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Instantly identify stockpiles across your surface model, even on large, complex sites.
Assign materials and generate consistent, repeatable volume reports ready for delivery.
Learn how to manage your stockpiles and generate reports directly from your PixElement project.
What is StockpileStudio?
StockpileStudio is a feature for accurate volumetric measurements and inventory management of stockpiles.
How accurate are the measurements?
Volume accuracy depends on input data quality, but with properly collected drone imagery or LiDAR, StockpileStudio delivers survey-grade results suitable for operational reporting and engineering workflows. Results are fully traceable back to the underlying surface model.
How does StockpileStudio handle equipment and temporary site conditions?
StockpileStudio automatically detects and suppresses conveyors, stacker booms, vehicles, and other temporary structures that may appear in aerial datasets. By analyzing surface continuity and stockpile morphology, the system isolates material surfaces from manmade objects and reconstructs a clean base surface when needed. This helps ensure volumes reflect material mass rather than temporary infrastructure or equipment movement.
How does StockpileStudio integrate with existing workflows?
StockpileStudio fits directly into existing photogrammetry and LiDAR processing pipelines, using surfaces and point cloud deliverables that are already generated.
What types of stockpiles does StockpileStudio support?
StockpileStudio supports common material stockpiles including aggregates, sand, gravel, coal, salt, ore, and other bulk materials. It works with both irregular and conical piles, as well as long windrows and storage bays.
What outputs does StockpileStudio provide?
StockpileStudio produces clear volume summaries, individual pile measurements, and exportable data that can be used for reporting, inventory tracking, or downstream CAD and GIS workflows.
Does StockpileStudio require LiDAR data?
No. StockpileStudio works with both photogrammetry-derived surfaces and LiDAR point clouds. LiDAR can improve performance in complex or partially vegetated areas, but is not required for most stockpile use cases.