QGIS Outperformed ArcGIS Pro in Rooftop Solar Analysis
A recent study found QGIS r.sun provided more accurate rooftop solar potential estimates than ArcGIS Pro.
Updated on Oct. 1, 2026 in Geography
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Researchers compared QGIS r.sun and ArcGIS Pro Raster Solar Radiation tools to assess urban rooftop photovoltaic potential across three study areas. The study concluded that QGIS produced estimates more closely aligned with PVGIS solar assessment data.
Why it matters
Accurate solar potential mapping is essential for optimizing urban renewable energy integration and city-scale infrastructure planning. The choice of GIS modeling software creates measurable differences in production estimates, impacting how planners evaluate solar viability.
QGIS r.sun achieved better accuracy by incorporating the Linke turbidity factor for atmospheric conditions. In contrast, ArcGIS Pro consistently overestimated production and failed to include reflected solar radiation in its underlying calculations.
The players
QGIS
An open-source geographic information system software package widely used for spatial analysis.
ArcGIS Pro
A proprietary desktop geographic information system application developed by Esri for 2D and 3D data visualization.
PVGIS
The Photovoltaic Geographical Information System, a tool used for solar radiation assessment and performance modeling.
The details
The models utilized input datasets covering solar radiation, surface slope, orientation, and local shading. QGIS r.sun relies on raster inputs—grid-based data representing geographic features—to process the ratio of diffuse to global radiation. Meanwhile, ArcGIS Pro was noted for processing advantages, such as its capacity to ingest pre-existing slope and orientation maps directly into its workflows.
Timeline
May: ArcGIS Pro recorded a production peak.
June: ArcGIS Pro recorded a production peak.
July: QGIS production reached its annual peak.
October: ArcGIS Pro recorded a production peak.
The Tech Race
The development of standardized rooftop solar mapping relies on the accuracy of GIS software as the foundation for energy transition data. This comparison provides a crucial benchmark for the software tools that will underpin the European Union's Digital Building Stock Model.
Urban planners and energy analysts should note that software selection significantly influences the projected output of solar installations. Using more precise atmospheric modeling tools like QGIS helps avoid the production overestimations observed in this comparative assessment.
The takeaway
Reliable renewable energy planning depends on the specific atmospheric and reflective variables included in software models. Practitioners should watch for updates to the European Union's Digital Building Stock Model, which will provide a centralized framework for large-scale solar mapping.
What happens next
Future research is expected to test solar production potential at a finer temporal scale to further refine modeling accuracy.
Further reading
For more on the spatial tools defining infrastructure, visit Geography.
Source note: This article includes information reported by Green Building Africa.
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