Table of Contents

• Introduction: The Importance and Challenges of Differential Earthwork Volume Management

• Benefits of “Visualizing” Earthwork Volumes Using Point Clouds

• Conventional Volume Measurement Methods and Their Limitations

• Simple Ways to Acquire 3D Point Clouds On Site

• Instant Differential Volume Calculation with High-Precision GNSS and a Smartphone

• Immediate Point Cloud Sharing via the Cloud

• One-Click Automatic Creation of As-Built Reports

• Conclusion: Promoting On-Site DX with Simple Surveying Using LRTK

• FAQ

Introduction: The Importance and Challenges of Differential Earthwork Volume Management

In civil engineering and land development, accurately measuring and managing the volume of earthwork (the amount of soil, or soil volume) associated with excavation and embankment is critically important. Whether the specified amounts were placed or removed before and after construction directly affects progress management (quantity control), acceptance of as-built inspections, and even contract payments. Therefore, surveying the terrain before and after construction and calculating the differential earthwork volume—the volumetric difference between the two surface models—is an essential process to verify that embankments were built to design and required excavations were achieved.

However, traditional differential volume measurement has many challenges. Terrain surveying itself is labor-intensive and time-consuming, and it is difficult to measure a large site densely in a short time. Limited measurement points cannot cover the entire site, and sparse measurement points risk overlooking small undulations, excess fill, or leftover excavation. As a result, there is a risk of additional earthworks after as-built inspection to correct shortages or over-excavation. Surveying on cliffs or steep slopes also poses safety hazards for workers. Especially for large-scale earthworks, it is unrealistic to cover the whole area manually, and new methods that measure volumes more efficiently and accurately have been sought.

Benefits of “Visualizing” Earthwork Volumes Using Point Clouds

A promising solution to these challenges is earthwork management using three-dimensional point cloud data. Point cloud data (point clouds) are 3D survey data that represent surfaces of terrain and structures as countless points. Each point has X, Y, Z coordinates (and sometimes attributes like color or reflectance) and can be acquired by laser scanners or photogrammetry. Dense point clouds that scan the entire terrain enable detailed 3D modeling that closely resembles reality. Elevation changes that are hard to grasp from flat drawings or photos can be intuitively visualized for the entire site using point clouds—this is a major advantage.

With point-cloud-based volume calculation, embankment and excavation volumes are obtained by directly comparing pre- and post-construction terrain data. Because point clouds capture the surface with countless measurement points, there is no need to interpolate between points as in conventional methods, enabling accurate volume computation that reflects fine surface irregularities. Once obtained, point cloud data can be stored as digital 3D records, allowing flexible reanalysis such as recalculating volumes for arbitrary areas or testing different reference surfaces without additional field surveys. The ability to reuse data repeatedly without extra site work also brings efficiency benefits.

The accuracy and reliability of point-cloud volume calculations have already been demonstrated. In validation cases, differences between volumes calculated from point clouds and those from conventional manual surveys have been reported to be around 1%. With proper conditions and operation, point-cloud volume calculation can achieve accuracy sufficient for field use. Recently, overlaying design data onto acquired point clouds and color-coding deviations (heat-mapping) has made it possible to visually identify embankment or excavation excesses and shortages. This not only provides volume values but also shows at a glance where soil is lacking or surplus, enabling quick identification of areas needing correction. Thus, point-cloud utilization raises both the precision of earthwork management and the clarity of results.

Conventional Volume Measurement Methods and Their Limitations

Traditional differential volume calculations have mainly used surveying instruments such as total stations (TS) and levels combined with CAD software. A typical workflow involves sending a surveying team to measure ground elevations at grid intervals or along representative cross-sections before construction. After completion, the site is surveyed again to obtain pre- and post-construction elevation data. Back at the office, these measurement points are processed into drawings and analyses. The average cross-section method calculates volumes per section from area differences and distances and sums them up. Alternatively, a digital terrain model (TIN) can be generated from point groups and the volume difference between two models computed automatically in CAD.

Such conventional methods require multiple field surveys and cumbersome data processing, so results often take days and the site may have moved to the next work phase by the time results are ready. The high workload combined with lack of real-time capability creates a dilemma where measured data are difficult to use immediately on site. Cross-section methods also rely on interpolation between measurement points, which can introduce errors depending on point layout. Overall, manual-dependent volume measurement is increasingly inadequate in terms of efficiency, accuracy, and speed for modern requirements.

Simple Ways to Acquire 3D Point Clouds On Site

While point clouds are clearly useful for volume management, the challenge has been how to acquire them easily on site. Traditionally this required expensive terrestrial 3D laser scanners, survey drones, or dedicated survey teams. However, recent advances in photogrammetry have enabled site staff to use smartphones or consumer drones to capture images and derive point clouds. Even without special equipment, familiar cameras can capture the site and generate 3D models from images, greatly lowering the barrier to point-cloud measurement.

Photogrammetry-based point cloud acquisition allows wide-area, easy measurement with handheld devices. For example, flying a drone collects photos of a large site quickly and can photograph steep or hazardous areas remotely. Using a smartphone camera to take sufficient photos from various angles and processing them with dedicated software can generate a high-density point cloud. Being able to create 3D point clouds with off-the-shelf cameras rather than expensive laser scanners is revolutionary and is attracting attention as a DX tool for sites.

Photogrammetry does have some challenges. Accuracy depends heavily on image resolution, exposure, and the presence of texture on the subject. Low-light or highly reflective areas are prone to errors, and dense vegetation or debris increases preprocessing effort to extract ground surface points. After shooting, image processing (point cloud generation) can take hours on a high-performance PC or cloud service, so completing the workflow from capture to volume calculation entirely on site can be difficult. Drone use also requires prior flight permissions and piloting skills. Moreover, smartphone-only photogrammetry may include positional errors in the captured images, causing the generated point cloud to be offset from the actual coordinate system. If the point cloud’s absolute height and position are unclear, it cannot be used for as-built quantity calculations. Thus, photogrammetry traditionally required setting control points on the ground to align the model to reference coordinates.

On the other hand, recent smartphones with LiDAR (light detection and ranging) can acquire point clouds while shooting, offering new possibilities. Scanning the site with a LiDAR-equipped tablet or phone generates point cloud data in real time on site. However, LiDAR alone may not provide sufficient georeferencing accuracy, so methods to attach precise positioning information to acquired point clouds are required. Combining these latest technologies is key to enabling anyone on site to complete high-accuracy point-cloud measurement easily.

Instant Differential Volume Calculation with High-Precision GNSS and a Smartphone

Integrating these latest technologies has produced the solution called “smartphone point-cloud surveying,” which allows “anyone to perform high-accuracy point-cloud surveys immediately.” Of particular note is a system that pairs a smartphone with a high-precision GNSS receiver (for example, LRTK), enabling centimeter-level positioning and 3D scanning on site. With a smartphone plus a small GNSS antenna—easy to carry—point clouds with accurate reference coordinates, which once required specialized equipment, can now be obtained.

With smartphone point-cloud surveying, acquired point cloud data can be uploaded to the cloud and differential volumes calculated automatically. For example, an LRTK cloud service can take an uploaded point cloud and, with a single click, compute the difference relative to a pre-registered design surface or past terrain data to instantly output embankment and excavation volumes. No complex software operation or manual calculation is necessary; quantities can be obtained quickly while on site. This workflow eliminates the photogrammetry problem of a time lag in obtaining results and enables measuring and immediately knowing volumes on the spot.

The efficiency gains from point-cloud utilization are notable. In one large site, a task that previously required four people for seven days was switched to drone photogrammetry plus point cloud analysis and completed by two people in one day. The working time was reduced to about 1/14 while the computed as-built quantity difference remained around 1% compared to conventional methods, confirming a dramatic improvement in efficiency and accuracy. High-precision GNSS also eliminates the need to install surveying control points on the ground, contributing not only to time savings but overall labor reduction across the process. Instant volume calculation using smartphones and GNSS can truly elevate construction management productivity to another level.

Note: the centimeter-level positioning described here should be understood as cm level accuracy (half-inch accuracy).

Immediate Point Cloud Sharing via the Cloud

Using a cloud platform allows acquired point clouds and computed results to be shared from the field instantly. Survey data are automatically saved to the cloud, so supervisors or clients in the office can view the site’s 3D model from a web browser in real time. Stakeholders in remote locations can inspect the same data simultaneously, eliminating communication delays and reducing rework caused by misunderstandings. Regular scanning of a large project weekly or monthly enables quantitative visualization of earthwork progress, smoothing progress reports and intermediate inspections. For remote sites, cloud-based sharing allows virtual inspections from the office, reducing travel time and personnel costs.

Sharing point cloud data also means sharing the full “irrefutable evidence” underlying quantity calculations. Rather than presenting only computed numbers, you can present the 3D terrain that produced them, which is highly persuasive for client explanations. In some cases, sharing point cloud data has eliminated the need for in-person verification with a tape measure under supervision, simplifying inspection procedures. The ability for everyone to instantly share the same visual information is a groundbreaking benefit that greatly streamlines site consensus-building.

One-Click Automatic Creation of As-Built Reports

Utilizing point clouds also streamlines the entire process from surveying to report generation. Traditionally, teams manually prepared drawings and tables from survey data to assemble reports. However, cloud platforms can automatically generate standardized as-built reports from measurement results. For example, LRTK Cloud provides a feature to output reports in a predefined form (PDF) from acquired point cloud data, allowing generation of a measurement report that includes photos, coordinate values, and notes with a single button. This removes the need to format results in Excel or CAD and greatly reduces the effort required to prepare report materials.

Reports can include not only automatically calculated embankment and excavation volumes but also cross-section and longitudinal/ transverse views extracted from the point cloud and 3D view images. This lets recipients directly compare document values with site reality, making it very useful for client presentations and as-built inspections. Since point cloud data themselves serve as the factual backing of site conditions, including them in reports is highly valuable. In practice, after comparing point clouds acquired by LRTK at embankment completion with the design surface and transferring automatic volume calculations to an as-built quantity table, attaching cross-section diagrams and 3D view images generated from the point cloud to the report allowed rapid and smooth as-built confirmation with the client. Speeding up measurement-to-report processes with point clouds accelerates site decision-making and robustly supports the PDCA cycle of civil engineering construction.

Conclusion: Promoting On-Site DX with Simple Surveying Using LRTK

Smartphone point-cloud surveying and differential volume calculation have the potential to transform earthwork management that once relied heavily on manual labor. Using GNSS-linked systems such as LRTK enables anyone to quickly and accurately grasp as-built conditions over wide areas, dramatically improving site productivity, safety, and quality. In a construction industry that requires ICT and DX promotion, introducing such familiar, easy-to-use smart tools is a first step toward smarter site management.

By adopting simple surveying with LRTK on site, you can measure whenever needed and immediately share and report results. This enables rapid decision-making based on high-accuracy as-built data while greatly reducing manpower and time, leading to improved overall efficiency and quality assurance of the project. Why not try this new, unconstrained approach to earthwork management at your site?

FAQ

Q: Can point clouds acquired with a smartphone meet the accuracy required for as-built management? A: For public works as-built management, a density of several dozen points per 1 m² (1 m² ≈ 10.8 ft²) on the ground is generally recommended. Smartphone LiDAR is not as dense as professional laser scanners, but by scanning slowly and carefully you can acquire a sufficient number of points. Positioning the scans with high-precision GNSS also secures positional accuracy, and with proper operation smartphone point clouds can achieve errors on the order of a few cm (a few in). Validation tests have confirmed that volumes calculated from smartphone + GNSS point clouds are comparable in accuracy to conventional surveys.

Q: Can measurements be taken in locations with poor satellite reception? A: High-precision GNSS performs best in open-sky conditions, but stable positioning is possible even in partially obstructed sites by using multiple GNSS constellations and augmentation signals. In forested or urban environments where satellite signals are easily blocked, accuracy may temporarily degrade, but you can cover such areas by combining ground control points. LRTK supports multiple frequencies and is compatible with augmentation information (CLAS) provided by the Japanese Quasi-Zenith Satellite System (“Michibiki”), enabling continued centimeter-level positioning even in mountainous areas without Internet connectivity.

Q: Is there a difference in measurement accuracy between flat sites and sloped terrain? A: In photogrammetry, vertical accuracy can be affected by camera orientation, but you can secure accuracy on slopes by photographing from multiple directions and applying GNSS height correction. Smartphone LiDAR emits from multiple angles during scanning, so it can capture undulating slopes without issue. However, steep slopes may have areas not visible from above, so combining drone aerial photography to cover blind spots is effective. Overall, with appropriate capture methods, both flat and sloped sites can achieve accuracy sufficient for as-built measurement.

Q: How can differences between pre- and post-construction be confirmed from point clouds? A: By comparing two point clouds (pre- and post-construction, or current surface and design surface), you can visualize not only volume differences but their spatial distribution. Displaying height differences in a color-coded heat map makes it intuitive to see where and how much soil was added or removed—for example, red for areas higher than design and blue for lower—so corrective areas are immediately obvious. You can also cut arbitrary cross-section lines on the point cloud and overlay pre- and post-construction cross-sectional shapes. These functions allow not only numerical results but also visual confirmation for acceptance decisions and site feedback.

Q: How can measurement data and volume calculation results be output and shared? A: Point clouds and calculation results can be easily shared and output via the cloud. LRTK Cloud can issue sharing links to a dedicated viewer where stakeholders can inspect and measure the data in 3D. Embankment and excavation results can be output as PDF reports and used directly as submission documents. Point cloud data can also be downloaded in common formats (LAS, XYZ, etc.) for secondary use in CAD or other point-cloud processing tools. These capabilities make data utilization and reporting smooth.