Table of contents

• Basic knowledge of 3D surveying and point cloud data

• What is a point cloud viewer? Its roles and functions

• Methods for volume calculation using point cloud data

• Advantages of calculating volumes with a point cloud viewer (comparison with traditional methods)

• Specific use cases on construction sites

• Start 3D surveying with your smartphone: easy point cloud measurement for anyone with LRTK

• FAQ

In construction and civil engineering sites, volume calculation (earthwork quantity calculation) for fill and excavation is an essential task for progress and quantity management. Traditionally, surveys measured terrain and produced cross-sections to calculate volumes using the average-end-area method. However, in recent years, 3D surveying using drones, laser scanners, and even smartphones has been spreading. From the point cloud data obtained by these technologies, dedicated point cloud viewers now allow quick and accurate volume calculations. This article explains the basics of what point cloud data are, how to use point cloud viewers, and practical tips for 3D surveying that are useful on construction sites. Finally, we introduce an easy smartphone surveying solution called “LRTK” for simple measurements.

Basic knowledge of 3D surveying and point cloud data

First, let’s cover the basics of 3D surveying and point cloud data. 3D surveying is a general term for methods that measure site terrain and structures in three dimensions and convert them into digital data. Representative methods are laser scanning (LiDAR) and photogrammetry. A laser scanner emits laser beams from a tripod or vehicle-mounted device and obtains coordinates of numerous points by measuring the time until the reflection returns. A single scan can yield a high-density point cloud of several million points, enabling terrain and structures to be recorded in millimeter-level detail. On the other hand, photogrammetry captures multiple photographs from drones or cameras and uses software to analyze images to generate 3D models or point clouds. It can capture large areas of ground quickly, and recent advances in software have made it easy to generate high-accuracy point cloud data.

The resulting point cloud data are collections of many measured points in space, where each point has X, Y, Z coordinate (position) information as three-dimensional data. Points can also have attributes such as color or return intensity. Simply put, a point cloud is a 3D model made up of countless points. While traditional surveys recorded only dozens to hundreds of points, point cloud surveying can acquire millions of points. Because the site shape can be measured at high density without omission, fine terrain undulations and subtle surface details of structures can be reproduced accurately. For this reason, use of point clouds is encouraged within digital initiatives such as the Ministry of Land, Infrastructure, Transport and Tourism’s i-Construction, and the construction industry is rapidly adopting 3D surveying.

What is a point cloud viewer? Its roles and functions

A point cloud viewer, as the name implies, is software or a cloud service for displaying and manipulating point cloud data. Obtained point cloud data consist of a vast number of points and, unlike ordinary 2D drawings or photographs, can only be utilized effectively with a dedicated viewer. A point cloud viewer visualizes point clouds in 3D space on a PC or tablet and allows free movement of the viewpoint to observe from any direction. Because you can survey the entire site as if you were there, it becomes intuitive to grasp vertical information and complex terrain shapes that were difficult to capture on paper drawings.

Basic functions of a point cloud viewer include not only displaying and browsing point clouds but also measurement and analysis tools. For example, you can measure the distance between any two points, calculate the area of a selected region, check height differences, and extract cross-sections. Moreover, more viewers now include volume calculation (earthwork quantity) functions. Volume calculation features automatically compute the volume of soil or fill within a specified area from point cloud data. Traditionally, point clouds had to be converted into a mesh or surface model to calculate volume, but recent software and cloud services allow you to upload point cloud data and simply specify the area to calculate volume. In other words, even without complex 3D CAD operations, point cloud viewers are moving toward an era where earthwork volumes can be obtained almost automatically with one click.

There are not only PC software versions of point cloud viewers but also cloud-based services that run in a web browser. Cloud-based viewers have the advantage of handling large point cloud datasets without installing dedicated software and can run on relatively low-spec PCs. If you upload point clouds acquired on site to the cloud, anyone in the office can share and view the 3D data on the web, facilitating information sharing. Thus, point cloud viewers play an important role that goes beyond mere display tools, supporting measurement, analysis, and data sharing.

Methods for volume calculation using point cloud data

Now, let’s look at the basic methods for calculating volumes (earthwork quantities) from point cloud data. Typical cases where you want to calculate volume are: 1) calculating fill/excavation volumes from the difference between pre- and post-construction terrain, and 2) calculating the volume of a single pile of fill or material.

① Volume calculation by differencing point clouds before and after construction: To accurately determine fill and excavation volumes in earthwork, it is effective to measure terrain with point clouds before and after construction and compute volumes from the difference. Specifically, acquire point cloud data of the original ground before starting work and of the terrain after construction (after fill completion or after excavation), and overlay the two datasets. By calculating the height difference between these two point clouds in a point cloud viewer or analysis software, the volumes of cut and fill areas are automatically computed. Because both datasets fully measure the entire ground surface, high-precision volume calculations that reflect subtle undulations are possible. Once point clouds are obtained, it is also easy to delimit arbitrary areas later for additional volume calculations, enabling flexible quantity extraction as needed. For example, if heavy rain alters the terrain mid-project, you can extract and recalculate only the affected area from the existing data without re-measuring the entire site.

② Volume calculation of a single fill relative to a reference plane: To determine the volume of a pile of surplus soil or stacked materials on site, treat the surrounding ground as a reference plane. First, prepare point cloud data that scans the entire area of the pile. The viewer’s volume measurement function lets you specify the polygonal area corresponding to the pile’s outline on the point cloud and set a reference plane—typically a horizontal virtual plane such as the average height of the surrounding ground. The software then automatically calculates the volume protruding above the reference plane within the specified area. In essence, it computes the volume by numerically integrating a prism that encloses the pile from the base. In many programs, once you select the area and set the reference plane height, the volume value is displayed with one click. For excavation, similarly specify the excavated region to calculate the volume missing below the reference plane (the removed earth).

As described above, point cloud data greatly automate and simplify earthwork quantity calculations. However, to obtain high-accuracy results, unifying surveying references is important. When comparing point clouds before and after construction, measurements must be taken in the same coordinate system and with the same reference points. For drone surveys, apply ground control points; for laser scans, perform instrument positioning corrections so that the point clouds align without discrepancy. Also, pre-delete unnecessary points outside the target area to reduce error sources and improve accuracy. On the point cloud viewer, remove noisy points such as vehicles and people that are not ground, or use clipping functions to hide unrelated areas, so calculations use clean data.

Advantages of calculating volumes with a point cloud viewer (comparison with traditional methods)

Using point cloud data for volume calculation offers many advantages over traditional manual methods. Here we summarize the benefits focusing on efficiency and accuracy.

• Dramatic improvement in work efficiency: The biggest advantage is the significant reduction in effort and time required for earthwork quantity calculations. For example, at a large-scale development site where previously a surveying team of four took one week (28 man-days) to measure and calculate as-built quantities, switching to drone aerial imaging to create point clouds and using a point cloud viewer to compute volumes reduced the task to two people in one day (2 man-days). That’s about 1/14 of the personnel-days and roughly 7% of the original work period. This dramatic efficiency gain stems from the characteristic of point clouds that measure the entire site continuously. Traditional workflows of surveying → drawing → manual calculation are replaced by point cloud data that delivers results on a computer immediately after measurement, eliminating intermediate steps. The result directly shortens schedules and reduces labor costs, improving overall site productivity.

• Comprehensive data and improved accuracy: Another benefit of point clouds is that the obtained data are extremely detailed and comprehensive. Manual surveying could only estimate shapes from cross-section lines spaced tens of meters apart or a limited number of measurement points, but point clouds are measured data consisting of millions of points covering the site thoroughly. This allows volume calculations to reflect tiny undulations and local depressions or rises that manual surveys might overlook. Comparative validations have shown that volumes calculated from point clouds often differ from traditional methods by only about 1–2%. In terms of safety, non-contact measurement using point clouds avoids sending workers into hazardous steep slopes or unstable areas. Furthermore, point cloud data have high reusability; once 3D data are acquired, you can later perform other analyses (cross-sections, settlement measurement, defect checks, etc.) using the same dataset. Keeping a digital record of the site at a level impossible with paper drawings or photos is a major advantage.

• Immediate results and faster decision-making: With a point cloud viewer, you can calculate volumes from data measured on site within the same day. This enables early grasp of as-built quantities and speeds up on-site decision-making. For example, if a person in charge measures daily excavation progress with point clouds and immediately calculates the remaining soil, they can promptly optimize the number of dump trucks and heavy equipment operations. Steps that formerly required waiting for specialized surveying staff reports or office-based calculations can now be completed on site in real time. This immediacy not only speeds up calculations but also enables quick responses to changing conditions and plan adjustments, making overall construction management more agile.

• Official recognition and reliability: Guidelines such as the Ministry of Land, Infrastructure, Transport and Tourism’s “Guidelines for Civil Engineering Work Quantity Calculation (draft)” are beginning to include methods for earthwork quantity calculation using point cloud data obtained from drone photogrammetry or 3D laser scanning. In other words, administrative bodies are starting to accept quantity calculation from 3D surveying, and the use of point cloud-derived figures in progress reports and inspections is likely to increase. Point cloud measurements require appropriate accuracy control and validation, but if conditions are met they can be treated as data with reliability equivalent to traditional surveying. Thus, point cloud-based volume calculation is gradually becoming a new standard not only in practical terms but also institutionally.

Specific use cases on construction sites

Point cloud data and volume calculation techniques are used in various scenarios on actual construction sites. Here are some concrete examples.

• Progress quantity management for fill and cut: In road construction and land development, it is important to accurately grasp the volume change due to fill and cut. Acquire point clouds of the ground surface before and after work or for each construction segment, and calculate earthwork quantities from the difference between the as-built and original terrain to present objective quantities. For example, you can compare planned earthwork volumes with actual executed volumes to detect shortages or excesses early.

• Stockpile and material inventory management: Point clouds are useful for measuring the volumes of stockpiles such as surplus soil or aggregates like crushed stone and gravel. Quantities that were once estimated visually or by cross-section methods can now be accurately determined by drone aerial imaging or by creating point clouds from ground-based handheld scanners or smartphones. This enables scientific backing for inventory management and transport planning. In one reported case, a site supervisor quickly scanned a small pile of surplus soil with a smartphone and immediately determined the volume to decide the required number of dump trucks.

• Verification of excavation and backfill quantities: For foundation or pipeline works that require excavation and backfill, comparing pre- and post-excavation point clouds allows verification of excavated and backfilled volumes. Quantities of rock produced by excavation, which are often hard to predict on site, can be calculated with point cloud measurements to assist transport planning. However, for complex rock shapes, unscanned voids behind visible surfaces can introduce errors, so scanning from multiple angles is advisable.

• Progress management during construction: For large earthworks, acquiring time-series point clouds weekly or monthly to record progress in 3D is increasingly common. Comparing time-series point clouds lets you visualize how much earthwork has changed at each point in time. This helps correct deviations from the plan early and can be used for as-built reporting. If point cloud data are shared in the cloud, remote headquarters or clients can view the current status in real time, improving information flow.

As shown above, the combination of a point cloud viewer and volume calculation has the potential to streamline overall site management beyond mere quantity computation. It is no longer an exotic advanced technology but is becoming an everyday tool that site supervisors and construction managers can handle themselves. The era in which “measuring earthworks with point clouds is the norm” is almost here.

Start 3D surveying with your smartphone: easy point cloud measurement for anyone with LRTK

If you think, “I understand point clouds are useful, but don’t I need expensive laser scanners or drones?”, rest assured. Recently, solutions that acquire point clouds using smartphones and simple devices have appeared, enabling beginners to start 3D surveying at low cost. A representative example is a smartphone surveying system called LRTK.

LRTK is a solution composed of an ultra-compact RTK-GNSS receiver that attaches to smartphones (iPhone or iPad, etc.) and a dedicated app. RTK-GNSS is a technology that corrects satellite positioning errors in real time to achieve centimeter-level high-precision positioning; by mounting an LRTK device on a smartphone, an ordinary smartphone quickly becomes a high-precision surveying instrument. Combining this with the smartphone’s built-in LiDAR sensor or camera enables anyone to acquire position-accurate 3D point clouds easily. The pocket-sized device weighing a few hundred grams can be carried on site at all times, allowing quick measurements whenever needed.

When you measure with the dedicated LRTK app, the obtained point cloud data and coordinate data of measured points are immediately synchronized to the LRTK Cloud. LRTK Cloud is a web-browser-based point cloud viewer, allowing 3D display of on-site point cloud data without installing software. The cloud also supports distance and area measurements and volume calculations from point clouds, so you can check quantities on the go or in the office. For example, uploading a point cloud of a pile scanned with a smartphone will automatically calculate and display the volume on the spot, eliminating the need to import data into a PC for analysis.

Advantages of smartphone surveying with LRTK include that it is easy for one person to operate and is vastly more affordable than traditional equipment. The design is intuitive enough that construction managers without specialized training can use it, creating an environment where “you can measure yourself whenever you want.” Tasks that previously required purchasing an expensive 3D laser scanner or outsourcing to a surveying company can often be handled with a single smartphone and LRTK. It also aligns with the Ministry of Land, Infrastructure, Transport and Tourism’s i-Construction initiative as a modern on-site DX tool.

Thus, point cloud technology is evolving to be both advanced and accessible. If you feel like trying 3D surveying at your site, starting with smartphone and LRTK-based simple surveying is one option. Detailed product information and implementation consultations are available on the LRTK official website, so check it out if interested. Incorporate state-of-the-art tools wisely to improve productivity on your site.

FAQ

Q1. Can I calculate volumes from point clouds without drones or expensive 3D scanners? A. Yes. While high-end laser scanners and drones are convenient for large-scale surveys, there are ways to utilize point cloud technology without them. For small areas, modern LiDAR-equipped smartphones and tablets such as the iPhone or iPad can acquire point clouds. If high-precision positioning is required, combining a smartphone with a GNSS device like LRTK allows centimeter-level point cloud surveying using inexpensive equipment. Photogrammetry from ground-based photographs without a drone is also an option. In short, by selecting the appropriate method for the site scale and purpose, you can obtain practical point cloud data and perform volume calculations without costly equipment.

Q2. Is operating a point cloud viewer difficult? Can beginners handle it? A. Point cloud viewers have become quite user-friendly in recent years, and basic viewing and measurement functions are not overly difficult for beginners. Interfaces differ between viewers, but many follow an intuitive flow where you move the viewpoint with a mouse and select functions such as “distance measurement” or “volume measurement” from menus. Cloud-based viewers are often designed to be usable without complex settings. Advanced analyses require some experience, but basic volume calculations can generally be understood after a few uses. Many software and services provide tutorials and support resources, so you can learn while referring to them. Start with small sample datasets and then move on to real site data as you become comfortable.

Q3. Can the precision of volumes calculated from point clouds be trusted? How do errors compare to traditional surveying? A. Volumes calculated from properly acquired point cloud data have been shown to be highly accurate, comparable to traditional surveying. For example, earthwork quantities derived from drone photogrammetry or terrestrial laser scanning often differ from traditional cross-section method results by about 1–2% in many cases. This means you can obtain figures nearly identical to carefully conducted traditional surveys. Achieving this accuracy requires proper reference point calibration during surveying and accurate registration (alignment) of point clouds. Noise or missing data in point clouds can introduce errors, so removing irrelevant points and performing appropriate post-processing are important. When conditions are met, point cloud surveying delivers accuracy on par with traditional methods, and public authorities are increasingly recognizing its effectiveness. Because point clouds can measure wide areas in detail, there tend to be fewer overlooked local errors, yielding highly reliable quantity calculations.

Q4. Does producing volumes from 3D point clouds take a lot of time? Don’t data processing and calculations require huge amounts of time? A. The time from creating point clouds to calculating volumes can be dramatically shorter than traditional methods, depending on the approach. In the past, post-processing after laser scanning sometimes took hours in specialized software. However, today automated systems that generate point clouds from drone imagery and apps that provide immediate results after smartphone scanning are available. For example, with drones you can capture a large area in about 15 minutes, upload photos to a cloud service, and receive point cloud models and orthophotos within a few hours. Smartphone scans may take tens of seconds to a few minutes of walking around, and some apps display volume calculation results instantly. Point cloud viewers’ processing is also optimized, and typical earthwork calculations return results almost in real time. Overall, total work time is usually much shorter than manual calculation. If datasets are large, cloud services can handle processing on servers without burdening your PC.

Q5. Are earthwork quantities measured and calculated from point clouds accepted as official as-built quantities? A. Although nationwide unified procedures are not yet fully established, point cloud surveying for as-built quantity management is being actively adopted in public projects. Government and municipal contracts have begun incorporating 3D as-built management guidelines as part of i-Construction, and cases using point cloud-derived quantities for inspections and quantity confirmation are increasing. However, to be officially accepted, procedures proving the reliability of the survey are required. For example, in photogrammetry you may need to set multiple known-elevation control points onsite for accuracy verification, and for laser scanning you should perform instrument calibration and error checks against existing terrain. You will likely need to provide documentation showing point cloud accuracy and calculation methods to the client or inspector. Given that technical standards are being established, point cloud measurement results that meet conditions are increasingly accepted as official records and quantity determination methods. There are already sites where quantities measured by point clouds were accepted in inspections. It is advisable to use point cloud methods alongside traditional approaches and proactively leverage the benefits of the new technology.