In recent years, point cloud measurement technology that combines LiDAR (Light Detection and Ranging) and GNSS (Global Navigation Satellite System) has attracted attention in the surveying and construction industries. Among these, a smartphone-integrated surveying system called "LRTK LiDAR" enables complete workflows—from surveying and as-built management to overlaying drawings via AR (augmented reality)—with a single device. This article starts with the principles and basic components of point cloud acquisition using LiDAR and GNSS, then comprehensively explains the practical benefits of smartphone-integrated LiDAR surveying, the use of point clouds for as-built management, visualization of construction drawings using AR, comparisons with conventional methods, an integrated workflow combining LRTK and smartphone LiDAR, and cloud sharing and report generation for acquired point cloud data. This complete guide reveals the full picture of LRTK LiDAR, which allows anyone to perform high-accuracy surveying with just one smartphone.

Table of Contents

• Principles and basic components of point cloud acquisition using LiDAR and GNSS

• Practical benefits of smartphone-integrated LiDAR surveying

• Use of point clouds in as-built management (accuracy, comparison, cross-sections)

• Expansion to drawing overlay and position checking using AR (augmented reality)

• Comparison and appropriate use with conventional methods (3D scanners, total stations, etc.)

• Integrated, end-to-end measurement workflow combining LRTK and smartphone LiDAR

• Flow from point cloud cloud sharing to report integration

• FAQ

Principles and basic components of point cloud acquisition using LiDAR and GNSS

LiDAR (Light Detection and Ranging) is a technology that irradiates laser light onto an object and measures distance from the return time of the reflected light, obtaining the surrounding shape as a collection of points (point cloud data). A single scan can acquire tens of thousands to hundreds of thousands of 3D coordinates, recording fine surface details and terrain with high density. GNSS (Global Navigation Satellite System), on the other hand, is a positioning technology that computes position by receiving signals from satellites, and by using the RTK method (Real-Time Kinematic) it is possible to perform high-accuracy positioning with errors on the order of a few centimeters (a few in).

LRTK LiDAR is a point cloud measurement system that combines LiDAR and RTK-GNSS. RTK-GNSS assigns absolute (global) coordinates in real time to the point cloud acquired by the LiDAR sensor, so that each point is given Earth-referenced coordinates. This enables generation of point cloud data compliant with geodetic coordinate systems during measurement, without post-processing to match control points or installing target markers on site.

The basic configuration of LRTK LiDAR consists of a smartphone equipped with a LiDAR sensor (for example, Pro models of iPhone) with a compact RTK-GNSS receiver attached, and a dedicated surveying app. While scanning the surroundings with the phone’s LiDAR, the GNSS receiver acquires the device position with cm level accuracy (half-inch accuracy), and the two data streams are integrated within the app. The phone’s built-in inertial measurement unit (IMU) and camera images are also used to estimate device attitude and to complement areas where LiDAR does not reach (photogrammetry-based point cloud generation). This combination of hardware and software coordination realizes the principle of LRTK LiDAR: positioning and point cloud acquisition as a single integrated process.

Practical benefits of smartphone-integrated LiDAR surveying

Smartphone-integrated LiDAR surveying offers various advantages for fieldwork. First, the equipment is extremely compact. With just a smartphone and a palm-sized GNSS receiver, there is no need to bring tripods, large scanners, or laptops to the site. One person can operate it easily, dramatically improving mobility. Carrying a pocketable device and being able to take measurements whenever the need arises provides convenience that fixed surveying instruments cannot match.

Next, operation is intuitive and requires no specialized knowledge. On the smartphone app screen, anyone can press “Start Scan,” point the camera, and walk to capture a 3D point cloud of the surroundings. Historically, high-accuracy surveying required skilled surveyors and complex settings, but LRTK LiDAR enables site staff to handle routine measurements and as-built checks themselves. This reduces dependence on surveying specialists for everyday measurement tasks.

The ability to handle confined spaces and complex terrain is another strength of smartphone LiDAR. For example, areas that tend to be blind spots for drones or large laser scanners—such as the underside of bridges, parts of slopes, or under trees—can be approached freely with a handheld smartphone for scanning. There is no need to bring large equipment for small-area partial surveys, and local point cloud complementation is efficient. Because acquired point clouds are visualized on the smartphone in real time, you can confirm and immediately re-scan any missed areas on site. This immediate verification reduces revisits due to measurement errors.

Also notable are the low cost and high efficiency inherent to smartphone integration. Initial investment is lower than equipping specialized high-cost devices, and provisioning one device per worker is more feasible, improving overall site efficiency. A single unit can perform position measurement, point cloud capture, photo documentation, and AR display, reducing the need to switch devices. For example, tasks that were previously performed separately—setting formwork with a total station, capturing point clouds with a laser scanner, and checking drawings on a tablet—can be handled end-to-end with a single smartphone using LRTK LiDAR.

Thus, smartphone-integrated LiDAR surveying enables “anyone, anywhere, immediately” to perform high-accuracy 3D measurements, significantly improving productivity and flexibility on site.

Use of point clouds in as-built management (accuracy, comparison, cross-sections)

As-built management in civil and construction projects is a quality-control process that verifies whether completed structures or graded terrain match the design shapes and dimensions. High-accuracy point cloud data acquired with LRTK LiDAR are highly useful for as-built management.

First, point clouds provide vastly denser as-built data than traditional survey points (single-height measurements by staff or isolated setup surveys). For example, scanning a road or graded area captures surface irregularities across the entire area to millimeter-level detail, ensuring localized elevation differences and unevenness are not overlooked. With such detailed as-built data, the accuracy and reliability of as-built determinations increase dramatically.

Acquired as-built point clouds are used to compare against design data. By overlaying point clouds with 3D design models (or design surface elevations) in dedicated software or on the cloud, you can immediately see whether construction results match the design. Creating a heat map that visualizes height differences between the design surface and measured point cloud—blue to green for small errors, yellow to red for large errors—lets you intuitively grasp construction accuracy. This enables on-site checks of embankment and excavation conformance to design, verification that finished slopes and layer thicknesses are within tolerances, and early detection and correction of defects.

Point cloud data also allow flexible generation of cross-sections and volume calculations. You can extract cross-sectional shapes by slicing the point cloud longitudinally or transversely at arbitrary positions and compare them with design cross-sections to evaluate as-built conditions. For example, producing cross-sections at regular intervals across a roadway and comparing them to standard design sections enables detailed verification of width and subgrade elevation. Volume (earthwork) surpluses and deficits can be calculated from differences between the completed-surface point cloud and the design model. On LRTK cloud services, you can overlay the design 3D model on the as-built point cloud and compute differential volumes with one click. This immediately answers questions like “How many cubic meters of fill remain?” or “How much extra excavation was performed?” and streamlines as-built checks and quantity estimation.

Because LRTK LiDAR point clouds are directly georeferenced by RTK-GNSS, conforming to required coordinate and elevation references for as-built management is straightforward. These point clouds can be used as-is for deliverables conforming to the Ministry of Land, Infrastructure, Transport and Tourism’s as-built management guidelines (for example, electronic deliverables for national projects). When accuracy verification is needed, you can scan a few known on-site control points and compare to confirm and correct errors. Even so, point cloud-based as-built management offers significantly simpler procedures and high-quality outcomes compared with conventional methods.

Expansion to drawing overlay and position checking using AR (augmented reality)

LRTK LiDAR also supports AR (augmented reality) displays using acquired point cloud data and design data. AR enables overlaying digital drawings and 3D models onto live site images, intuitively visualizing design and construction plans on site.

For example, if you load the planned structure model or design terrain onto the smartphone, you can display that 3D model in AR at the intended position through the camera view. Since LRTK LiDAR point clouds already have global coordinates assigned during acquisition, models can be placed at correct coordinates, enabling AR projections that do not drift. Even as workers move around the site, AR-displayed objects remain in their correct positions, helping stakeholders share completion images and check for discrepancies with design. As a “site visualization” tool, AR can be used during meetings with clients to show the expected finished appearance on the spot.

AR also improves the efficiency of staking-out and marking tasks. LRTK systems can drop virtual “AR stakes” at arbitrary coordinate positions. For instance, if you input reference points or stake-out positions from the design into the app, virtual stakes appear at those locations on the smartphone screen. Workers can follow on-screen arrows to move to those positions, enabling identification of target points with cm-level accuracy (half-inch accuracy) even in places where GPS reception is poor or physical markers cannot be installed (steep slopes, over water, etc.). Tasks that previously required using surveying instruments to compute coordinates and place stakes can now be performed intuitively by anyone via AR stake display, allowing quick and labor-saving on-site position checks.

Visualizing previously acquired point clouds of underground utilities with AR is also an effective application. For example, if you AR-display location data of buried pipes or cables previously scanned, it becomes easier to avoid them during subsequent excavations. Being able to render invisible underground items as see-through layers reduces the risk of accidental damage and improves safety.

By leveraging LRTK LiDAR’s AR capabilities, you can seamlessly link drawings and the field, share completion expectations, and guide surveying tasks—creating new workflows that connect the site and design. Augmented reality enables intuitive position checks, allowing the whole team to share a spatial image that planar drawings or stakes alone could not convey.

Comparison and appropriate use with conventional methods (3D scanners, total stations, etc.)

The emergence of LRTK LiDAR has expanded the range of measurement options on site. Below is a comparison between representative conventional methods (drone photogrammetry, terrestrial 3D laser scanners, total station surveying, etc.) and smartphone LiDAR measurement, outlining strengths and appropriate uses for each.

• Drone photogrammetry: Aerial photogrammetry via drone is effective for large areas (several hectares or more) and bulk measurement from above. It can generate overview terrain models quickly and is suited for large earthworks or forest surveys. However, drone use is constrained by weather and flight permissions and is difficult to use in urban or indoor environments. Achieving high accuracy often requires placing ground control points (GCPs) and post-processing, which adds effort. Smartphone LiDAR is limited to the walkable range of an operator, but it can be used regardless of weather or location and captures detailed point clouds. For large projects, a combined approach—drone for the overall survey and smartphone LiDAR to fill in details and blind spots—is effective.

• Terrestrial 3D laser scanners: Tripod-mounted laser scanners can measure accurately to several hundred meters and are powerful for precise recording of entire structures, tunnels, or plants. However, these devices are large, expensive, and require specialized skills for operation and data processing. They also require post-scan merging (registration) of multiple scans. In contrast, smartphone LiDAR is a mobile tool focused on everyday small-scale measurements. Although its accuracy is about 2 cm (about 0.8 in) compared to laser scanners with measurements on the order of several millimeters (a few hundredths of an inch), smartphone LiDAR provides real-time results on site and automates data registration and coordinate calculations. For scenarios prioritizing responsiveness with sufficient accuracy, smartphone LiDAR excels; for millimeter-level accuracy or long-distance measurement, conventional scanners are more appropriate.

• Total station (TS) surveying: TS measures coordinates point by point with high accuracy (millimeter-level) using prisms or reflective targets, and remains indispensable for tasks like layout of structural lines, foundation positioning, and deformation monitoring. However, capturing surface geometry requires many points and is time-consuming. Smartphone LiDAR acquires surfaces comprehensively as a point cloud, making it efficient for broad shape capture. Note that in GNSS-denied environments like indoors or tunnels, smartphone LiDAR alone cannot obtain absolute coordinates in real time; TS or known control points are needed later to georeference the point cloud. Therefore, use TS for indoor surveying or local high-precision control, and smartphone LiDAR for outdoor broad 3D capture.

• Handheld SLAM scanners: Recently, handheld 3D scanners using SLAM (simultaneous localization and mapping) have appeared. They create point cloud maps by simply walking indoors or outdoors and are conceptually similar to smartphone LiDAR, but they are costly as dedicated devices and often require external GNSS base stations or target markers to provide absolute coordinates for the obtained point cloud. LRTK LiDAR, by contrast, uses a general-purpose smartphone combined with RTK-GNSS to directly georeference scans, offering low-cost, easy acquisition of absolute-coordinate point clouds.

Considering the above, select and combine methods on site according to project scale, required accuracy, and surrounding environment. LRTK LiDAR is particularly positioned as a new option that balances overwhelming efficiency and sufficient accuracy for small- to medium-scale projects and routine surveying tasks. For ultra-high precision or special conditions, combining conventional techniques remains important. Leveraging each method’s strengths and choosing appropriately maximizes surveying productivity across projects.

Integrated, end-to-end measurement workflow combining LRTK and smartphone LiDAR

Here we outline a typical measurement workflow using LRTK LiDAR. When smartphones, GNSS/LiDAR devices, and cloud services are integrated in LRTK, surveying and data utilization on site are seamlessly connected.

• Preparation and setup: On site, attach the RTK receiver to the LiDAR-equipped smartphone and launch the dedicated app. Even for first-time use, complex settings are not required; simply ensure the device can receive RTK correction data (from internet-based reference station data or satellite augmentation signals) and positioning is ready. (LRTK supports the QZSS CLAS satellite augmentation signal in Japan, enabling cm-level positioning even in mountainous areas outside cellular coverage.) If needed, mount the device on a monopod or pole and input the height offset for more stable positioning.

• Positioning and start scanning: Select the surveying mode in the app and begin measurement. To acquire a point cloud, press “Start Scan” and walk around the area you want to measure while holding the smartphone. The LiDAR sensor captures surrounding geometry while GNSS continuously logs the operator’s position. Point clouds are generated in real time on the screen, allowing you to confirm coverage and density as you proceed. You can pause and resume as needed and re-scan missed areas flexibly.

• Data saving and cloud sync: After scanning, save the data in the app. The acquired point cloud and measured coordinate data are stored on the smartphone with metadata (date/time, GNSS accuracy, notes, etc.). With one tap, you can sync to the cloud from the field and upload data before leaving the site. Once synced, the data can be viewed and shared from an office PC or other stakeholders’ devices via a web browser.

• Data use and analysis: Point cloud data uploaded to the cloud can be analyzed and utilized extensively on the LRTK web platform. For example, you can inspect the 3D model by rotating and zooming in a point cloud viewer, measure distances and elevation differences between arbitrary points, and calculate areas and volumes via a browser. You can also upload design drawings or BIM models and overlay them with point clouds to analyze as-built differences. The platform can automatically generate cross-sections from point clouds for CAD export, and attach geotagged photos to the point cloud—integrations that directly connect field measurement data to design and reporting workflows.

• Reporting and sharing: After completing analysis, compile results such as cross-sections, heat map images, and volume calculation reports into deliverables. Because LRTK cloud data are always stored in the latest version, stakeholders can view the most recent survey results via shared links. No dedicated software installation or high-performance PC is required; anyone with a web browser can handle 3D point clouds, facilitating smooth information sharing with clients and subcontractors.

Through this integrated workflow, data acquisition, processing, and sharing are digitally connected end-to-end. Field-collected information is uploaded to the cloud immediately and used directly for analysis and reporting, greatly reducing data handover and cumbersome post-processing that characterized traditional workflows. As a result, the cycle from surveying to construction management shortens, accelerating on-site DX (digital transformation).

Flow from point cloud cloud sharing to report integration

Point cloud data acquired by LRTK LiDAR can be maximized through cloud-based sharing and smooth integration into reports. Traditionally, sharing surveying data among stakeholders required compiling CAD drawings or PDF reports for distribution. LRTK centralizes measurement data in the cloud, enabling efficient workflows as follows.

● Immediate verification via cloud sharing: Point clouds uploaded from the field are instantly viewable from the office or other locations via the internet. Supervisors or clients located remotely can review 3D data right after the field scan, enabling real-time sharing and faster decision-making. Because the sharing is via a web browser, recipients do not need specialized software—simply sending a URL allows anyone to interactively view and operate the point cloud on their PC or tablet.

● Export to standard formats: Cloud point cloud data and measurements can be exported to familiar formats for use in established workflows. Point clouds can be exported as LAS or PLY for detailed analysis in existing point cloud software, or as DXF for CAD import as plans or sections. Measured coordinate lists can be exported as CSV or SIMA formats for electronic deliverables. The convenience of completing workflows within the LRTK system while maintaining compatibility with external tools enables smooth integration into company processes.

● Use in reports: Heat maps, cross-sections, and measurement lists generated in the cloud can be directly used in as-built management reports and internal documents. For example, including a heat map created from point clouds in a report provides a visual summary of construction accuracy. Cross-sections and numeric tables can be pasted into reports without manual transcription, reducing errors and time spent creating drawings. With less effort spent on report preparation, staff can focus on higher-value analysis and construction planning.

In this way, LRTK LiDAR data are digitally linked from acquisition through processing, sharing, and reporting. Faster communication between field and office not only improves measurement accuracy but also enhances the speed and quality of reporting—an important value for modern construction sites.

FAQ

Q. What level of accuracy can be obtained with LRTK LiDAR? A. Under typical conditions, horizontal positioning accuracy is on the order of ±1–2 cm (±0.4–0.8 in), and vertical accuracy is on the order of ±2–3 cm (±0.8–1.2 in). Relative accuracy between points in the point cloud (shape distortion) is also within about 2 cm (about 0.8 in), which is sufficient for standard civil surveying and as-built management. However, GNSS positioning quality depends on satellite reception and the surrounding environment, so conducting surveys in locations with good sky visibility is recommended for reliable accuracy.

Q. Which smartphones are supported? Is a dedicated device required? A. LRTK LiDAR operates on iPhones or iPads equipped with LiDAR sensors. Specifically, compatible devices include Apple iPhone 12 Pro and later, and iPad Pro models from 2020 onward, which have built-in LiDAR units accessible by the app for point cloud capture. As of 2025, there are no known Android device examples supported; LRTK is primarily supported on iOS devices with LiDAR. For high-accuracy positioning, a separate LRTK GNSS receiver is required, which can be used simply by attaching a dedicated compact device to the smartphone.

Q. Can it be used in areas without cellular connectivity? A. Yes. LRTK supports CLAS correction information distributed by the QZSS “Michibiki” satellite, enabling positioning even where internet connectivity is unavailable. By equipping the LRTK receiver with a dedicated antenna in advance, you can receive satellite-based correction signals and maintain cm-level accuracy in mountainous or remote island areas outside base station communication coverage. However, in environments where GNSS signals themselves cannot be received—such as inside tunnels—positioning is not possible in real time, so use alternative methods as described elsewhere.

Q. How long does point cloud measurement take, and what range can be measured? A. Measurement time and coverage vary depending on site size and complexity, but small structures can be scanned in tens of seconds to a few minutes. For example, walking along a slope with a height difference of about 30 m (98.4 ft) and scanning from end to end can typically acquire a complete point cloud in about one minute. The effective range of point clouds is fundamentally limited to the LiDAR sensor’s line-of-sight (a radius of a few meters (a few ft)), but by moving the operator, data can reach somewhat farther (tens of meters away). With image analysis augmentation, LRTK has achieved point cloud generation for targets up to about 50–60 m (164.0–196.9 ft) away. Note that point density becomes coarser at longer distances, so for areas requiring high accuracy, scanning from closer distances is recommended.

Q. Can LRTK LiDAR be used indoors or in tunnels? A. Partially, but care is needed. LiDAR sensors themselves function indoors and in tunnels, so you can capture surrounding geometry as a point cloud. However, in environments where GNSS signals cannot reach, you cannot assign absolute coordinates in real time; the acquired point cloud will be in a relative (local) coordinate system. Additional work is required later to tie the local point cloud to outdoor control points. Also, relying only on IMU-based position estimation can lead to gradual drift and distortion in large indoor spaces. For high-accuracy indoor measurements, we recommend combining LRTK’s simplified surveys with verification using total stations at key points.

Q. Will conventional surveying instruments become unnecessary? A. LRTK LiDAR is a highly versatile and convenient tool, but it does not replace all traditional instruments in every situation. For example, total station surveys remain effective for foundation work requiring millimeter-level control, and drone or aerial photogrammetry is efficient for surveys covering tens of hectares. For indoor or underground surveys where LRTK faces limitations, conventional methods or other 3D scanning technologies are still needed. Nevertheless, for routine civil surveying and as-built measurements on small to medium sites, there are many scenarios where LRTK LiDAR can “complete everything with this one device.” By combining LRTK with conventional instruments as appropriate, you can significantly reduce labor and improve efficiency for most surveying tasks.