Digitizing Volume Management for Embankment Construction! Comprehensive Guide to Tools That Enable Instant On-Site Measurement

Embankment work at construction sites is not merely transporting and piling soil, but an extremely important process that requires meticulous management based on accurate volume calculations. Traditional surveying methods created cross-sectional drawings from multiple measurement points and calculated volumes from them, but this approach had many challenges and limitations. The more complex the site terrain becomes, the more subjectivity enters into the placement of measurement points, and errors accumulate in the final volume calculation. Furthermore, even if multiple surveyors perform the same work, the results can vary, compromising consistency in management. However, using 3D point cloud data greatly mitigates these issues. A 3D point cloud is the coordinate information of millions to tens of millions of points acquired by laser scanning or drones, and by analyzing this with advanced processing techniques, more accurate and reliable volume calculations have become possible.

In this article, digitalization enables on-site measurements to be performed in real time and the system to automatically calculate volumes. The introduction of such cutting-edge technologies dramatically improves the quality of construction management. From the three perspectives of pursuing accuracy, improving efficiency, and reducing costs, we will explain the value of volume calculation using 3D point clouds.

Conventional embankment volume calculation methods and challenges

Traditional embankment volume calculations have been carried out primarily by combining two methods: the cross-section method and the longitudinal-section method. In the cross-section method, multiple sections are set perpendicular to the construction line, the amount of soil in each section is calculated, and the total embankment volume is obtained by summing them. This approach is particularly effective for linear projects such as road construction and has been a reliable method adopted at many sites for many years. Typically, cross sections are set at intervals of 10 m (32.8 ft) to 20 m (65.6 ft), and the ground elevation at each location is estimated from multiple survey points. However, when the site topography is complex—for example, where valleys are intricately incised, existing structures are scattered, or rock is exposed—judgement is required to determine appropriate section locations.

At the stage of selecting cross‑section locations, there is a serious issue in that the surveyor’s experience and judgment can greatly influence the results. For example, if cross sections are taken at 10 m (32.8 ft) intervals at one site but at 15 m (49.2 ft) intervals at another, the calculated results can differ even for the same terrain. In the worst case, calculation errors can exceed 5 percent, and in large-scale projects this can translate into differences in earthwork volume of several hundred cubic meters or more. Furthermore, fine topographic variations between cross sections cannot be fully captured by the cross‑section method. If the surface undulates, contains locally deep depressions, or fills have been constructed to accommodate complex terrain such as alluvial fans, these features are not reflected in the calculations, causing systematic errors in the final volume.

The longitudinal section method suffers from the same problems. In this approach, cross-sections are produced along the project’s centerline and volumes are calculated from terrain changes before and after construction. However, terrain changes in directions perpendicular to the centerline are difficult for these sectional methods to capture accurately. In particular, when the terrain changes abruptly near the edges of embankments, capturing those changes accurately requires many measurement points, which in turn greatly increases the surveying effort. Also, because terrain can change slightly over time, it is difficult to verify that no unintended terrain changes occurred between the pre-construction and post-construction surveys.

Characteristics and Advantages of 3D Point Cloud Data

3D point cloud data has the potential to fundamentally solve the problems of conventional cross-section methods. A 3D point cloud is a digital record of the coordinates of countless points in space, and each point contains three-dimensional information: X coordinate, Y coordinate, and Z coordinate (elevation). Such dense point cloud data can be efficiently acquired by a combination of laser scanners, cameras and IMUs (inertial measurement units) mounted on drones, and GNSS receivers. What is important is that this point cloud data captures even the minute undulations of the ground surface. Topographic changes on the order of millimeters (mm; in) are also recorded and stored as data.

The greatest advantage of 3D point cloud data is its overwhelming density of measurement points. In conventional surveying, depending on site conditions, it was common to have dozens to hundreds of measurement points per hectare. By contrast, 3D point clouds can yield tens of thousands to hundreds of thousands of points, or in some cases millions of points, over the same area. This dramatic difference in density means that fine variations in terrain are fully captured, and as a result volumes can be calculated with higher accuracy. Also, once 3D point cloud data is acquired, it can be analyzed later from various angles and viewpoints. The high reproducibility—different surveyors analyzing the same data will obtain the same results—is another important advantage that traditional methods could not provide. Because the objectivity of the data is guaranteed, if questions arise later about calculation results, it is easy to reuse the data to perform recalculations.

Moreover, 3D point cloud data makes time-series comparison extremely easy. By acquiring data at multiple points in time—such as the early, middle, and final stages of embankment construction—and overlaying them, it becomes possible to understand in detail which parts of the embankment have progressed and by how much, or whether any uneven construction has occurred. Such time-series analysis enables improved construction quality and early detection of unexpected problems. Furthermore, if a construction-quality issue is found, tracing its cause is also straightforward. For example, if it is discovered that the embankment height at a certain location falls short of the plan, data analysis can be used to infer whether the cause is equipment failure, worker error, or ground subsidence.

On-site 3D point cloud data acquisition methods

There are several options for efficiently acquiring 3D point cloud data at embankment sites. The first is the use of drones equipped with laser scanners. This approach has the major advantage of being able to measure large areas in a short time. Because drones can be flown with minimal manpower, they can safely perform measurements on hazardous slopes or in areas that are difficult to access. Typically, they are flown to about 100 m (328.1 ft) above ground and pass over the construction area multiple times to collect measurement data. With drone surveying, it is possible to measure several hectares in a single day, making it particularly time-efficient for large construction areas. However, drone-based surveying has the drawback of being susceptible to weather. Rain or strong winds can make flight difficult, and because the sun’s position differs greatly between morning and afternoon, shadow patterns change, which can affect the quality of the point cloud data.

The second option is the use of a ground-based laser scanner. In this method, the scanner is mounted on a tripod and measurements are taken from multiple positions on site in sequence. Ground-based scanners have the advantage of higher accuracy than drones. Typically, errors are kept to a few centimeters or less (a few in or less), and measurement accuracy at close range is particularly good. They can also obtain relatively accurate data around complex terrain and existing structures. However, because the area that can be covered by a single scan is limited, large construction areas require many measurement positions, which in turn increases the time required for surveying work. Furthermore, registration—the process of aligning multiple scans acquired from different positions into a unified coordinate system—is necessary, and this process involves technical effort.

The third option is to use photogrammetry. By processing high-resolution images captured from multiple angles, it generates a 3D point cloud. This approach has the significant advantage of being low-cost to implement, and with a drone equipped with a high-performance camera it can achieve sufficient accuracy. However, on soil surfaces with a uniform texture it can be difficult to extract feature points, posing a risk of reduced measurement accuracy. In particular, newly deposited soil often has a uniform surface and photogrammetry algorithms may not be able to find feature points, so caution is required. The choice of the optimal method should be made by comprehensively considering multiple factors such as project scale, site topography, accuracy requirements, budget allocation, and weather conditions.

Process for Calculating Volume from 3D Point Cloud Data

Once 3D point cloud data has been acquired, the subsequent data processing stage becomes extremely important. First, the acquired point cloud data contains noise that needs to be removed. Noise refers to points generated by measurement errors rather than the actual ground surface. For example, points captured when the drone was vibrating, points reflected from low-reflectivity objects, points that captured dust or other particles in the atmosphere, or points that mistakenly recorded parts of existing structures all qualify as noise. Properly removing these points greatly improves the accuracy of subsequent processing. Statistical methods that automatically detect outliers are often used for noise removal.

Next, it is necessary to distinguish between embankment areas and non-embankment areas. This is called a classification process, in which a computer automatically extracts embankment regions from terrain features, or an operator manually specifies the areas. Automatic classification is fast, but because its accuracy may not be perfect, verification is indispensable. Manual specification takes time, but yields more reliable results. In practice, a hybrid approach—checking the results of automatic processing and making adjustments as needed—is most efficient. For example, workers visually confirm the boundary lines of embankment areas and correct any discrepancies with the automatic classification results.

When the fill area is determined, compare the two point cloud datasets—the pre-construction surface and the post-construction surface—and calculate the volume difference. This calculation is performed by aligning the two point clouds in a unified coordinate system, determining the elevation difference at each point, and aggregating those differences on a grid. The results yield not only the total volume for the fill area but also the volume for each subarea. This makes it possible to grasp construction progress in detail. For example, by dividing the construction area into a grid of 5 m (16.4 ft) squares and calculating the volume within each grid cell, it becomes immediately clear which parts of the work are lagging behind.

Steps for Practical Application in the Workplace

When actually applying 3D point cloud data at an embankment construction site, a stepwise approach is effective. First, as the initial stage, record the pre-construction conditions in detail. Because the measurement accuracy at this stage becomes the baseline for all subsequent comparative calculations, it requires careful attention. It is also important to perform multiple measurements and verify the consistency of the data. Recording all conditions, such as measurement time, weather conditions, and the drone’s flight parameters, will be useful later when conducting quality assessments.

In the second stage, after construction begins, data are collected at regular intervals. Typically, measurements are taken when the embankment volume reaches a predetermined reference amount, or when it reaches progress milestones that serve as indicators of construction progress (for example, 30 percent, 60 percent, 90 percent of the plan). These periodic measurements allow verification of whether the work is proceeding as planned. If deviations from the plan are detected, their causes can be identified and the construction plan adjusted. For example, if it is discovered that embankment progress in a particular area is significantly behind the plan, an investigation can determine whether the cause is an issue with the placement of heavy machinery or an unexpected change in soil properties, and appropriate countermeasures can be taken.

In the third stage, after construction is completed, the final volume is measured and compared with the design value. This comparison provides a basis for assessing construction accuracy and, if necessary, deciding on additional works or corrections. Normally, embankment construction requires accuracy within ±5 percent of the design value, but by utilizing 3D point cloud data this accuracy requirement can be reliably met. In addition, this data can be used to improve accuracy in future similar projects. By analyzing accumulated data to understand the difficulty of construction under specific terrain conditions, staffing and scheduling for future projects can be made more rational.

Practical Tips for Improving Accuracy

There are several practical tips for improving the processing accuracy of 3D point cloud data. The first is the installation of ground control points (GCPs). This involves placing multiple points on-site with known coordinates and linking them to the measurement data to enhance overall coordinate accuracy. Especially in large construction areas, the number and arrangement of these ground control points greatly affect data accuracy. In general, it is recommended to place them at the four corners and the center of the construction area. Ground control points should be made of highly reflective materials and be clearly identifiable during measurement. In drone-based aerial surveys, particularly over large areas, employing multiple ground control points has been reported to improve accuracy by more than five times.

The second is consideration of environmental conditions during measurement. Measuring at the same time of day standardizes the direction of sunlight and minimizes the impact of shadows. Also, measurements should be avoided on rainy days or days with high humidity. Under these conditions, lasers and cameras can operate unreliably, posing a risk of reduced data quality. Furthermore, the ambient temperature during measurement also has an impact. In extremely low-temperature environments, drone battery performance deteriorates and flight time is shortened. When planning measurements, it is important to fully take weather conditions into account and choose the optimal measurement day.

The third point is the selection and proper configuration of data processing software. Point cloud processing software comes in a variety of products, each adopting different algorithms. By choosing the software best suited to your company's site conditions and appropriately adjusting its parameters, higher accuracy can be achieved. Comparing and reviewing results processed by multiple software packages is also an effective quality assurance method. For example, by processing the same point cloud data with multiple software packages and checking the differences in the calculation results, you can discover that a particular software is not suitable for the characteristics of the site.

Path to Streamlining Embankment Volume Management

By leveraging 3D point cloud data, the entire process of managing embankment volumes can be greatly streamlined. With traditional methods, surveying and volume calculation could take anywhere from several days to several weeks. In contrast, using 3D point clouds can significantly shorten the time from measurement to report preparation. Moreover, because the data are managed digitally, multiple stakeholders can share the same information, greatly improving transparency in construction management. Owners, designers, contractors, and supervisors can all access the same data and monitor construction progress in real time.

The benefits of such digitization go beyond mere time savings. By enabling decision-making based on accurate and detailed data, it leads to optimization of construction planning and early detection of problems. In addition, the accumulated data can be used as benchmark information for future similar projects, contributing to improved overall quality of operations. For example, if data on embankment settlement amounts and compaction characteristics under specific terrain conditions are accumulated, prediction accuracy for new projects improves.

Currently, many construction companies are advancing the introduction of earthwork management systems that utilize 3D point cloud data. These companies are achieving significant cost reductions and quality improvements through automation of measurements, increased efficiency in data processing, and standardization of reporting processes. Introducing such cutting-edge technology at your site can also be expected to bring substantial benefits.

The Potential for High-Precision Measurements Using Smartphones

In recent years, devices that add high-precision positioning measurement functions to smartphones have appeared, and they are poised to revolutionize embankment measurement. Conventional drones and scanners were very expensive and complicated to maintain, but smartphone-based solutions greatly lower the barriers to adoption. By utilizing equipment such as GNSS high-precision positioning devices that attach to iPhones, field workers can obtain location information with centimeter-level accuracy (half-inch accuracy) while carrying a device small enough to be portable. These mobile devices require relatively low initial investment, making it economically feasible to deploy multiple units.

By using such mobile devices at multiple measurement points and collecting their coordinate information, it is possible to achieve an information density equivalent to point cloud data. Furthermore, a workflow in which data are sent to the cloud in real time and processing results can be checked while on site can also be realized. By leveraging smartphones, on-site staff without special training can participate in measurement tasks, resulting in a significant increase in site flexibility. In addition to improved work efficiency, worker safety is also enhanced. Measurements using conventional surveying instruments required carrying heavy equipment and performing work on hazardous slopes, but by using mobile devices, lightweight and safer measurements can be achieved. Going forward, such mobile-based high-precision measurement systems are expected to become mainstream for embankment volume management.