Stockpile Measurement & Cut/Fill Analysis
How LiDAR Enables Volume Calculation
Volume calculation requires two things: an accurate reference surface and an accurate current surface. LiDAR provides both through its ability to capture millions of elevation points per second from aerial platforms.
The core workflow involves three stages:
- Point cloud classification: separating ground points from vegetation, buildings, and other objects
- Surface generation: creating a DTM (bare earth) and/or DSM (top surface including objects) from the classified points
- Volume computation: calculating the difference between two surfaces or between a surface and a reference plane
The accuracy of the final volume depends directly on the quality of the classification and surface models. Errors in ground point classification cascade into DTM errors, which produce incorrect volume figures.
A DTM generated from classified LiDAR data in Lidarvisor. The bare earth surface is the foundation for accurate volume calculation.
Volume Calculation Methods
There are three primary methods for calculating volumes from LiDAR-derived surfaces. Each serves a different use case.
1. Surface-to-Plane
Stockpile Volume
Measures the volume between a surface model and a flat reference plane. The standard approach for stockpile measurement.
How it works:
- Generate a DSM from the LiDAR point cloud
- Define a reference plane at the stockpile base
- Calculate the volume between them
Accuracy: ±2-5% with drone LiDAR at 50+ points/m²
Industries: Mining, aggregate yards, grain storage, landfill management
2. Surface-to-Surface
Cut and Fill
Compares two surface models to determine where material has been added (fill) or removed (cut). The primary method for earthworks management.
How it works:
- Generate a DTM from the “before” survey
- Generate a DTM from the “after” survey
- Subtract: positive = fill, negative = cut
Key advantage: Centimeter resolution vs. spot measurements
Industries: Road construction, site grading, dam building, dredging
3. Multi-Temporal
Change Detection
Compares surface models from different dates to quantify terrain changes over time.
Applications:
- Mining progress: monthly extraction volumes
- Erosion monitoring: soil or cliff face loss
- Landfill capacity: remaining airspace calculations
- Construction progress: earthwork quantities vs. design
A classified point cloud of a quarry in Lidarvisor. Accurate classification separates ground from vegetation and equipment for reliable volume calculations.
Step-by-Step: Point Cloud to Volume
01
Capture LiDAR Data
Fly the survey area with drone or aircraft LiDAR. Aim for 50+ pts/m² for stockpiles, 10+ pts/m² for large-area earthworks, with 30% swath overlap.
02
Classify the Point Cloud
Separate ground points from vegetation, vehicles, and structures. AI-powered tools like Lidarvisor automate this step, classifying points into 12 standard categories.
03
Generate Surface Models
Create a DTM from ground points (bare earth) and DSM from all first-return points (includes stockpiles). Export as GeoTIFF at 0.1–1.0m cell size.
04
Calculate Volumes
Use GIS or surveying software to compute volumes. For each grid cell, multiply the height difference between surfaces by the cell area and sum all cells.
Need clean DTM and DSM for your volume calculations? Lidarvisor handles the classification and surface generation automatically.
Filtering vegetation from the quarry point cloud reveals the true terrain surface. Clean classification is critical for accurate volume calculations.
DTM vs DSM: Which Surface?
Choosing the correct surface model is critical:
- Use DTM for earthworks cut/fill: bare earth surface excluding temporary objects
- Use DSM for stockpile volume: stockpiles are above-ground objects the DSM captures correctly
- Use both for comprehensive analysis: comparing DSM against DTM gives the most complete picture
Many professionals use a combination: the DTM as the base reference surface and the DSM as the measurement surface. The difference at any point represents the height of above-ground material.
Industry Applications
LiDAR volume calculation serves critical functions across multiple sectors:
Accuracy Considerations
Volume accuracy depends on several factors in the LiDAR processing chain:
| Factor | Impact on Volume Accuracy | How to Mitigate |
|---|---|---|
| Point density | Low density misses surface details on irregular stockpiles | Fly at 50+ pts/m² for stockpiles |
| Classification errors | Vegetation or vehicles misclassified as ground inflates DTM | Use AI classification with vehicle removal |
| Georeferencing | Positional offsets create false volume changes | Use consistent GCP network across surveys |
| DTM resolution | Coarse cell size smooths terrain features and edges | Use 0.1–0.25m cell size for stockpiles |
| Edge delineation | Poor boundaries affect base plane estimation | Capture toe-of-slope clearly in flight planning |
The most common source of error is poor point cloud classification. When vegetation is not properly separated from ground, the DTM includes vegetation height, inflating the apparent terrain elevation. Similarly, vehicles and equipment left on stockpiles during the survey appear as part of the surface, adding false volume.
Lidarvisor’s AI classification addresses both issues by automatically identifying and separating vegetation (low, medium, and high), vehicles, and equipment from ground points, producing clean surface models ready for volume analysis.
Software Comparison for Volume Calculation
Once you have your DTM and DSM exported from Lidarvisor as GeoTIFF files, several software packages can perform the volume computation:
| Software | License | Best For | Volume Tools |
|---|---|---|---|
| QGIS | Free / Open Source | GIS professionals, budget teams | Raster Calculator, Zonal Statistics, Volume tool |
| ArcGIS Pro | Commercial | Enterprise GIS workflows | Cut Fill, Surface Volume, 3D Analyst |
| Civil 3D | Commercial | Civil engineering, road design | TIN Volumes, Grading, Quantity Takeoff |
| Global Mapper | Commercial | General-purpose surveying | Pile Volume, Cut and Fill, Flatten/Fill |
| CloudCompare | Free / Open Source | Point cloud comparison | Cloud-to-Cloud distance, Volume tool |
Streamline with Automated Classification
The bottleneck in most LiDAR volume calculation projects is not the volume computation itself, which is mathematically straightforward. It is the point cloud classification step that precedes surface model generation.
Traditional Approach
Specialized software, extensive parameter tuning, and hours of manual review. For recurring surveys like monthly stockpile inventories, this overhead makes LiDAR-based volumes impractical.
Streamlined with Lidarvisor
Upload your LAS/LAZ file and receive automatic classification into 12 categories, DTM and DSM generation, and GeoTIFF export. Minutes, not hours. Monthly or weekly surveys become practical.
Key Takeaways
- Surface models are the foundation: LiDAR volume calculation relies on accurate DTM and DSM generated from classified point clouds
- Three primary methods: surface-to-plane (stockpiles), surface-to-surface (cut/fill), and multi-temporal comparison (change detection)
- Classification quality matters most: separating vegetation and vehicles from ground is the single biggest accuracy factor
- Automation removes the bottleneck: AI classification makes frequent volume surveys practical
- Use your preferred tools downstream: export DTM/DSM as GeoTIFF for volume computation in any GIS or CAD software
Frequently Asked Questions
With drone LiDAR at 50+ points/m² and proper classification, stockpile volume accuracy is typically ±2-5%. The main accuracy factors are point density, classification quality (especially vehicle and vegetation removal), georeferencing consistency, and DTM cell size resolution.
Monthly surveys are standard for mining stockpile inventory and construction progress tracking. Weekly surveys are practical with automated classification tools and are increasingly common for active construction sites and high-value stockpile operations.
After generating DTM/DSM rasters, you can compute volumes in QGIS (free), ArcGIS Pro, Civil 3D, Global Mapper, or CloudCompare (free). Each has dedicated volume calculation tools for surface-to-plane and surface-to-surface analysis.
Lidarvisor handles the critical first steps: point cloud classification, DTM generation, and DSM generation. These surface models are exported as GeoTIFF files, which you then import into your preferred GIS or CAD software for volume computation.