Table of Contents

• What is a point cloud? Basic principles of differential earthwork calculation and measurement flow

• Challenges and burdens of conventional point-cloud acquisition methods (laser scanners, UAVs)

• Mechanism and features of point-cloud scanning with a smartphone + RTK

• Workflow for comparing current state, as-built, and design models using a smartphone

• Automatic differential earthwork calculation in the cloud and the value of immediacy

• Time savings, labor reduction, and safety improvements achievable on site

• LRTK features: high-precision RTK positioning, AR utilization, cloud sharing, point-cloud support

• FAQ (frequently asked questions)

What is a point cloud? Basic principles of differential earthwork calculation and measurement flow

Point cloud data is three-dimensional data composed of a large number of points in space (XYZ coordinates) along with associated attribute information (color, reflectance intensity, etc.). It represents real terrain and structures as a collection of countless points and can record shapes down to millimeter-level detail. Point clouds are typically acquired by terrestrial 3D laser scanners or photogrammetry, and their use is advancing in civil engineering and construction sites as a means to capture detailed terrain shapes.

Differential earthwork calculation refers to comparing surface data from different times—such as before and after construction or before and after filling/excavation—to compute changes in volume (fill volume, excavation volume). The basic principle is simple: compute volumes from the terrain models before and after construction and take the difference to determine the actual moved earth. Traditionally, volume calculation was commonly done on-site using cross-section drawings measured in the field and methods like the average end-area method, but this required measuring heights at regular intervals and calculating for each cross section by hand, demanding considerable labor and time. By contrast, using point-cloud data involves scanning the surface in detail before and after construction to obtain 3D point clouds, and then automatically calculating earthwork volumes from their differences. Because point clouds measure the surface down to every nook and cranny, including subtle undulations, they can model terrain precisely and enable high-accuracy volume calculations. Once a mesh model is generated from the acquired point cloud, it is also easy to recalculate volumes for different areas without additional field surveys. This greatly reduces the on-site measurement work and the effort required for volume calculation, and allows for rapid determination of as-built quantities, which is a major advantage.

The efficiency gains from utilizing point-cloud data have already been demonstrated at real construction sites. For example, at one major construction company's site, a task that previously required four people working seven days (28 person-days total) to measure and calculate earthwork volumes was switched to a method of creating point clouds from drone aerial photographs to calculate volumes, and reportedly it was completed by two people in one day (2 person-days). This represents about 1/14 of the effort to achieve the same result, dramatically reducing labor and time. Moreover, the accuracy of the as-built quantity calculations was reported to be comparable to traditional methods (errors around 1%), meaning point-cloud-based earthwork calculation excels not only in efficiency but also in accuracy, and its importance has grown significantly in recent years.

Challenges and burdens of conventional point-cloud acquisition methods (laser scanners, UAVs)

Representative conventional methods for acquiring point-cloud data include terrestrial 3D laser scanning and UAV (drone) photogrammetry. Both can obtain high-precision 3D data, but their on-site operation involves several challenges and burdens.

For terrestrial laser scanners, large equipment is mounted on a tripod and set up to scan the surroundings at each station to acquire point clouds. Measuring a wide site requires scanning from multiple locations and later merging the data, which demands target placement and alignment work that require expertise and time. The equipment itself costs several million yen and is heavy to transport, and operation requires skilled operators. As a result, it has been difficult to perform 3D measurements casually or repeatedly on site, and such measurements were often limited to specific times.

For drone (UAV) photogrammetry, aerial images of the entire site are captured to generate point clouds and terrain models. This can cover large areas in a short time, but flights must comply with regulations and safety management. Flights may be restricted in densely populated areas or where there are many overhead obstacles, and adverse weather (strong winds or rain) can prevent measurement. In addition, generating a 3D model from photos requires high-performance PCs or cloud processing, so results are not immediately available at the site after shooting. When drone surveys are outsourced to specialist survey teams, scheduling and preparation take time, making frequent checks of as-built conditions difficult.

Thus, conventional point-cloud acquisition requires expensive equipment, specialized skills, and thorough preparation, imposing constraints on speed and ease of use. Even though the benefits of point clouds are clear, site personnel have often said, “It’s difficult to rely on external specialists every time” and “We can’t measure whenever we want.”

Mechanism and features of point-cloud scanning with a smartphone + RTK

A solution that is attracting attention for changing this situation is smartphone + RTK point-cloud scanning. RTK stands for Real Time Kinematic, a technology that corrects satellite positioning (GPS/GNSS) errors to provide high-precision positioning in real time. In Japan, centimeter-level augmentation services provided by Michibiki (quasi-zenith satellites) such as CLAS and network-based electronic reference point systems make it easy to obtain very high positioning accuracy within a few centimeters.

RTK positioning once required high-precision GNSS equipment costing hundreds of thousands of dollars, but small RTK-capable GNSS receivers that can connect to smartphones have now appeared. Using a specialty receiver that attaches to a smartphone via the Lightning port or Bluetooth, correction information can be applied in real time to the GPS signals the phone receives. For example, attaching a small antenna about 1–2 cm thick and weighing around 150 g to an iPhone can supply centimeter-level positioning to the phone. By using this smartphone RTK receiver (commonly called LRTK), a smartphone can instantly become a surveying device capable of centimeter-level positioning.

What happens when this high-precision position information is combined with smartphone point-cloud measurement? In fact, higher-end iPhone and iPad models are equipped with a LiDAR sensor (a light-based distance measurement sensor), and with a dedicated app they can scan surrounding terrain in a short time and acquire large amounts of 3D point-cloud data. Holding a LiDAR-equipped iPhone (for example, iPhone 12 Pro and later) or iPad Pro and sweeping it like a camera app while walking allows you to record the shape of nearby structures and ground as if shooting video. Point clouds totaling millions of points can be acquired on the spot and displayed in real time on the smartphone screen, which is impressive. The effective range of the LiDAR sensor is about a 5m radius, but by walking around and scanning you can capture targets such as slopes and spoil piles completely.

By combining this smartphone LiDAR scan with the RTK technology described above, it becomes possible to acquire high-precision, low-distortion point-cloud data that was difficult with a smartphone alone. Mechanically, during scanning the smartphone RTK receiver (LRTK) continuously measures the phone’s current position (latitude, longitude, and height) to centimeter accuracy and assigns accurate coordinates in real time to each acquired point in the point cloud. Simply put, the points obtained by LiDAR are recorded with “correct world-coordinate positions” tagged to them. Because RTK also traces the smartphone’s motion with high precision, problems like point-cloud model distortion when scanning a wide area at once are greatly reduced. This dramatically improves both the shape accuracy (how faithfully the shape of the actual object is reproduced) and the positional accuracy (whether the acquired data is placed in the correct coordinate system).

A major advantage of point-clouds acquired with smartphone + RTK is that they are aligned to surveying coordinate systems from the outset. Traditionally, point clouds had to be registered to reference points after acquisition, requiring translations and rotations to align to known points. But with smartphone scanning, when the on-site scan is completed you already have 3D data consistent with world coordinates, greatly reducing post-processing. For example, it becomes possible to overlay the design model with the acquired point cloud and check differences immediately after acquisition, and multiple point clouds acquired on different days can be compared as-is to visualize construction progress. If the dedicated app uploads point clouds to the cloud, 3D data can be checked and shared from an office PC browser with a single tap. Without special expensive equipment or specialist skills, an era in which anyone can perform high-precision 3D surveying instantly with just a smartphone + LRTK is approaching.

Workflow for comparing current state, as-built, and design models using a smartphone

Using a smartphone and LRTK makes it dramatically easier to scan the current terrain (existing condition) and the post-construction shape (as-built) on site and detect differences by comparing them with the design 3D model. Let’s follow the concrete workflow.

• Prepare design data: First, upload the design 3D model data or previously acquired point-cloud data to the smartphone’s dedicated app or a cloud service as the comparison target (for example, the pre-construction ground model). These should be uploaded in the specified coordinate system beforehand.

• Scan the site with a smartphone: At the site, attach an LRTK receiver to a LiDAR-capable smartphone and perform a point-cloud scan of the target area. Walk around the area to be measured, making sure to scan terrain and structures without omissions. Because the point cloud is displayed in real time on the smartphone screen, you can check for blind spots or missed measurements as you go. Once you have the current 3D point cloud in a short time, you can compute volumes on the spot as needed or generate a mesh to create a surface model.

• Automatic comparison with the design model: The acquired current point cloud already has highly accurate position coordinates, so it is automatically aligned with the design model prepared in the cloud. The software can then compare the two to generate difference data indicating fill or cut surpluses/deficits. You can create height-difference heat maps or calculate fill and excavation volumes for designated areas with a few clicks.

• Review and utilize the differential results: The heat maps and numerical data obtained from the comparison can be checked immediately on-site with a smartphone or tablet. Using AR, you can overlay the heat map onto the live view of the site on the smartphone screen and intuitively see where and how much the site differs from the design. Until now, pinpointing defects for as-built management required referencing as-built drawings and was time-consuming, but AR visualization lets you identify problem areas on the spot and move directly to corrective action. Differential data can be shared via the cloud with office personnel, helping align understanding between the field and the office for rapid decision-making.

Because the whole process—from current condition to as-built to design comparison—can be completed with a single smartphone, workflows for as-built inspection and quality control are beginning to change dramatically. As-built quantity checks that previously required a surveying department can now be carried out quickly by on-site technicians themselves.

Automatic differential earthwork calculation in the cloud and the value of immediacy

Point-cloud data acquired with a smartphone can be uploaded to a cloud platform for storage and analysis. The cloud provides high-performance compute resources to process heavy 3D data and perform complex differential calculations in a short time. Traditionally, earthwork calculations required drafting by experienced technicians and manual or spreadsheet calculations, but the immediacy provided by automation creates significant value.

For example, suppose a fill or backfill operation in a section has just been completed and you scan the as-built with a smartphone and calculate differential earthwork against the design model in the cloud. If results like “fill volume for the specified area: XX cubic meters; excavation volume: YY cubic meters” are automatically produced within minutes to tens of minutes, you can immediately assess construction accuracy on site and apply it to the next process. What used to be known only the next day can now be known in near real time, minimizing rework and additional corrective measures. If you share cloud-generated heat maps and reports with stakeholders immediately, reporting to clients and obtaining internal approvals can proceed rapidly.

Accumulating data in the cloud also helps track changes over time and supports future verification. You can compare the as-built point cloud from one day with a later point cloud to quantify progress, or store final data as evidence. Because these data can be displayed and analyzed intuitively in a browser, managers and technicians who are not on site can make decisions based on the same information. “Measure immediately on site, share results immediately, and make decisions”—cloud integration enables site management with an unprecedented sense of speed.

Time savings, labor reduction, and safety improvements achievable on site

The new measurement method that leverages smartphones and point-cloud technology provides effects on-site such as time savings, labor reduction, and improved safety.

First, significant reductions in work time. As-built checks that previously required waiting for the surveying team and additional time for results can now be measured and obtained whenever needed with just a smartphone. A task that once took half a day to measure a large slope might be completed in minutes with smartphone LiDAR. Increasing measurement frequency dramatically enables fine-grained tracking of daily construction progress and quick countermeasures.

Next, reductions in personnel and cost. Smartphone point-cloud measurement can generally be performed by a single person, replacing surveying tasks that once required multiple personnel. You no longer need to worry about not having enough assistant supervisors to perform surveying that day. Reducing the number of times work is outsourced to specialists also cuts subcontracting costs. Freed personnel can be reassigned to other important tasks, contributing to overall productivity improvements.

Improved safety is also notable. Surveying on cliffs and steep slopes always carries risks of falls and rockfall, but smartphone point-cloud scanning can be done from a safe distance. Because you don’t need to touch or approach the target directly, measurements in high or hazardous areas can be taken with reduced risk. Shorter work times also reduce the time spent in dangerous areas. For example, when measuring a slope manually, personnel were previously placed at the top and bottom and took time to complete the work; now it can be finished in minutes from below by waving a smartphone, greatly increasing safety. Point-cloud data records terrain conditions in detail, eliminating the need to enter narrow spaces for manual measurements.

By adopting smartphone point-cloud scanning, a cycle of rapid data acquisition → immediate analysis → immediate response becomes possible, accelerating on-site digital transformation (DX). In situations with limited time and personnel, easy-to-use 3D measurement technology will play an increasingly important role in safely and reliably advancing construction.

LRTK features: high-precision RTK positioning, AR utilization, cloud sharing, point-cloud support

Finally, let’s summarize the main features of LRTK, a solution that strongly supports smartphone point-cloud measurement. LRTK is a surveying system centered on the smartphone-mounted RTK-GNSS receiver mentioned earlier, providing an all-in-one set of convenient features that promote site DX.

• Centimeter-level RTK positioning: The LRTK receiver enables centimeter-level positioning with a smartphone. This ensures that acquired point clouds and geotagged photos always have highly reliable coordinates. Accurate absolute-coordinate point-cloud measurement, which was difficult in the past, can now be completed with just a smartphone.

• Intuitive guidance and verification via AR: High-precision alignment enables effective use of AR functions on site. For example, you can overlay the design model or a differential heat map on the real-world view to check as-built quality on the spot. There is also a coordinate navigation feature that guides users with markers on the smartphone screen to arbitrary coordinate positions, useful for stakeout and placing structures.

• Cloud sharing and immediate data processing: Scanned point clouds and observed point information can be automatically uploaded and saved to the cloud. There is no need to bring acquired data back to the office; cloud analysis for earthwork calculation and drafting can start on the spot. Generated outputs can be shared with the team immediately, and 3D models can be checked remotely via a browser.

• Support for point-cloud measurement and analysis: LRTK is not just a positioning device; its dedicated app provides 3D scanning (point-cloud measurement) functionality. It supports quick LiDAR scans using smartphone LiDAR and also a mode to generate high-resolution point-cloud models from photographs, allowing you to choose according to the situation. Since analysis such as volume calculation and cross-section generation can be performed consistently from acquired data, even those without surveying expertise can use it with confidence.

As described above, using LRTK enables a seamless integration of RTK positioning, point-cloud measurement, AR utilization, and cloud sharing to realize the next-generation smartphone surveying. For surveyors and construction managers, LRTK lowers the barrier to surveying while maintaining accuracy and efficiency, making it a reliable ally in the DX era. Increasing numbers of people say, “If I can measure easily and accurately with a smartphone, I want to try it,” and we may be approaching an era of one-smartphone-per-person surveying.

FAQ (frequently asked questions)

Q1. What do I need to start point-cloud scanning with a smartphone? A1. You need a smartphone equipped with a LiDAR sensor (e.g., iPhone 12 Pro and later, or iPad Pro) and a smartphone-compatible GNSS receiver (RTK antenna) that supports high-precision positioning. Additionally, install a dedicated app capable of point-cloud scanning and earthwork calculation. Smartphones without LiDAR can still use a photo-based point-cloud measurement mode, but for real-time capability and accuracy, the combination of a LiDAR-equipped device + RTK receiver is recommended.

Q2. How large an area can a smartphone LiDAR measure? A2. The effective range of built-in smartphone LiDAR is said to be about 5 m. Therefore, the area that can be scanned at one time is roughly within a 5 m radius, but the operator can walk around to sequentially acquire point clouds for a wider area. Multiple scan datasets can be merged later to create a larger terrain model. For very large areas, generating point clouds from many photos taken by the smartphone camera (photogrammetry mode) is also effective. This method can cover areas without range limitation, but because it requires cloud image processing, its immediacy is lower. It is advisable to use LiDAR scanning and photo-based scanning according to site conditions.

Q3. How reliable is the measurement accuracy? Is it comparable to traditional surveying? A3. The positioning accuracy obtained with smartphone + RTK point-cloud measurement can generally be considered on the order of a few centimeters in horizontal and vertical dimensions. Field verifications have reported cases where as-built earthwork volumes calculated from point clouds fell within about 1–3% error compared to results from traditional surveying methods. However, accuracy depends on reception conditions and scanning methods. In open environments with stable GNSS reception and careful scanning to avoid LiDAR gaps, accuracy sufficient for civil construction management can be obtained. Conversely, measurements with a smartphone alone (without RTK) may result in meter-level positional errors, so RTK is recommended for accurate as-built control.

Q4. Can it be used in areas without network coverage, such as mountainous regions? A4. Yes. LRTK can receive RTK correction information without an internet connection by using signals such as the CLAS signal from the Michibiki quasi-zenith satellites. Therefore, centimeter-level real-time positioning is possible even at sites outside network coverage. Point-cloud scanning itself can be completed on the smartphone, so measurements can continue at sites where radio communication is not available. Data synchronization to the cloud and detailed analysis can be performed after returning to a coverage area. The ability to use smartphone surveying in offline environments is a significant advantage.

Q5. How should I choose between drone surveying, conventional laser scanners, and smartphone scanning? A5. Drones and high-performance laser scanners are suitable for special applications such as detailed measurement of large areas at once or capturing terrain under forest canopy. Smartphone + RTK point-cloud measurement is optimal for situations that prioritize “ease and speed,” such as routine progress management or as-built checks at small to medium sites. For example, smartphone surveying is very effective when site supervisors want to measure daily backfill volumes themselves, whereas drone surveys are efficient for measuring an entire large development site via cruise flights. Smartphone scans are also effective in indoor spaces or densely built urban areas where drones cannot fly. Considering the characteristics of each method, it is desirable to use or combine them according to site scale and purpose.

Q6. Can beginners with little knowledge of machinery or surveying use it? A6. Yes. Smartphone-based point-cloud measurement is designed for intuitive operation so that it can be started without specialist knowledge. Dedicated apps provide guided scanning procedures, and complex coordinate calculations and earthwork computations are automated. Having basic surveying knowledge helps achieve better results, but the tools are made for site supervisors and technicians to handle in daily work. After a few trials, beginners can get the hang of it. By overturning the conventional notion that “surveying is the work of specialists,” smartphone + LRTK is permeating sites as a surveying tool anyone can use.