How to Reduce Surveying Costs for Embankment Volume｜Low-Cost Measurement Achieved with Smartphone × RTK

Earthfill work at construction sites is not merely transporting and piling soil; it is an extremely important process that requires meticulous management based on accurate volume calculations. Traditional surveying methods created cross-sections 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 when multiple surveyors carry out the same task, the results can vary, undermining consistency in management. However, by utilizing 3D point cloud data, this issue can be greatly improved. A 3D point cloud refers to coordinate information of millions to tens of millions of points acquired by laser scanning or drones, and by analyzing this data with advanced processing techniques, more accurate and reliable volume calculations have become possible.

This article explains how combining smartphones with high-precision GNSS technology can enable low-cost measurements that replace traditional expensive surveying systems. From the three perspectives of pursuing accuracy, improving efficiency, and reducing costs, we will explain the value of using 3D point clouds for volume calculation.

Conventional Embankment Volume Calculation Methods and Challenges

Conventional embankment volume calculations have been carried out mainly 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 from their sum. This approach is especially 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-surface elevation at each location is inferred from multiple survey points. However, when site topography is complex—for example, when valley topography is intricately convoluted, existing structures are scattered, or bedrock is exposed—judgment is required to determine appropriate section locations.

At the stage of selecting cross-section locations, there is a serious issue that the surveyor's experience and judgment can heavily influence the results. For example, at one site cross-sections were taken at 10 m (32.8 ft) intervals, while at another site they were taken at 15 m (49.2 ft) intervals, and the calculated results can differ even for the same terrain. In the worst case, calculation errors can reach 5 percent or more, which in large-scale projects can translate into differences of hundreds of cubic meters of earth. Furthermore, fine topographic variations between cross-sections cannot be fully captured by the cross-section method. If the ground surface varies in a wavelike manner, if there are locally deep depressions, or if embankments have been constructed to accommodate complex terrain such as alluvial fans, these features will not be reflected in the calculations, causing systematic errors in the final volumes.

Longitudinal section methods also suffer from the same problems. In this approach, cross-sections are generated along the project's centerline and volumes are calculated from terrain changes before and after construction. However, terrain changes in the direction perpendicular to the centerline are difficult for these section methods to capture accurately. In particular, when the terrain changes rapidly near the edges of embankments, many measurement points are required to capture those changes precisely, which greatly increases the surveying workload. Additionally, the terrain can change slightly over time, making it difficult to verify whether unintended terrain changes occurred between the pre-construction and post-construction measurements.

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 digital data that records the coordinates of countless points in space, with each point containing 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, drone-mounted cameras and IMUs (inertial measurement units), and GNSS receivers. Importantly, this point cloud data captures even subtle undulations of the ground surface. Terrain changes on the order of millimeters (mm) — approximately 0.04–0.35 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. In contrast, 3D point clouds can yield tens of thousands to hundreds of thousands, and in some cases millions, of points over the same area. This dramatic difference in density means that all fine variations in terrain are recorded, and as a result volumes can be calculated with higher accuracy. Moreover, once 3D point cloud data is acquired, it can be analyzed from various angles and viewpoints afterward. The high reproducibility—different surveyors analyzing the same data obtain the same results—is another significant advantage not achievable with traditional methods. Because the objectivity of the data is guaranteed, if questions arise later about calculation results, it is easy to reuse the data and recompute.

Furthermore, 3D point cloud data is extremely easy to compare over time. By acquiring data at multiple points — such as the early, middle, and completion stages of embankment works — and overlaying them, you can precisely determine which parts of the embankment have progressed and by how much, or whether uneven construction is occurring. This kind of time-series analysis enables improved construction quality and the early detection of unexpected problems. Moreover, 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 is below the planned level, data analysis can help infer whether the cause is equipment failure, operator error, or ground subsidence.

On-site 3D Point Cloud Data Acquisition Methods

To efficiently acquire 3D point cloud data at an embankment construction site, there are several options. The first is using a drone equipped with a laser scanner. This approach has the major advantage of being able to survey large areas in a short time. Because drones can be operated without manual intervention, measurements can be conducted safely on hazardous slopes and in areas that are difficult to access. Generally, the drone is flown up to an altitude of approximately 100 m (328.1 ft) above ground, making multiple passes over the construction area to collect measurement data. Drone surveying can cover several hectares per day, making it particularly time-efficient for expansive construction areas. However, drone-based surveying has the drawback of being susceptible to weather conditions. Flying becomes difficult on rainy or windy days, 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 sequentially from multiple positions on site. Ground-based scanners have the advantage of higher accuracy than drones. Typically, errors are kept to a few centimeters (a few inches) or less, and measurement accuracy at close range is particularly good. They can also acquire relatively accurate data around complex terrain and existing structures. However, because the area covered by a single scan is limited, many scanning positions are required on large construction sites, which increases the time required for surveying. Furthermore, a process called registration is necessary to align multiple scans acquired from different positions into a unified coordinate system, and this process requires technical effort.

The third option is to use photogrammetry. By processing high-resolution images taken from multiple angles, it generates a 3D point cloud. This approach has the major advantage of being low-cost, and with a drone equipped with a high-performance camera you can achieve sufficient accuracy. However, on soil surfaces with a uniform texture, extracting feature points can be difficult, posing a risk of reduced measurement accuracy. In particular, freshly deposited soil often has a uniform surface, and photogrammetry algorithms may fail to find feature points, so caution is needed. Choosing the optimal method must be determined 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, and this noise needs to be removed. Noise refers to points generated by measurement errors rather than the actual ground surface. For example, points captured when a drone was vibrating, points reflected from low-reflectivity objects, points that recorded dust in the atmosphere, or points where parts of existing structures were mistakenly recorded all correspond to noise. By appropriately removing these, the accuracy of subsequent processing is greatly improved. For noise removal, statistical methods that automatically detect outliers are often used.

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 regions. Automatic classification is fast, but its accuracy may not be perfect, so verification is essential. Manual specification takes time but yields more reliable results. In practice, the most efficient approach is a hybrid one: checking the results of automatic processing and adjusting them as needed. For example, workers visually check the boundary lines of embankment areas and correct any discrepancies with the automatic classification results.

Once the fill area is defined, compare the two point cloud datasets—the pre-construction ground surface and the post-construction ground surface—and calculate the volume difference. This calculation is performed by aligning both point clouds in a unified coordinate system, determining the elevation difference at each point, and aggregating those differences into a grid. The results provide not only the total volume of the fill area but also the volumes for smaller subareas. This allows detailed monitoring of construction progress. 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 are falling behind.

Steps for practical application in the workplace

In practice, when utilizing 3D point cloud data at an embankment construction site, a phased approach is effective. As the first phase, record the pre-construction conditions in detail. The measurement accuracy at this stage will serve as the baseline for all subsequent comparative calculations, so it is necessary to take sufficient care. It is also important to conduct multiple measurements and verify the consistency of the data. Recording all conditions—measurement time, weather conditions, drone flight parameters, and so on—will serve as a useful reference when performing quality evaluations later.

In the second stage, after construction begins, data are acquired periodically. Generally, measurements are taken when the embankment volume reaches a predetermined reference amount, or when it reaches quantities that serve as milestones of construction progress (for example, 30 percent, 60 percent, 90 percent of the plan). These periodic measurements allow verification of whether construction is progressing according to plan. If deviations from the plan are found, their causes can be identified and the construction plan adjusted. For example, if it is discovered that embankment progress in a specific area is significantly lagging behind the plan, an investigation can determine whether the cause is equipment placement issues or unexpected changes in soil conditions, and appropriate countermeasures can be implemented.

In the third phase, the final volume is measured after construction completion and compared against the design values. This comparison provides the basis for evaluating construction accuracy and, if necessary, deciding on additional work or corrective measures. Typically, embankment construction requires accuracy within ±5 percent of the design values, but by using 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 the accumulated data to understand construction difficulty under specific terrain conditions, workforce allocation and project scheduling for future projects can be made more rational.

Practical tips for improving accuracy

There are several practical tips to improve the processing accuracy of 3D point cloud data. The first is the placement of ground control points (GCPs). This involves installing multiple points on-site with known coordinates and tying them to the survey data to improve overall positional accuracy. Especially in large construction areas, the number and arrangement of these ground control points greatly affect data accuracy. It is generally recommended to place them at the four corners and the center of the site. Ground control points should be made of highly reflective materials and be clearly identifiable during surveying. For aerial surveys using drones, it has been reported that using multiple ground control points, particularly over large areas, can improve accuracy by more than five times.

The second consideration is the 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, the operation of lasers and cameras can become unstable, increasing the risk of reduced data quality. Furthermore, the ambient temperature during measurement also has an effect. In extremely low-temperature environments, drone battery performance deteriorates and flight time is shortened. When planning measurement schedules, it is important to fully take meteorological conditions into account and select the optimal measurement day.

The third is the selection of data processing software and appropriate settings. Point cloud processing software comes in a variety of products, each employing different algorithms. By choosing the software best suited to your company’s site conditions and properly adjusting 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 calculation results, you can discover that a particular software is not well suited to the characteristics of the site.

The 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 through volume calculation could take days to weeks. In contrast, utilizing 3D point clouds can significantly shorten the time from measurement to report preparation. Moreover, because the data is managed digitally, multiple stakeholders can share the same information, greatly improving transparency in construction management. Project owners, designers, contractors, and supervisors can all access the same data and monitor construction progress in real time.

The benefits of such digitization are not limited to mere time savings. Because it enables decision-making based on accurate, 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 an overall improvement in the quality of operations. For example, if data on embankment settlement amounts and compaction characteristics under specific terrain conditions are accumulated, the accuracy of predictions for new projects will improve.

Currently, many construction companies are increasingly adopting embankment management systems that utilize 3D point cloud data. These companies have achieved substantial cost reductions and quality improvements through automation of measurements, increased efficiency in data processing, and standardization of reporting processes. By introducing such cutting-edge technology at your site as well, you can expect significant benefits.

The Potential for High-Precision Measurement 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. Traditional drones and scanners were very expensive and complex to maintain, but smartphone-based solutions greatly lower the barriers to adoption. By utilizing equipment such as iPhone-mounted GNSS high-precision positioning devices, it has become possible to obtain position information with centimeter-level accuracy (half-inch accuracy) from a size portable enough for field workers to carry. These mobile devices require a relatively low initial investment, making it economically feasible to deploy multiple units.

By using these mobile devices at multiple measurement points and collecting their coordinate information, it is possible to achieve an information density equivalent to that of point cloud data. Furthermore, a workflow can be implemented in which data is sent to the cloud in real time and processing results can be reviewed on-site. By leveraging smartphones, on-site staff without special training can participate in measurement tasks, significantly increasing on-site flexibility as a result. In addition to improved operational efficiency, worker safety is also enhanced. Traditional surveying equipment required carrying heavy instruments and performing work on hazardous slopes; by contrast, mobile devices enable lightweight and safer measurements. Going forward, such mobile-based high-precision measurement systems are expected to become mainstream for embankment volume management.