Visualize Differential Earthwork Volumes with Point Clouds! Instant Cloud Sharing and One-Click Report Generation

Table of Contents

• Introduction: The Importance and Challenges of Differential Earthwork Management

• Benefits of “Visualizing” Earthwork Volumes Using Point Clouds

• Conventional Earthwork Measurement Methods and Their Limitations

• How to Easily Acquire 3D Point Clouds on Site

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

• Immediate Sharing of Point Cloud Data via the Cloud

• One-Click Automatic Generation of As-Built Reports

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

• FAQ

Introduction: The Importance and Challenges of Differential Earthwork Management

In civil and land development works, it is critically important to accurately quantify and manage the volumes of soil involved in excavation and embankment (earthwork volumes). Whether the required amount of material was placed or removed before and after construction directly affects progress management (work-in-progress measurement), pass/fail results of as-built inspections, and even the calculation of contract payments. Therefore, surveying the terrain before and after construction and calculating the differential earthwork volume, the volume difference between the two surfaces, is an indispensable process to verify that embankments were constructed according to design and that the specified excavation volumes were achieved.

However, conventional measurement of differential earthwork volumes has many challenges. First, terrain surveying has traditionally been manpower-intensive, time-consuming, and it is difficult to measure a wide site in detail in a short time. A limited number of survey points cannot cover the entire site, and the coarseness of measurement points can cause small irregularities or leftover embankment/excavation to be overlooked. As a result, there is a risk that remedial work—such as adding missing fill or reworking over-excavation—will be required after as-built inspections. Surveying dangerous locations such as cliffs or steep slopes also raises safety concerns for personnel. Especially in large-scale earthworks, it is unrealistic to cover the entire area manually, and a new method that can measure earthwork volumes more efficiently and accurately has been increasingly demanded.

Benefits of “Visualizing” Earthwork Volumes Using Point Clouds

A promising solution to these challenges is the use of three-dimensional point cloud data for earthwork management. Point cloud data (point clouds) are 3D survey data that represent the surfaces of terrain and structures as a collection of countless points. Each point has X, Y, and Z coordinate values (and sometimes attributes such as color or reflectance) and can be acquired by laser scanners or photogrammetry. From a finely scanned point cloud of the entire terrain, complex terrain can be modeled in 3D with a level of detail close to reality. Unlike planar drawings or photos, point clouds can record site-wide topography in three dimensions, making it intuitive to visualize conditions before and after construction—this is a major advantage.

Using point clouds for earthwork calculations involves directly comparing terrain data from before and after construction to compute fill and cut volumes. Because point clouds capture the surface with countless measurement points, there is no need to interpolate between survey points as in conventional methods, enabling accurate volume calculations that reflect even minute surface irregularities. Moreover, once acquired, point cloud data can be stored as digital 3D records, allowing flexible analysis such as recalculating volumes for arbitrary areas later or estimating against different reference surfaces. The data can be reused repeatedly without additional field surveys, offering clear efficiency benefits.

The accuracy and reliability of point-cloud-based volume calculations have already been demonstrated. In validation examples, the as-built quantities derived from point clouds have in some cases differed from conventional manual survey values by only about 1%. When conditions are controlled and operations are conducted properly, point-cloud-based volume calculations can deliver on-site accuracy sufficient for practical use. Recently, it has also become possible to overlay design data on acquired point clouds and display deviations as color-coded heat maps, visually indicating excesses or shortages in fill and cut. This shows not only the quantities but also exactly where soil is lacking or in excess at a glance, allowing rapid identification of areas requiring correction. Thus, point cloud utilization both enhances the precision of earthwork management and makes results easier to understand.

Conventional Earthwork Measurement Methods and Their Limitations

Conventional differential earthwork calculations have primarily relied on a combination of surveying instruments such as total stations (TS) and levels with CAD software. A typical workflow is that a survey team first visits the site before construction to measure ground elevations at a regular grid interval or to capture cross-sectional shapes along representative longitudinal and transverse lines. After completion of the work, they perform similar surveys and prepare height data for both before and after. Back at the office, the survey point data are used to produce drawings and perform analysis. With the average cross-section method, volumes for each segment are calculated from the area difference between cross sections before and after and the distance between them, and then summed for the total earthwork. Alternatively, a digital terrain model (TIN) can be created from the survey points and the volume difference between two models can be automatically calculated within CAD.

These conventional methods require multiple field surveys and complex data processing to compute differential volumes. Naturally, they take days to complete, and it is not uncommon that by the time results are available, the site has moved on to the next stage. Because the process is laborious but lacks real-time capability, it is difficult to immediately apply survey results on site, creating a dilemma. The cross-section method also has inherent limitations: interpolation between measurement points can introduce errors depending on point placement. Overall, manual-based earthwork measurement is increasingly mismatched with modern demands for efficiency, accuracy, and speed.

How to Easily Acquire 3D Point Clouds on Site

While point clouds are clearly useful for earthwork management, the challenge has been how to easily acquire those point clouds on site. Traditionally, this required expensive dedicated equipment such as terrestrial 3D laser scanners or survey drones, and work by a surveying team. However, recent advances in photogrammetry have enabled site staff themselves to acquire point cloud data using smartphones or drones. Even without specialized equipment, familiar cameras can capture the site and generate 3D models from images, significantly lowering the barrier to point cloud measurement.

Photogrammetric point cloud acquisition is characterized by the ease of measuring wide areas with handheld devices. For example, flying a drone over a site can quickly collect photographic data of a large area, and remote imaging can reach steep or hazardous locations where people cannot safely enter. With a smartphone camera, taking sufficient photos from various angles around the target and processing them with dedicated analysis software can generate a high-density point cloud model. The ability to create three-dimensional point clouds using only commercially available cameras, without costly laser scanners, is revolutionary and is drawing attention as a tool for on-site DX.

Nonetheless, photogrammetry still has several challenges. The accuracy of point cloud generation from photos is highly dependent on shooting conditions such as image resolution, exposure, and the presence of texture on subjects. Errors tend to occur in dark areas or on strongly reflective surfaces, and preprocessing to extract only ground points can be time-consuming if vegetation or debris is present. Even after on-site shooting, image processing (point cloud generation) may require hours on a high-performance PC or cloud service, making it difficult to complete the workflow from capture to volume calculation entirely on site. Drone use also requires prior flight permissions and piloting skills. Furthermore, standalone smartphone photogrammetry can include positional errors in the captured images, causing the generated point cloud model to be displaced from the real-world coordinate system. Even if point clouds are created, they are useless for quantity calculations if their absolute elevation and position are unclear. For this reason, photogrammetry has traditionally required additional steps such as placing ground control points to align models to reference coordinates and correct accuracy.

Conversely, the LiDAR (light detection and ranging) functions now available on some smartphones have opened new possibilities by allowing point clouds to be captured simultaneously with imaging. Scanning a site with a LiDAR-equipped tablet or smartphone generates point cloud data in real time on site. However, these sensors alone do not provide sufficient georeferencing accuracy, so methods to add accurate positioning information to the acquired point cloud are still needed. Combining these latest technologies effectively is key to enabling anyone on site to complete high-accuracy point cloud measurements easily.

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

Integrating these latest technologies has given rise to “smartphone point cloud surveying” as a solution that enables “anyone to perform high-accuracy point cloud surveys immediately.” Particularly notable is a system that pairs a smartphone with a high-precision GNSS receiver (e.g., LRTK), allowing centimeter-class positioning and 3D scanning to be performed easily on site. With portable equipment such as a smartphone plus a small GNSS antenna, it becomes possible to acquire accurately georeferenced point cloud data that previously required specialized instruments.

In smartphone point cloud surveying, the acquired point cloud data can be uploaded directly to the cloud for automatic differential volume calculation. For example, LRTK cloud services can compute the difference between uploaded point clouds and pre-registered design surfaces or past terrain data with one click, instantly producing fill and excavation volumes. No complex software operation or manual calculation is required, and on-site personnel can grasp as-built quantities in a short time. This workflow eliminates the time lag that hampered photogrammetry—measurements taken on site immediately yield volumes on site.

The efficiency gains from point cloud utilization are striking. In one large-scale example, a task that formerly required four people working seven days was switched to drone photogrammetry plus point cloud analysis and completed by two people in one day. Work time was reduced to about 1/14, and the resulting as-built quantity error remained within about 1% compared to the conventional method, confirming dramatic improvements in both efficiency and accuracy. High-precision GNSS also eliminates the need to install survey control points, contributing not only to time savings but to overall labor reduction in the workflow. Instant volume calculation using a smartphone and GNSS is a technology that can truly elevate construction management productivity to the next level.

Immediate Sharing of Point Cloud Data via the Cloud

Using a cloud platform enables instant sharing of acquired point clouds and calculation results from the field. Survey data are automatically saved to the cloud, allowing supervisors or clients in the office to view the site’s 3D model in real time via a web browser. Stakeholders in remote locations can inspect the same data simultaneously, eliminating communication lag and reducing rework due to misunderstandings. For large projects, scanning the site weekly or monthly lets you quantitatively visualize earthwork progress and streamline progress reporting and interim inspections. For remote sites, cloud-based data sharing can serve as a virtual presence for inspections from the office, reducing travel time and labor costs.

Sharing point cloud data also means sharing the full “irrefutable evidence” that underlies quantity calculations. Not only can automatically computed volume numbers be presented, but the underlying terrain can be delivered as a 3D model, making explanations to clients highly persuasive. In practice, sharing point cloud data has in some cases eliminated the need for on-site attendance and physical measurement during as-built inspections, simplifying inspection procedures. The ability for all stakeholders to instantly share the same visual information is a revolutionary advantage that greatly streamlines on-site consensus building.

One-Click Automatic Generation of As-Built Reports

Using point clouds can also streamline the entire process from surveying to report creation. Traditionally, personnel had to manually create drawings and tables from survey data and assemble them into reports. However, cloud platforms can automatically generate standardized as-built reports from measurement results. For example, LRTK Cloud offers a function to output reports in prescribed formats (PDF) from acquired point cloud data, enabling generation of measurement reports that include photos, coordinate values, and notes with a single button click. This removes the need to format documents in Excel or CAD and greatly reduces the effort required to prepare report materials.

Reports can include not only automatically calculated fill and cut volumes but also longitudinal and cross-sectional drawings and 3D view images extracted from the point cloud. This allows numerical results on paper to be directly cross-referenced with actual site imagery, making the documents extremely useful for client explanations and as-built inspections. Because point cloud data themselves provide documentary evidence of site conditions, including them in reports has significant value. In one case, point clouds acquired with LRTK at the completion of embankment work were compared with the design surface, the automatically calculated volumes were transferred to an as-built quantity table, and cross-sectional drawings and 3D view images generated from the point cloud were attached to the report and submitted to the client, resulting in a quick and smooth as-built confirmation. Speeding up the measurement-to-report cycle with point clouds accelerates decision-making on site and powerfully supports the PDCA cycle in civil construction.

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

The combination of smartphone point cloud surveying and differential volume calculation has the potential to revolutionize earthwork management that has relied on manual processes. By leveraging GNSS-integrated systems such as LRTK, anyone can quickly obtain high-accuracy overviews of large areas, dramatically improving productivity, safety, and quality on site. In a construction industry where ICT and DX adoption is increasingly required, introducing familiar, easy-to-use smart tools is a practical first step toward smarter site management.

Introducing simple surveying with LRTK on site enables immediate measurement when needed and instant sharing and reporting of results. This saves substantial manpower and time while enabling rapid decision-making based on high-accuracy as-built data, contributing to overall project efficiency and quality assurance. Why not try this new earthwork management approach that breaks free from conventional practices at your site?

FAQ

Q: Can point clouds acquired with a smartphone meet the accuracy requirements for as-built management? A: For public works as-built management, a density of several dozen points per 1 m^2 (10.8 ft^2) on ground point clouds is generally recommended. Smartphone-integrated LiDAR does not achieve the same point density as professional laser scanners, but by scanning slowly and carefully it can capture a sufficient number of points. In addition, by performing point cloud acquisition while positioning with a high-precision GNSS, positional accuracy can be ensured, and with proper operation smartphone point clouds can achieve errors on the order of a few cm (a few in). Validation tests have shown that volumes calculated from point clouds acquired with a smartphone plus GNSS are comparable in accuracy to values from conventional surveys.

Q: Can measurements be taken in areas with poor satellite reception? A: High-precision GNSS performs best in open-sky conditions, but stable positioning is possible at sites with some obstructions by using multiple satellite constellations and augmentation signals. In environments where satellite signals are easily blocked—such as forests or dense urban areas—accuracy may temporarily degrade, but such locations can be covered by combining ground control points. LRTK supports multiple frequencies and augmentation information distributed from Japan’s Quasi-Zenith Satellite System (“Michibiki”) (CLAS), and it is designed to maintain centimeter-level (inch-level) positioning even in mountainous areas outside of internet coverage.

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 accuracy on slopes can be ensured by photographing from multiple directions as needed and by applying GNSS-based height corrections. Smartphone LiDAR emits from multiple angles during scanning, enabling 3D capture of undulating slopes. However, on steep slopes there may be occluded areas that cannot be seen from above, so combining drone aerial imaging to cover blind spots is effective. Overall, whether on flat or sloped terrain, sufficient as-built accuracy can be obtained if point clouds are acquired using appropriate methods.

Q: How can differences before and after construction be checked using point cloud data? A: By comparing two acquired point clouds (before and after construction, or as-built vs. design), you can visualize not only volume differences but also their spatial distribution. Specifically, displaying the height difference between the two as a color heat map makes it easy to see where and by how much soil has been added or removed. For example, areas higher than the design can be shown in red and lower areas in blue, instantly highlighting regions requiring correction. You can also slice arbitrary section lines on the point cloud to overlay pre- and post-construction cross-sectional shapes. These functions enable not only numeric outputs but also visual confirmation of differences for pass/fail judgments and site feedback.

Q: How can measurement data and volume calculation results be exported and shared? A: Acquired point cloud data and calculation results can be easily shared and exported via the cloud. LRTK Cloud can issue sharing links to a dedicated viewer that allows stakeholders to view and measure the data in 3D, and these links can be distributed for free inspection. Fill and excavation calculation results can be output as PDF reports and used directly as as-built submission documents. If needed, the point cloud itself can be downloaded in common formats (LAS or XYZ, etc.) for secondary use in CAD or other point cloud processing tools. These capabilities make data utilization and reporting smooth and efficient.