powerful spatial analysis and data manipulation tools directly at users’ fingertips. Key capabilities unlocked include:

  • Filtering feature selections by location-based conditions
  • Computing geometric properties like areas and lengths without intermediate steps
  • Constructing new shapes and geometries from existing features programmatically
  • Updating attributes dynamically with user-defined calculations based on space

With over 60 available geometry functions, the possibilities are vast. Unlocking this toolkit within QGIS greatly enhances workflows and productivity working with spatial data.

Leave a Reply

Your email address will not be published. Required fields are marked *