01
Why Stockpile Volume Measurements Can Be Difficult
Stockpiles rarely have simple shapes.
Material settles unevenly. Equipment moves through the area. Piles grow, shrink, merge, and change shape throughout the year. That makes estimating volume based on basic dimensions difficult.
Traditional methods can involve collecting individual points around the pile and across its surface. The quality of the resulting volume calculation depends heavily on how well those points represent the actual shape of the material.
LiDAR approaches the problem differently. Instead of measuring a limited number of locations, it captures dense surface data across the pile.
02
Creating a 3D Model of the Stockpile
During LiDAR data collection, the visible surface of the stockpile is measured from many locations.
Those measurements form a three-dimensional point cloud. The point cloud can then be processed into a surface model representing the shape of the material.
Once the stockpile surface and its base are defined, software can calculate the volume between them. This approach allows irregular slopes, peaks, depressions, and edges to be represented in far greater detail than a simple length-times-width estimate.
- Capture surface measurements across the entire pile
- Build a classified 3D point cloud
- Generate a triangulated surface model
- Define the base or ground surface
- Compute the volume between surfaces
03
Why Dense Data Matters for Volume Calculations
Imagine measuring a pile using only a few points.
Those measurements may accurately represent the locations where they were taken, but the surface between them still has to be estimated. The more irregular the pile, the more important that missing detail becomes.
LiDAR captures many more measurements across the surface. That helps the digital model follow the actual shape of the stockpile rather than relying on a small number of representative points. For aggregate piles, dirt stockpiles, gravel, excavation material, and similar applications, that additional surface detail can improve confidence in the resulting calculations.
04
Measuring Pits and Excavations
The same general concept applies to pits and excavations.
LiDAR can capture the shape of excavation areas, borrow pits, aggregate pits, mine surfaces, graded areas, retention areas, and cut-and-fill operations. A three-dimensional model can then be used to evaluate surface changes and calculate quantities.
When measurements are collected repeatedly, project teams can also compare datasets from different dates.
- Excavation areas
- Borrow pits
- Aggregate pits
- Mine surfaces
- Graded areas
- Retention areas
- Cut-and-fill operations
05
Track Material Changes Over Time
One of the major benefits of LiDAR volume measurement is repeatability.
A company may need to know more than the current amount of material. It may need to understand how inventory is changing.
For example, a material yard could scan the same stockpile periodically and compare results. A contractor could compare surfaces before and after excavation. A mining operation could measure material movement between production periods.
- How much material was added?
- How much material was removed?
- How much excavation has occurred?
- How much material remains?
- How has the pit surface changed?
- Does the quantity match internal inventory records?
06
Faster Data Collection Across Multiple Stockpiles
The efficiency advantage becomes especially important when a site contains multiple piles.
Collecting individual measurements across every stockpile can require considerable field time. LiDAR allows a large amount of surface information to be collected during the same visit.
Depending on site size and conditions, multiple stockpiles can be documented as part of one collection effort. This can make regular inventory measurements more practical for businesses that previously relied primarily on estimates.
07
Reduce Time Around Active Equipment
Material yards, mines, and construction sites are active environments.
Loaders, haul trucks, excavators, and other equipment may be moving throughout the property. Reducing the amount of time personnel need to physically move across stockpiles and active work areas can make the data collection process more efficient.
Every site is different, and proper safety procedures are still required, but remote data collection can reduce the need to manually occupy every location being measured.
08
How Is Stockpile Volume Calculated?
At a basic level, stockpile volume calculations compare the measured surface of the pile against a defined base surface.
The accuracy of that base matters. If the underlying ground surface is known, it may be possible to compare the current stockpile against that surface. In other situations, the base may need to be estimated or defined from surrounding information.
This is why understanding site conditions is important before performing the calculation. An accurate surface model of the pile cannot completely compensate for an incorrectly defined base.
09
Why Repeated Scans Can Become More Valuable
The first LiDAR collection creates a detailed snapshot of current conditions.
Future collections can become even more useful because they allow direct comparison. When datasets are collected using consistent control and procedures, teams can evaluate changes between dates.
Instead of relying on estimates or visual observations, project managers can work from measured three-dimensional surfaces.
- Inventory management
- Production tracking
- Earthwork monitoring
- Contractor billing
- Material reconciliation
- Project documentation
10
Who Can Benefit From LiDAR Volume Calculations?
LiDAR stockpile and pit measurements can be useful for a wide range of operations.
Any operation managing significant quantities of bulk material may benefit from faster and more repeatable measurement. LiDAR is used by aggregate producers, mining companies, excavation contractors, general contractors, civil contractors, material yards, ready-mix operations, municipal projects, and land development companies.
- Aggregate producers
- Sand and gravel operations
- Mining companies
- Excavation contractors
- General contractors
- Civil contractors
- Material yards
- Ready-mix operations
- Municipal projects
- Land development companies
