Innovative Volume Calculation with 3D Point Clouds! Achieving Safe, Rapid Earthwork Quantity Measurement

Table of Contents

• Principles of volume calculation using point cloud scanning and differences from traditional methods

• Improved work efficiency: earthwork measurement with fewer personnel and shorter time

• Increased accuracy and prevention of human error: reliability of point cloud data

• Case studies and concrete applications

• Simple surveying with a smartphone: promoting on-site DX with LRTK

• FAQ

In civil engineering sites, measuring earthwork quantities (volume calculation) associated with embankment and excavation is an essential task for schedule and progress control. Traditionally, this volume calculation was commonly performed by measuring cross sections on site with surveying instruments and manually calculating volumes using methods such as the average cross-section method. However, in recent years the spread of a new approach using 3D point cloud data has begun to greatly change the earthwork measurement process. In addition to drone aerial photogrammetry and terrestrial laser scanners, easy 3D point cloud surveying using smartphone LiDAR sensors has emerged, enabling embankment and excavation volumes to be calculated more quickly and accurately from high-density point cloud data.

This article explains the basic principles of volume calculation using point cloud scans and the differences from traditional methods, and details how utilizing 3D point clouds improves work efficiency and surveying accuracy. We also present concrete on-site use cases such as land development, excavation, slope management, and road construction, and cover point cloud data processing workflows and visualization methods (mesh modeling, difference heatmaps, cross-section comparisons, etc.). At the end of the article we introduce the latest easy surveying tool LRTK that anyone can use with a smartphone, and offer tips for on-site implementation. Now, let's explore the innovative world of earthwork measurement enabled by point cloud scanning.

Principles of volume calculation using point cloud scanning and differences from traditional methods

The principle of earthwork calculation using 3D point cloud data is simple. You compute the volume difference between a reference ground surface model and a comparison ground surface model. For example, in land development you overlay the pre-construction original ground model with the post-construction (after embankment completion) ground model and calculate the embankment volume from their difference. When two terrain datasets are overlaid in three-dimensional space, the gaps where they do not fully overlap indicate “missing soil,” while the parts that overlap and protrude indicate “excess soil.” By numerically integrating (volume computation by computer) the volumes of those voids and protrusions, the cut and fill volumes can be automatically calculated. Traditionally, surveyors created cross-section drawings from field surveys and used the average cross-section method to obtain volumes, but directly comparing point cloud datasets allows the entire ground surface to be targeted and thus enables high-accuracy volume calculations that reflect fine terrain variations easily missed by manual methods. Also, once point cloud data are acquired, it is easy to perform additional volume calculations later for arbitrary regions and to use the data for various quantity calculations as needed. Even when you want to know the volume of a single embankment pile or spoil heap, you can specify the embankment outline on the point cloud and use the surrounding existing ground as the reference plane, and the volume protruding from the reference will be automatically calculated. In short, digitizing the whole terrain with a 3D scan enables highly accurate volume calculations for both embankment and excavation.

Before the spread of point cloud scanning technology, the following traditional methods were used. Each method has advantages, but they also faced many challenges in terms of manpower and time.

• Staff-and-level cross-section surveying: The most basic method uses a level and a staff to measure ground elevations at regular intervals, create cross-section drawings, and calculate volumes using the average cross-section method. Although simple, in large sites the number of measurable points is limited, making it easy to miss local undulations, and the whole process—from surveying to drawing creation and volume calculation—required tremendous effort and time.

• Total station (TS) surveying: TS surveying using an electronic distance meter and prism is a standard method for obtaining high-precision 3D coordinates. Many survey points are observed to create an as-built terrain model from which volumes are calculated. However, TS surveying typically requires two or more personnel (an operator and a staff holder, and sometimes additional assistants), and covering a wide area requires repeatedly repositioning the tripod for multiple measurements. If observation point spacing is coarse, fine surface irregularities may not be captured and can cause errors in volume calculation, so increasing accuracy required additional manpower to increase the number of survey points.

• UAV (drone) photogrammetry: This method acquires multiple aerial photos with a drone and generates 3D models or point clouds via software from those images. Its advantage is the ability to survey wide areas quickly from altitude, and improvements in photogrammetry have increased accuracy. However, drone operation requires technical expertise and flight permission, and cannot be used in no-fly zones such as urban areas or around airports. High-accuracy surveys also require ground control points (GCPs) and position correction via RTK-GNSS, and image processing to generate point clouds demands time and advanced software. Weather sensitivity is another constraint, so despite being convenient it is not a universally usable method.

• Terrestrial laser scanner (TLS) surveying: High-performance laser scanners mounted on tripods are set up on site to directly scan the ground surface, acquiring high-density point clouds of millions of points. TLS can measure down to millimeter detail, yielding very high accuracy for volume calculations. On the other hand, the equipment is large and expensive and requires expert handling. Scanning wide areas with poor visibility requires relocating setups and performing multiple scans, then aligning and integrating the datasets afterward, which is time-consuming. The operational and data-processing burdens make frequent surveying difficult.

As shown above, each traditional method for earthwork measurement has strengths, but they commonly impose significant burdens in terms of manpower and time. Not only does the surveying itself require time and effort, but organizing acquired data, calculating volumes, and compiling drawings and reports also required extensive manual work. Moreover, because multiple specialized instruments and high-level skills were needed, sites suffering from chronic personnel shortages often could not perform surveys at adequate frequency. In addition, advanced equipment like drones and TLS are constrained by weather and safety management, so they cannot be used “anytime, anywhere.” Against this backdrop, demand has grown for quicker and easier earthwork measurement. The introduction of 3D point cloud scanning technology is the new solution that meets this need.

Improved work efficiency: earthwork measurement with fewer personnel and shorter time

Introducing point cloud scanning technology dramatically improves the efficiency of earthwork measurement. Processes that used to take days to weeks from surveying to calculation have been significantly shortened in some cases. The main efficiency points are summarized below.

• Significant reduction in work time: The time required for field surveying and volume calculation is dramatically reduced. For example, at a large-scale land development site, a task that previously took a survey team of four one week (a total of 28 person-days) to measure and calculate as-built earthwork quantities was completed with point cloud scanning by two people in one day (a total of 2 person-days). That corresponds to roughly 1/14 in personnel-days and about 7% of the calendar days. The efficiency comes from point cloud scanning’s ability to measure the entire site surface at once, and the traditional staged process of “survey → drawing creation → manual calculation” can be largely skipped because results are available on a computer immediately after data acquisition. This leads directly to shorter construction schedules and reduced labor costs, improving overall site productivity.

• Reduction in required personnel: Point cloud scanning allows surveying work to be completed with fewer personnel. Traditional TS surveying required teams of 2–3 people, and drone photogrammetry usually needed 1–2 people for piloting and monitoring. By contrast, handheld laser scanners or smartphone-based point cloud measurement can generally be performed by a single person. A single operator carrying the device can walk through the site and acquire data without interrupting other workers. In situations of severe labor shortage, the ability for one person to manage as-built control with one device is impactful and can greatly reduce the cost of allocating multiple staff for surveying.

• Immediate processing and rapid decision-making: Data acquired as point clouds can be processed for volume calculation and analysis immediately in dedicated software or cloud services. Previously, field data had to be taken back to the office and entered into software for volume calculation and report generation, which could take a day or more. With point cloud scanning, these processes are automated and streamlined, allowing results to be known the same day. This enables on-site numeric confirmation of “how many cubic meters of fill are still needed” or “how much has been excavated,” allowing decisions about the next steps to be made on-site. Dump truck counts and heavy equipment operation plans can be optimized in real time, enabling quick responses to changing conditions and plan adjustments. Eliminating the need to wait for final reports speeds up the entire construction management cycle.

• Improved safety and flexible measurement: Site environment and safety affect surveying efficiency. Traditionally, measuring steep slopes often required workers to climb dangerous slopes to place staffs or measure distances. Point cloud scanning can measure an entire slope remotely from a safe location at the slope base. It also enables scanning around areas with poor footing or active heavy machinery without interrupting operations, achieving both safety and efficiency. Additionally, point cloud scanning is effective in urban or indoor spaces where drones cannot fly, and laser scanners are mostly unaffected by light rain, providing the flexibility to “measure when you need to.” Thus, point cloud scanning not only reduces the time and personnel required for surveys but also enables real-time feedback and safety improvements, greatly enhancing overall operational efficiency.

Increased accuracy and prevention of human error: reliability of point cloud data

Introducing point cloud scanning also contributes greatly to improved surveying accuracy. High-density point cloud data composed of many points can measure the ground surface almost continuously, accurately capturing minute irregularities and localized depressions that manual surveying might miss. As a result, volume calculations reflect details that human surveying could overlook, yielding reliable numbers that do not rely on estimation. In comparative validations between traditional methods and point cloud-derived volumes, reports show that volumes calculated from point clouds fell within about 1–2% of values obtained using the conventional cross-section method. When point cloud data are acquired following appropriate procedures, it is becoming clear that volumes can be computed with accuracy comparable to traditional approaches.

Moreover, point cloud scanning is effective at reducing human error. Traditional methods involve reading survey point values and performing manual or spreadsheet calculations, where misreads, recording errors, and calculation mistakes can occur. In point cloud surveying, the process from measurement to calculation is digitally integrated, reducing the opportunity for subjective or manual errors. Differences in operator skill and judgment are also reduced, making it easier to ensure consistent quality regardless of who performs the measurements. Sharing automatically computed volume values immediately after on-site scanning prevents communication errors among multiple personnel. In this way, digitalization and automation of surveying help prevent human errors and enhance the reproducibility and objectivity of results.

The reliability of the acquired point cloud data itself is also extremely high, making it useful as a digital record of the site. Once a 3D point cloud is stored in the cloud, it can be reused for subsequent analyses. For example, if later you need a cross-section of a specific area or want to re-check the volume of embankment removed at that time, you can perform the analysis from the previously acquired point cloud without additional surveying. Because the site situation can be archived with a precision impossible with paper drawings or photographs, point clouds help prevent re-surveying due to missed measurements or decision errors caused by insufficient records.

Note that point cloud-based quantity calculation methods are gradually gaining official acceptance. Guidelines such as the Ministry of Land, Infrastructure, Transport and Tourism’s “Guidelines for Quantity Calculation of Civil Engineering Works (draft)” have begun to include methods for earthwork calculation using point cloud data obtained from drone surveys and 3D laser scans. If conditions are met, point cloud surveying results can be treated as equivalent to traditional surveys, and institutional frameworks are evolving so that in the future quantities derived from point clouds will increasingly be used formally for progress reporting and inspections. From a regulatory perspective, point cloud scanning is being positioned as a new standard with reliability being secured.

In addition, point cloud scanning enables various 3D analyses and visualizations beyond numeric results. Some of the analysis methods unique to digital data are described below.

• Surface model generation through meshing: Point clouds are collections of discrete points, but for analysis they are automatically converted into triangular meshes or voxels (3D grids) to form surface models and compute volumes. In all methods, generating a smooth surface model of the ground from the point cloud is important. During mesh generation, appropriate interpolation is applied according to point density to obtain precise terrain representation. However, if points are extremely sparse the mesh shape may be inaccurate, so ensuring sufficient point density during measurement is key to maintaining accuracy.

• Calculating volume differences and visualizing differences: Once you have two terrain datasets (either point clouds or generated surface models) to use as the reference and comparison, embankment and excavation volumes can be automatically computed from height differences. By selecting comparison targets in software, the system can instantly display results such as “embankment: ○○ cubic meters” and “excavation: ○○ cubic meters” within a specified area. Some software can output a color-coded difference heatmap. For instance, when overlaying the design model (planned ground) and the as-built point cloud, areas that have reached design elevation can be shown in blue, while areas that are lower than design (embankment shortfall) can be shown in red, color-coding the surface. This makes it intuitive to see “where soil is lacking and where too much has been removed,” and using these visualizations together with numeric volume results facilitates information sharing among site stakeholders and streamlines as-built inspections.

• Creating and comparing cross-sections: It is also easy to extract longitudinal and transverse cross-sections from point cloud data at arbitrary locations. Traditionally, shape could be understood only along pre-set section lines during surveying, but once a point cloud is acquired you can create as many cross-sections as needed afterward. For example, you can overlay a roadway design cross-section and the measured post-construction cross-section to compare, or evaluate deviations between a slope’s designed gradient line and the actual section, all with a single click. Cross-sections are useful for confirming subtle shape differences that may not be apparent from numeric volume differences alone, and they provide material for judging as-built quality. Thus, data acquired from point cloud scanning offers great flexibility for multifaceted post-survey analysis.

Case studies and concrete applications

Volume calculation using 3D point cloud scans is being practically adopted across various civil and construction site tasks. Representative application scenes are introduced below.

• As-built management of embankment and excavation: In road construction and land development, accurately grasping terrain changes due to embankment and excavation is important. By acquiring point cloud data of the ground surface before construction and after completion—or by section—and calculating the differential volume between the design surface and the original terrain, objective data can be provided for as-built quantities. On actual development sites, this is used to compare planned earthwork volumes with as-built results early on and to detect shortages or surpluses of embankment materials.

• Application to slope management: Point cloud scanning is also powerful for maintaining steep slopes and embankments. For example, after heavy rains at a slope failure site, rapidly calculating the volume of collapsed soil allows immediate judgment on the amount of material to be removed and restored. During slope finishing in construction, point cloud cross-section comparisons can check how much the current slope deviates from the design gradient and shape. Because dangerous slopes can be measured remotely without personnel entry, it is possible to safely and frequently monitor slope shape changes and earthwork quantities.

• Managing spoil and material stockpile volumes: Point clouds are useful for managing volumes of spoil heaps and material stockpiles such as crushed stone and gravel. Where volumes were formerly roughly estimated from pile appearance, drone overflights or ground-based handheld scanners and smartphones can generate point clouds to compute accurate volumes. This enables inventory management and transport planning based on data. In practice, a site supervisor once quickly scanned a small spoil pile with a smartphone, determined its volume on the spot, and decided the necessary number of dump trucks.

• Verifying excavation and backfill volumes: Point cloud-based volume verification is effective in works involving excavation and backfilling, such as sewer installation and building foundation works. By acquiring terrain point clouds before excavation and after backfilling and computing their difference, you can calculate excavated and backfill volumes to verify whether the required volume has been backfilled correctly or whether unintended over-excavation occurred. The volume of rock fragments produced during excavation is difficult to predict on site, but point cloud measurement can instantly compute rock volumes to assist transport planning. (Note: For complex-shaped rocks, point clouds may not capture backside voids, so scanning from multiple angles to secure accuracy is recommended.)

• Progress management during construction (time-series as-built records): For large earthworks, periodic acquisition of as-built point cloud data on a weekly or monthly basis and recording construction progress in 3D is becoming common. Comparing time-series point clouds allows visualization of “how much and when the earthwork volume increased or decreased.” This enables early correction of deviations from plan and serves as evidence for as-built progress reports. Because point cloud data can be shared via the cloud among stakeholders, the same 3D model can be viewed during site meetings with clients or supervisors, facilitating remote understanding of site conditions and issuing instructions from afar.

Simple surveying with a smartphone: promoting on-site DX with LRTK

You may understand the usefulness of point cloud scanning but wonder, “Do I need expensive laser scanners or drones to introduce this?” To address that concern, we introduce a recent easy 3D surveying tool using a smartphone. A representative example is the smartphone surveying system called LRTK.

LRTK is a solution composed of an ultra-compact RTK-GNSS receiver (weighing only about 125 g) that attaches to a smartphone and a dedicated app. RTK (real-time kinematic) is a technique that corrects satellite positioning (GPS/GNSS) errors in real time to improve position accuracy to the centimeter level. When an LRTK device is attached to a smartphone, the smartphone’s GPS positioning, which normally has errors on the order of meters, becomes survey-grade high precision. Combining this high-precision positioning with the smartphone’s built-in LiDAR sensor or camera allows anyone to easily acquire high-accuracy 3D point clouds. The simplicity—only the smartphone and a pocket-sized antenna are required—means the device can always be carried on site, enabling a “measure when you need to” environment.

When measurements are performed with the dedicated LRTK app, the acquired point cloud data and survey point coordinates are synchronized in real time to the cloud service “LRTK Cloud.” On LRTK Cloud you can view point cloud data in 3D via a browser and intuitively measure distances, areas, and volumes. For example, if you scan an embankment with your smartphone and upload it to the cloud, the volume is automatically calculated and displayed on the spot, eliminating the need to bring data back to a PC for analysis. Because the cloud 3D data can be immediately shared with stakeholders, site-acquired point cloud models can be viewed in real time by office supervisors or clients.

The advantages of smartphone surveying with LRTK are ease of use for anyone and overwhelmingly lower cost compared to traditional equipment. The app is designed to be intuitive so that field personnel without specialized training can operate it, creating an environment where “you can measure yourself whenever you need to.” Tasks that once required purchasing expensive laser scanners or outsourcing to surveying companies can often be handled with an LRTK-equipped smartphone. LRTK aligns with the Ministry of Land, Infrastructure, Transport and Tourism’s i-Construction initiative and is a modern on-site DX (digital transformation) tool.

Thus, while point cloud surveying technology is advancing in sophistication, it is evolving into forms that are easy to use on site. If you feel “I’d like to introduce this on my site” or “I want to try it first,” starting with smartphone-based LRTK surveying is one option. More detailed product information and consultation about implementation are available at the [LRTK Official Site](https://www.lrtk.lefixea.com/). Please check it out. By appropriately adopting cutting-edge technology, you can improve site productivity and strengthen safety management.

FAQ

Q. What is point cloud data? How is it obtained? A. Point cloud data are a collection of many points (coordinate data) that constitute the surface of an object or terrain. By plotting countless points in 3D space, they represent the shape of terrain or structures. Representative acquisition methods are laser surveying (LiDAR) and photogrammetry. In laser surveying, special laser scanners or smartphone-built-in LiDAR sensors emit laser light and measure the distance to the target from returning signals to obtain point coordinates. In photogrammetry, drones or cameras take many photos from various angles, and image analysis finds corresponding feature points to reconstruct 3D shape. Recently, smartphone LiDAR and high-performance cameras have made point cloud acquisition easier, lowering the threshold for measurement.

Q. How reliable is the accuracy of volume calculations using point clouds? A. With properly acquired point cloud data, volume calculation accuracy can be expected to be comparable to traditional surveying methods. Validation examples report point cloud-derived volumes within about 1–2% of volumes obtained by conventional cross-section methods. The key is acquiring point clouds at sufficient density and reducing error factors. For example, in drone photogrammetry take high-resolution photos with sufficient overlap, and in laser scanning avoid occlusions by scanning from multiple directions to improve accuracy. Software that computes volumes from point clouds also performs automatic mesh interpolation and filtering to generate a model closer to the actual shape before volume calculation, producing more reliable results than rough manual estimates.

Q. Can earthwork measurement using point clouds be done without drones or expensive equipment? A. Yes. Until a few years ago, obtaining high-precision point clouds required specialized laser scanners or a full drone setup. Today, however, solutions have emerged that allow easy acquisition of high-precision point clouds by combining a smartphone with small devices. One such solution is LRTK introduced above. By combining RTK-GNSS high-precision positioning with point clouds acquired by a smartphone’s LiDAR or camera, earthwork measurement on site is possible without drones or dedicated equipment. For large sites or wide-area surveys, drones may still be more efficient, but for small-scale measurements and daily as-built control, smartphone point clouds are often sufficient. By choosing among drones, lasers, and smartphones according to requirements, you can utilize point cloud measurement while keeping costs down.

Q. Are volumes measured by point clouds accepted as official as-built quantities? A. The trend is moving in that direction. The Ministry of Land, Infrastructure, Transport and Tourism’s guidelines (such as the “Guidelines for Quantity Calculation of Civil Engineering Works (draft)”) have begun to specify earthwork calculation methods using point cloud data. When requirements (measurement accuracy and management methods) are met, point cloud surveying results can be treated as equivalent to traditional human-conducted surveys, and more clients are accepting as-built reports based on drone or laser scan data. However, full standardization and universal adoption may still take time, so for now you need to follow the client’s policies and site-specific arrangements. Nevertheless, point cloud scanning is expected to accelerate its positioning as a new standard.

Q. Is it difficult to master 3D point clouds? Can beginners handle it? A. While it may once have seemed to require specialist knowledge, tools have become more beginner-friendly. Smartphone surveying tools like LRTK are designed so site personnel can intuitively capture point clouds with smartphone operations and perform volume calculation and sharing via the cloud. By following on-screen prompts to move the smartphone, a 3D scan is completed and complex calculations are handled automatically in the cloud, leaving the user simply to review results. Interfaces are designed for users without training, and products with support systems are available if you need help. Starting with small embankment measurements will likely feel surprisingly easy. Once mastered, many site personnel find point cloud data indispensable.