Key takeaways
- For bare, open piles, photogrammetry matches LiDAR on volume accuracy at lower cost.
- LiDAR earns its premium when vegetation, dust or low light defeats a camera.
- Either way, the volume number is only as good as the base surface and the ground control behind it.
“Should my stockpile survey use LiDAR or photogrammetry?” is one of the most common questions aggregate and mining operators ask, and the honest answer is that for most open piles the two reach the same volume number. They get there differently, and the differences — cost, turnaround, and how each handles vegetation and surface texture — are what should drive the choice, not a blanket claim that one is always more accurate.
What each method actually measures
Both produce a 3D surface of the pile that is compared against a base plane to compute volume. The difference is how the surface is captured.
Photogrammetry
The drone shoots hundreds of overlapping photos; software matches common points across them to reconstruct a dense 3D point cloud and an orthomosaic. It is a passive, camera-based method: it needs texture and light to work, and it reconstructs whatever surface the camera can see.
LiDAR
A LiDAR payload (for example the DJI Zenmuse L1 or L2 on the Matrice platform) fires laser pulses and times their return to measure range directly. It is an active sensor: it makes its own measurement rather than inferring geometry from images, and some pulses penetrate gaps in light vegetation to reach the ground beneath.
Where each one wins for stockpiles
Photogrammetry is the default for open aggregate piles
- Bare gravel, sand, salt and ore piles have plenty of texture for image matching.
- Volume accuracy is routinely in the low single-digit percent of the true pile volume when flown with proper overlap and ground control.
- It is cheaper — a standard RTK-capable drone, no specialized payload — so it is the practical default when the material and site are camera-friendly.
- The orthomosaic is a useful by-product for documenting the yard.
LiDAR earns its premium in specific conditions
- Vegetation. Piles reclaimed by grass or brush, or sites where you need the true ground surface under light cover, favour LiDAR because it can see between the plants.
- Low light or low texture. Uniform, low-contrast material or poor light degrades photo matching; LiDAR does not depend on either.
- Dust and steep faces. Active ranging holds up better on featureless steep faces where photogrammetry can thin out.
Accuracy, cost and turnaround, side by side
| Factor | Photogrammetry | LiDAR |
|---|---|---|
| Volume accuracy on open piles | Low single-digit % of volume | Comparable on open piles |
| Vegetation penetration | None — sees the canopy | Partial through light cover |
| Needs good light + texture | Yes | No |
| Relative cost | Lower | Higher (specialized payload) |
| Colour orthomosaic by-product | Yes | Not inherently (needs paired camera) |
| Processing | Heavier image processing | Lighter, more direct point cloud |
What actually governs the volume number
Chasing the sensor debate misses the bigger levers. On most disputed stockpile numbers the sensor is not the problem — the base surface and the control are:
- The base plane. Volume is measured against an assumed ground surface under the pile. Get that wrong and neither sensor saves you.
- Ground control. Independent, surveyed ground control points are the check that catches systematic bias in either method.
- Consistency between cycles. For month-over-month movement, flying the same method the same way matters more than which method you picked.
How UAV Imaging approaches it
For standard aggregate, gravel and salt piles on open ground, UAV Imaging measures stockpiles with drone photogrammetry — it matches LiDAR on volume accuracy for these piles at a lower cost, and delivers a colour orthomosaic alongside the volume report. Where vegetation, low light or reclaimed surfaces get in the way, LiDAR is the tool. Both are flown with independent ground control and delivered with an accuracy report, so the volume number stands up for inventory reconciliation, financial reporting or contract payment.