Flexible and Effective Stockpile Measurement with FJD Trion S1

In industries like mining, construction, agriculture, and logistics, stockpile measurement is a critical task that can affect planning, change project schedules, and ultimately, impact the bottom line. Whether it's coal, gravel, ore, grains, or sand, understanding the volume of these bulk objects in piles is essential for strategic planning and production. Traditionally, this process was labor-intensive and time-consuming, but thanks to 3D laser scanning technology, you can measure irregular piles faster and more accurately.

The Downsides of Traditional Methods

Traditional stockpile volume calculations often relied on estimations made using the capacity of transportation vehicles, for example, the weight or volume capacity of dump trucks. Also common are manual measurements and surveying methods using tools like total stations and RTK rovers to measure points, lines, and calculate distances, areas, and volumes.
Some downsides include:
  • Low efficiency: Manual measurements are time-consuming and require concerted efforts from teams to get the calculations done quickly.
  • Low accuracy: Errors are inevitable and inaccurate data could translate to greater operational uncertainty and profit losses.
  • Safety risks: The sudden release of large quantities of heavy materials poses a serious threat. Factors like heavy rain, freeze/thaw conditions, and other elements can elevate the risk, leading to potential harm to workers and equipment as they work near stockpiles.

Embracing 3D Laser Scanning Technology

3D laser scanning technology has revolutionized the way stockpiles can be measured. Here's why it's a game-changer:

Speed and Efficiency

With 3D laser scanning, surveyors no longer need to mark the surface of the stockpile or set reference lines. The scanner quickly and accurately captures the entire stockpile with laser beams. A walk around the target stockpile from a safe distance in minutes can provide a rich dataset that might have taken hours or days to acquire.

Accurate 3D Models for Informed Decision-making

3D laser scanners deliver comprehensive data, generating a centimeter-level accurate point cloud model of the stockpile. This data can be quickly analyzed in-depth, providing operators with precise datapoints for informed decision-making.

Cost Savings in the Long Run

While the upfront investment in a laser scanner solution is not trivial, the savings can be substantial in the long run. Time and money saved on ground-based manual methods can be redirected towards tasks that enhance productivity. Additionally, having data to track stockpile changes streamlines operations and fosters clearer communications between teams.

The Process: Scan, Process, and Get Results

Data Acquisition

Use an integrated solution like the FJD Trion S1 3D LiDAR Scanner to capture accurate data.
stockpile scanning diagram

  1. Scout the site: Prior to scanning, thoroughly evaluate the site to analyze the environment and identify potential obstructions to the walking path, and avoid moving people or machinery.
  2. Plan a route: Plan a scanning route that includes enough overlap (at least 5 m) at the start and end points of the scan to ensure at least one loop closure.
  3. Scan: As you scan, move slowly, avoid rapid or sudden turns, and ensure the scanner is pointed straight at the stockpile to maximize data integrity. Use real-time kinematic (RTK) to assist in mapping if the stockplies are located outdoors, and weather conditions are favourable.

Data Processing

Process the point cloud model in software programs like FJD Trion Model.
FJD Trion Model workflow

  1. Boundary Clipping: Remove objects outside the target stockpile.
  2. Point Cloud Denoising: Trim noise points caused by environmental factors like moving people automatically or manually.
  3. Hole Filling: Fill in missing data points by applying a curvature-based mesh.

Generate a volume report after all edits are complete.

Sample volume report

Application of Results

  1. Stockpile Volume: Determine the total volume of the stockpile being measured.
  2. Footprint: Obtain the projected footprint of the stockpile.
  3. Stack Height: Measure the height of the stockpile at various locations.
  4. Surface Area: Accurately calculate the surface area of the stockpile.
  5. Excavation and Filling Volume: Create a plane for volume calculation during excavation and filling.
  6. Contour Maps: Generate contour maps with customizable spacing.


Let's look at a couple of real-world examples of how the FJD Trion S1 is transforming stockpile measurement:

Case 1: Power Plant Inventory

In a Southeast Asian power plant, the FJD Trion S1 three-dimensional laser scanner was used to calculate the volume of an 18,000-square-meter coal pile. The entire operation, including scanning and data processing, was completed in just 19 minutes. The detailed data obtained through the Trion Model point cloud post-processing software allowed for accurate coal inventory assessments, optimizing worker schedules and ensuring efficient operations.

Case 2: Aggregates in Poland

In Poland, monthly measurements of aggregate volumes at mobile concrete plants were typically conducted using drone photogrammetry. However, due to no-fly zones for national defense, the surveying method had to change.
FJD Trion S1 + RTK
Enter the FJD Trion S1 scanner equipped with an RTK (Real-Time Kinematic) kit. 

Software process

In just 30 minutes, the surveyor measured stockpile volumes of over 15,000 cubic meters with exceptional accuracy. 

Stockpile vs pointcloud

The point cloud data were processed and transformed into the national coordinate system, enabling comparisons with previous measurements.


3D laser scanning technology, exemplified by the FJD Trion S1, is reshaping stockpile measurement. It offers speed, accuracy, and efficiency that traditional methods can't match. By embracing this technology, industries can make more informed decisions, improve operational efficiency and safety, and gain a competitive edge.

Learn more about the FJD Trion S1 scanner here.

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