Table of Contents

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

• Challenges and effort 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 with a smartphone

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

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

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

• FAQ (frequently asked questions)

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

Point cloud data is three-dimensional data composed of numerous points in space (XYZ coordinates) with associated attribute information such as color or return intensity. 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 are increasingly used on civil engineering and construction sites as a means to capture detailed surface geometry.

Differential earthwork volume calculation compares surface data from different times—such as before and after construction, or before and after embankment/excavation—to calculate increases or decreases in volume (fill or cut). The basic principle is simple: compute volumes from terrain models at each time and take the difference to determine the actual moved earth. Traditionally, volume calculations were commonly done on-site using cross-sections measured by survey crews and methods like the average end area method; this required manually measuring heights at regular intervals and calculating for each cross-section, which was labor- and time-intensive. In contrast, methods using point cloud data scan the surface thoroughly before and after work to obtain 3D point clouds and then automatically compute earthwork volumes from their differences. Because point clouds measure the surface down to every nook and cranny, they can precisely model terrain including subtle undulations, enabling high-accuracy volume calculations. Once a mesh model is generated from acquired point clouds, recalculating volumes for different areas without additional field measurements is also easy. This greatly reduces the fieldwork and effort required for volume computation and enables rapid determination of as-built quantities—another major benefit.

The efficiency gains from using point cloud data have already been demonstrated on real construction sites. For example, at one major construction company site, a task that previously required four people working seven days (28 person-days total) for earthwork measurement and calculation was switched to a workflow that created point clouds from drone photography and computed volumes, and it reportedly was completed by just two people in one day (2 person-days). This represents about 1/14 of the labor for the same result, a dramatic reduction in manpower and time. Moreover, the accuracy of the as-built quantity calculation was essentially comparable to the conventional method (about 1% error), showing that point-cloud-based earthwork calculation is not only efficient but also accurate—hence its growing importance in recent years.

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

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 effort.

For terrestrial laser scanners, large equipment is mounted on tripods and used to scan the surroundings at each station to acquire point clouds. Measuring large sites requires scanning from multiple stations and later merging the data, which involves placing targets and performing alignment work that demands expertise and time. The equipment itself is very expensive (hundreds of thousands of dollars equivalent) and cumbersome to transport, and operation requires skilled operators. As a result, it has been difficult to perform frequent on-site measurements casually, and 3D surveying could typically only be done at limited times.

For drone (UAV) photogrammetry, the site can be photographed from above to generate point clouds and terrain models. This approach can cover wide areas in a short time, but flights must comply with regulations and safety management. Flights are restricted in densely populated areas or where there are many obstacles, and weather (strong winds or rain) can prevent measurements. In addition, generating 3D models from photos requires high-performance PCs or cloud processing, so results are not immediately available on site after shooting. If drone surveying is outsourced to a specialized survey team, scheduling and preparation take time, making frequent as-built checks difficult.

Thus, conventional point-cloud acquisition has required expensive equipment, specialized skills, and thorough preparation, imposing constraints on speed and ease of use. Although the benefits of point clouds are understood, site personnel often reported that “relying on external specialists every time is difficult” and “we can’t measure whenever we want.”

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

In recent years, a solution that is changing this situation is smartphone + RTK point-cloud scanning. RTK stands for Real Time Kinematic, a technique that corrects satellite positioning (GPS/GNSS) errors in real time to achieve high precision. In Japan, centimeter-level augmentation services such as Michibiki’s CLAS and network-based electronic reference station systems make it easy to obtain positioning accuracy within a few centimeters.

RTK positioning used to require GNSS equipment costing hundreds of thousands of dollars, but now ultra-compact RTK-capable GNSS receivers that connect to smartphones are available. By using a dedicated receiver that attaches via the smartphone’s Lightning connector or Bluetooth, correction information can be applied to the GPS signals received by the phone in real time. For example, simply attaching a small antenna about 1–2 cm (0.4–0.8 in) thick and weighing roughly 150 g to an iPhone can provide the current position to the phone with centimeter-level accuracy. 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? Higher-end iPhone and iPad models include a LiDAR sensor (a distance-measuring sensor using light), and with a dedicated app they can quickly scan surrounding terrain to obtain large amounts of 3D point-cloud data. Holding a LiDAR-equipped iPhone (for example, iPhone 12 Pro or later) or iPad Pro and waving it as you would a camera will record the shapes of nearby structures and ground as if shooting a video. Millions of points can be acquired on the spot, and the real-time 3D display on the smartphone screen is impressive. The effective range of a LiDAR sensor is approximately a radius of 5 m (16.4 ft), but by walking around to scan, you can comprehensively capture the target including slopes and mounds of soil.

Combining smartphone LiDAR scanning with the RTK technique described above enables high-precision, low-distortion point-cloud acquisition that was difficult with a smartphone alone. During scanning, the smartphone RTK receiver (LRTK) continuously measures the phone’s current position (latitude, longitude, and height) at centimeter accuracy and assigns accurate coordinates to each acquired point in real time. Simply put, the cloud of points obtained by LiDAR is recorded while being tagged with “correct world coordinates.” RTK also traces the smartphone’s motion with high precision, greatly reducing issues like distortion of the point-cloud model when scanning a wide area at once. As a result, both the shape accuracy (how faithfully the model reproduces the real shape) and the positional accuracy (whether the acquired data is correctly placed in a coordinate system) are dramatically improved.

A major advantage of point clouds acquired with smartphone + RTK is that they are aligned to a survey coordinate system from the start. Traditionally, point clouds required post-processing like aligning datasets to ground control points or applying translations and rotations to match known points. But with smartphone scanning, the 3D data is already consistent with world coordinates when the scan is completed on site, significantly reducing post-processing effort. For example, it becomes immediately possible to overlay the design model and point cloud right after acquisition to check differences, and point clouds acquired on different days can be directly compared to visualize construction progress. If point-cloud data is uploaded to the cloud from a dedicated app, 3D data can be checked and shared from an office PC browser with one tap. An era is approaching in which anyone can perform immediate high-precision 3D surveying with just a smartphone + LRTK, without special expensive equipment or expert skills.

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

Using a smartphone and LRTK makes it much easier to scan the site’s current terrain (as-built) or post-construction shape (as-built) and compare it with the design 3D model to detect differences. Here is a concrete workflow.

• Prepare design data: Upload the design 3D model data and any previously acquired point cloud data to the smartphone’s dedicated app or cloud service as comparison targets (for example, the pre-construction ground model). These should be uploaded in the appropriate coordinate system in advance.

• Scan the site with the smartphone: On site, attach the LRTK receiver to a LiDAR-capable smartphone and perform point-cloud scanning of the target area. Walk around the area you want to measure to scan terrain and structures without omission. The smartphone screen displays the point cloud in real time, allowing you to confirm there are no blind spots or missed measurements. Once you have quickly acquired the as-built 3D point cloud, you can calculate volumes on the spot or generate a mesh to model the surface as needed.

• Automatic comparison with the design model: Because the acquired as-built point cloud already has high-precision positional coordinates, automatic alignment with the design model prepared in the cloud is already complete. Software can then compare the two and generate differential data indicating excess or deficiency in fill or cut. You can create a heat map color-coding height differences of the surface or calculate fill and excavation volumes for a designated area with just a few clicks.

• Review and use differential results: The heat maps and numerical results from the comparison can be checked immediately on a smartphone or tablet on site. Using AR features, you can overlay the heat map on the live camera view of the site to intuitively see where and by how much the as-built differs from the design. Previously, identifying defective areas from as-built control drawings and then locating them on site was time-consuming, but AR visualization allows you to identify problem areas on the spot and move directly to corrective work. Differential data can be shared via the cloud with office personnel, enabling rapid decision-making with aligned understanding between the field and office.

Because the entire process—from scanning current state to comparing as-built and design—can be completed with a single smartphone, workflows for as-built inspection and quality control are beginning to change dramatically. Tasks that used to be requested from specialized surveying departments can increasingly be performed quickly by site technicians themselves.

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

Point cloud data obtained with a smartphone can be uploaded to and stored on a cloud platform for analysis. The cloud provides powerful computational resources, allowing heavy 3D data processing and complex differential calculations to be completed quickly. The immediacy enabled by this automation creates significant value.

For example, assume a fill or backfill operation in a section has just been completed and you scan the as-built with a smartphone, then calculate the differential earthwork against the design model in the cloud. If the cloud can automatically output results such as “fill volume for the designated area: XX cubic meters, excavation volume: YY cubic meters” within minutes to tens of minutes, you can immediately evaluate construction accuracy on site and apply the findings to the next process. What used to take until the next day to determine as-built quantities can now be done almost in real time, minimizing rework and additional measures. If the heat maps and reports generated in the cloud are shared with stakeholders immediately, reporting to clients and internal approvals can proceed faster.

Additionally, storing data in the cloud supports time-series change tracking and future verification. You can compare an as-built point cloud from one day with a later point cloud to quantify progress, or keep completion data as evidence. Because these data can be intuitively displayed and analyzed in 3D via a browser, supervisors and engineers off-site can make decisions based on the same information. “Measure on site and share results immediately to enable fast decision-making”—cloud integration enables site management with a speed previously unattainable.

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

The new measurement method using smartphones and point-cloud technology brings effects of time savings, labor reduction, and safety improvements to on-site operations.

First, substantial reduction in work time. As-built checks that used to require waiting for a survey team and then additional time for survey results can now be done whenever needed with just a smartphone. In cases where slope as-built measurement took half a day, smartphone LiDAR may complete it in minutes. By dramatically increasing measurement frequency, you can closely track daily construction progress and quickly implement countermeasures.

Next, reduction in personnel and cost. Smartphone point-cloud measurement can generally be performed by one person, replacing survey work that used to require multiple people. There is no worry such as “we don’t have enough assistant supervisors today, so we can’t do surveying.” Reducing the frequency of outsourcing to specialized vendors also lowers subcontracting costs. The personnel freed up by efficiency gains can be allocated to other important tasks, improving overall productivity.

Finally, improved safety should not be overlooked. Surveying on cliffs or steep slopes carries fall and rockfall risks, but smartphone point-cloud scanning can be performed from a safe distance. Because you do not need to approach or touch the measured target, measurements in high or hazardous areas can be conducted with reduced risk. Shorter work times also reduce the duration spent in dangerous areas. For example, where manual slope measurement used to require staff positioned at the top and bottom for extended periods, simply waving a smartphone from below for a few minutes can complete the task, greatly improving safety. Because point clouds record terrain conditions down to every corner, there is no need to cram into narrow spaces to take measurements.

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

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

Finally, here are 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 described above, and it offers an all-in-one set of convenient functions that promote on-site DX.

• Centimeter-level RTK positioning: With an LRTK receiver, a smartphone can achieve positioning accuracy within a few centimeters. This ensures that acquired point clouds and geo-tagged photos always have highly reliable coordinates. Accurate point-cloud measurement with absolute coordinates, which was difficult until now, can be completed with just a smartphone.

• Intuitive guidance and verification with AR: High-precision alignment enables effective on-site use of AR (augmented reality). For example, you can overlay the design model or differential heat map on the real scene to check as-built compliance immediately. An additional coordinate navigation feature can guide you to arbitrary coordinate positions with markers on the smartphone screen, useful for staking out or positioning structures.

• Cloud sharing and immediate data processing: Scanned point clouds and observed point data can be automatically uploaded and stored in the cloud. There is no need to take acquired data back to the office—the cloud analysis for earthwork calculation and diagram generation can start on the spot. Results can be shared with the team immediately, and 3D models can be viewed remotely via a browser.

• Support for point-cloud measurement and analysis: LRTK is not just a positioning device; its dedicated app also provides 3D scanning (point-cloud measurement) functionality. It supports quick scans using smartphone LiDAR as well as modes that generate high-resolution point clouds from photographs, allowing flexible use depending on the situation. From acquired data, analyses such as volume calculation and cross-section creation can be performed end-to-end, so even users without surveying expertise can obtain reliable results.

As described above, LRTK enables a seamless integration of RTK positioning, point-cloud measurement, AR utilization, and cloud sharing to realize a next-generation smartphone surveying solution. For surveyors and construction managers on site, LRTK lowers the barrier to surveying while balancing accuracy and efficiency, making it a reliable ally in the DX era. Growing voices say, “If I can easily and accurately measure with just my smartphone, I want to try it,” and we may soon enter an era where each person has a smartphone for 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 or later, or iPad Pro) and a smartphone GNSS receiver (RTK antenna) that supports high-precision positioning. In addition, install a dedicated app that can perform point-cloud scanning and earthwork calculations. For smartphones without LiDAR, a photogrammetry mode using photos is available, but for real-time capability and accuracy, the combination of a LiDAR-equipped device + RTK receiver is recommended.

Q2. How large an area can smartphone LiDAR measure? A2. The effective range of built-in smartphone LiDAR is about 5 m (16.4 ft). Thus, the area that can be scanned at one time is roughly within a 5 m radius, but an operator can walk around to sequentially acquire point clouds for larger areas. Multiple scan datasets can be merged afterward to create a wider terrain model. For very large areas, generating point clouds from numerous photos taken with the smartphone camera (photogrammetry mode) is also effective. This approach has no distance limitation, but it requires cloud-based image processing and is less immediate. 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 conventional surveying? A3. Positioning accuracy obtained with smartphone + RTK-based point-cloud measurement is generally on the order of a few centimeters in all dimensions. Field validations have reported cases where as-built earthwork volumes computed from point clouds agreed with conventional surveying results within about 1–3% error. However, accuracy depends on the receiver’s signal conditions and the scanning method. In open environments with stable GNSS reception and careful LiDAR scanning to avoid omissions, accuracy sufficient for civil construction management can be achieved. Conversely, measurements with a smartphone alone (without RTK) can exhibit positional errors on the order of meters, so RTK is recommended for accurate as-built control.

Q4. Can it be used in remote mountain areas without network coverage? A4. Yes. LRTK can receive RTK correction information in environments without internet connectivity by using signals such as the Michibiki CLAS service. Therefore, real-time centimeter-level positioning is possible even at sites without mobile network coverage. Point-cloud scanning itself can be completed on the smartphone, so measurements can continue in areas without reception. Data synchronization with the cloud and detailed analysis can be performed after returning to an area with connectivity. The ability to use smartphone surveying in offline environments is a major advantage.

Q5. How should I decide between drone surveying, conventional laser scanners, and smartphone-based methods? A5. Drones and high-end laser scanners are well suited to applications that require detailed measurement of large areas at once or capturing terrain under forest cover, among other specialized uses. Smartphone + RTK point-cloud measurement is ideal for routine progress management and as-built checks on small to mid-sized sites where “ease and speed” are priorities. For example, a site supervisor measuring daily backfill volumes will find smartphone surveying powerful, whereas surveying an entire vast development site is more efficiently done with drone flights. Smartphone scanning is also effective indoors or in dense urban areas where drones cannot fly. Consider the characteristics of each method and use or combine them according to site scale and purpose.

Q6. Can beginners with little knowledge of machinery or surveying use this? A6. Yes. Smartphone-based point-cloud measurement is designed for intuitive operation so that those without specialized knowledge can start using it. Dedicated apps provide guided scanning procedures, and complex coordinate and volume calculations are automated. Basic surveying knowledge helps achieve better results, but the tools are created for site supervisors and technicians to use routinely. With a few trials, beginners can quickly learn the workflow. By overturning the conventional notion that “surveying is the work of specialists,” smartphone + LRTK is spreading as a surveying tool anyone can use on job sites.