The Customer
A client needed accurate geometry to support consistent spatial data creation in GIS digitization workflows. In QGIS-based digitization, manual tracing often introduced angular errors and inconsistencies, especially when operators worked on building edges and polygon structures.
The workflow involved GIS operators working with building geometries that required right-angled structures for better consistency. The tool was especially useful in projects involving urban mapping and structured building datasets where orthogonality was important.
The Challenge
Manual digitization created visually acceptable polygons that were not always geometrically accurate, affecting data quality and increasing correction effort.
- Edge Alignment
Building edges were not perfectly aligned, resulting in inconsistent right-angle geometry and affecting the accuracy of digitized building footprints.
- Angular Deviation
Slight hand movement while tracing edges introduced angular deviations, thereby reducing the quality of topology and geometry.
- Manual Correction Effort
Uneven polygon structures required time-consuming manual corrections, slowing down the digitization workflow for GIS operators.
- Shape Preservation
Irregular structures made correction difficult, since not all polygons were meant to be perfectly orthogonal, and over-correction could distort building footprints.
- Post-Processing Workload
The lack of automated orthogonality support increased post-processing effort in workflows that required high geometric accuracy.
The Solution
A custom orthogonality maintenance tool was developed using Python and the PyQGIS framework to automate geometry correction directly within QGIS.
- JOSM-inspired Approach:
The tool was inspired by JOSM’s “Q” feature and adapted for QGIS workflows to automate orthogonality correction of building geometries. - Angle Analysis:
The tool analyzed the angles formed between consecutive line segments in a polygon to identify geometric features that required correction. - Deviation Detection:
Segment directions were calculated, and internal angles between edges were measured to detect deviations from 90° and 180°. - Geometry Transformation:
Geometric transformations were applied to reposition vertices and maintain orthogonality in building structures. - Polygon Reconstruction:
Polygon geometry was reconstructed after correction to support consistent right-angled building footprints. - Distortion Control:
Logic was included to minimize distortion so corrected polygons remained visually close to the original digitized structure. - Interactive Editing:
This support was implemented using QGIS, Python, the PyQGIS API, vector geometry processing, and spatial editing tools.
The Result
- The tool improved digitization quality by automating orthogonality correction and reducing repetitive manual editing.
- Improved orthogonal accuracy of building footprints.
- Reduced post-processing effort for GIS operators.
- Better geometric consistency across corrected polygon structures.
- Increased productivity for GIS teams.
- Improved spatial data quality in QGIS-based digitization workflows.
- Streamlined creation of accurate building footprints for structured building datasets.
The Summary
The custom Python and PyQGIS tool improved QGIS digitization workflows by automating orthogonality correction for building geometries. Inspired by JOSM’s orthogonalization approach, it helped reduce manual correction effort, improved geometric consistency, and supported higher-quality spatial data while preserving the visual integrity of original polygon structures.
- Automated geometry correction
- Improved orthogonal accuracy
- Reduced manual editing
- Better polygon consistency
- Enhanced spatial data quality
- QGIS workflow efficiency
Is Manual Geometry Correction Slowing Down Your GIS Operations?
Automated spatial editing tools can improve consistency, reduce delays, and support better-quality building footprint creation.
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