LRTK LiDAR Complete Guide to Point Clouds: From Surveying and As-Built Management to AR — All in One Device

In recent years, point cloud measurement technology combining LiDAR (Light Detection and Ranging) and GNSS (Global Navigation Satellite Systems) has attracted attention in the surveying and construction industries. In particular, using the smartphone-integrated surveying system LRTK LiDAR makes it possible to complete everything from surveying and as-built management to AR (augmented reality) overlaying with a single device. This article starts with the principles and basic configuration of point cloud acquisition using LiDAR and GNSS, then explains the practical advantages of smartphone-integrated LiDAR surveying, the use of point clouds for as-built management, visualization of construction drawings via AR, comparisons with conventional methods, an integrated workflow combining LRTK and smartphone LiDAR, and the process from acquired point cloud data to cloud sharing and report creation. This complete guide reveals the full scope of LRTK LiDAR, which enables anyone to perform high-precision surveying easily with a single smartphone.

Table of Contents

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

• Practical advantages of LiDAR surveying with an integrated smartphone

• How to use point clouds for as-built management (accuracy, comparison, cross-sections)

• Expanding into overlaying drawings and position verification using AR (augmented reality)

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

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

• The flow from point cloud cloud sharing to report integration

• FAQ

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

LiDAR (Light Detection and Ranging) is a technology that emits laser light onto objects and measures distance from the return time of the reflected light to capture the surrounding shape as a set 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 at high density. Meanwhile, GNSS (Global Navigation Satellite Systems) is a positioning technology that calculates position by receiving signals from satellites; in particular, using the RTK method (Real-Time Kinematic) enables high-precision positioning with errors of a few centimeters.

LRTK LiDAR is a point cloud measurement system that combines LiDAR and RTK-GNSS. RTK-GNSS provides real-time absolute coordinates (global coordinates) to the point cloud acquired by the LiDAR sensor, assigning Earth-referenced coordinate values to each point. This allows generation of point cloud data in a geodetic coordinate system simultaneously with measurement, without the need to match to control points or place target markers on site in post-processing.

The basic configuration of LRTK LiDAR is a smartphone equipped with a LiDAR sensor (e.g., certain iPhone Pro models) with a compact RTK-GNSS receiver attached, used together with a dedicated surveying app. While the smartphone’s LiDAR scans the surroundings, the GNSS receiver acquires the device’s position at cm level accuracy (half-inch accuracy), and the app integrates both data streams. The smartphone’s built-in inertial measurement unit (IMU) and camera images are also used to estimate device attitude and to complement areas out of the LiDAR’s reach (photogrammetry-based point cloud generation). This interaction of hardware and software—integrating positioning and point cloud acquisition into one package—is the core principle of LRTK LiDAR.

Practical advantages of LiDAR surveying with an integrated smartphone

Smartphone-integrated LiDAR surveying offers various practical 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 a laptop to the site. One-person operation is easy, dramatically increasing mobility. Carrying a pocketable device at all times and being able to take measurements whenever needed—“just measure this quickly”—is an ease that fixed surveying instruments cannot match.

Next, the intuitive operation requiring no specialized knowledge is important. On the smartphone app, anyone can press “Start Scan,” point the camera, and walk around to capture the surrounding 3D point cloud. Historically, high-precision measurement required skilled surveyors and complex settings, but with LRTK LiDAR, onsite staff can easily handle routine scans. This allows everyday measurements and as-built checks to be performed without relying solely on surveying specialists.

The ability to work in confined spaces and complex terrain is also a strength of smartphone LiDAR. For example, areas that tend to be occluded for drones or large laser scanners—such as under bridges, certain slope sections, or under trees—can be scanned by moving a handheld smartphone close to the target. There is no need to deploy bulky equipment for small-area partial surveys, making local point cloud supplementation efficient. Because the acquired point cloud is visualized in real time on the smartphone, users can confirm and re-scan any omissions on the spot, ensuring coverage and preventing revisits due to missed measurements.

Additionally, the low cost and high efficiency inherent to smartphone integration should not be overlooked. Initial investment is lower compared with procuring dedicated high-end equipment, and distributing one device per person on site is feasible, improving overall work efficiency. One device can perform position measurement, point cloud capture, photo documentation, and AR display, reducing the need to swap between multiple devices. For example, tasks that traditionally required separate actions—setting out with a total station, capturing point clouds with a laser scanner, checking drawings on a tablet—can be handled consistently with a single smartphone using LRTK LiDAR.

In summary, smartphone-integrated LiDAR surveying enables “anyone, anywhere, immediately” to conduct high-precision 3D measurements, significantly improving productivity and flexibility in the field.

How to use point clouds for as-built management (accuracy, comparison, cross-sections)

In civil and construction works, as-built management is the quality control process for verifying that completed structures and formed terrain match the design shapes and dimensions. High-precision point cloud data acquired by LRTK LiDAR are extremely useful for this as-built management.

First, point clouds provide vastly denser current-condition data compared to traditional survey points (spot leveling or single fixed measurements). For example, scanning a road or developed land captures surface irregularities across the entire area down to the millimeter level, ensuring local elevation differences and unevenness are not overlooked. With such detailed current-condition data, the accuracy and reliability of as-built judgments improve dramatically.

The acquired point cloud can be used to compare against design data. By overlaying the point cloud with a 3D design model (or design elevation surface) in dedicated software or on the cloud, you can instantly determine whether construction matches the design. Creating a “heatmap” that visualizes height differences between the design surface and the measured point cloud—where small errors are shown in blue–green and larger discrepancies in yellow–red—lets you intuitively grasp construction accuracy. This enables immediate onsite checks to see whether embankments or cuts conform to design, whether finish slopes and thicknesses are within tolerances, and, if not, to discover and correct faults early.

Moreover, point cloud data allow free creation of cross-sections and earthwork volume calculations. You can slice the point cloud longitudinally or transversely at arbitrary positions to extract cross-sectional shapes and overlay them with design sections to evaluate as-built conditions. For example, by generating transverse point cloud sections at regular intervals along a road and comparing them with standard design cross-sections, you can examine carriageway width and pavement elevation in detail. Also, by calculating the difference between the completed terrain point cloud and the design model, you can compute volume (earthwork) excesses or shortages. On LRTK LiDAR’s cloud services, you can overlay the current point cloud with a 3D design model and calculate differential volumes with one click—instantly answering questions like “how many cubic meters of fill remain needed?” or “how much did we over-excavate compared to the design?”—thus streamlining as-built verification and quantity estimation.

Because point clouds acquired by LRTK LiDAR are directly tied to geodetic coordinates via RTK-GNSS, compliance with reference coordinate systems and vertical datums required by as-built management procedures is straightforward. These point clouds can be used directly for deliverables conforming to the Ministry of Land, Infrastructure, Transport and Tourism’s as-built management requirements (for example, electronic submissions for national projects). When precision verification is necessary, you can scan existing site control points and compare to confirm and correct errors. Even so, point cloud utilization dramatically simplifies procedures relative to traditional methods, enabling high-quality as-built management with much less complexity.

Expanding into overlaying drawings and position verification using AR (augmented reality)

LRTK LiDAR also supports AR (augmented reality) display using acquired point clouds and design data. With AR technology, digital drawings and 3D models can be overlaid on live site imagery to intuitively visualize design and construction plans onsite.

For example, if you load a model of the planned completed structure or design terrain data into the smartphone, you can display that 3D model in AR at its designated location through the camera. Since LRTK LiDAR assigns global coordinates to point clouds during acquisition, models can be placed at the correct coordinate positions, enabling AR projections that do not shift out of place. As workers move around the site, AR objects remain in the correct positions, helping stakeholders share the construction completion image and check for discrepancies with the design. As a “site visualization” tool, it can also be used in meetings with clients to show the expected finished appearance on the spot.

AR also contributes to speeding up stakeout and marking tasks. In LRTK systems, you can place virtual “AR stakes” (visual markers) at arbitrary coordinate positions. For example, by inputting design control points or stakeout positions into the app, virtual stakes appear on the screen at those locations. The worker can follow on-screen guide arrows to move to the target; even in areas where GPS reception is poor or where physical markers cannot be placed (steep slopes, over water, etc.), the system can identify target points with centimeter-level precision. Tasks that previously required surveying instruments to determine coordinates for staking can now be performed intuitively using AR stake displays, enabling faster and more labor-saving as-built position checks.

Additionally, visualizing previously acquired buried utility point clouds in AR is an effective use case. For instance, if you previously scanned the positions of buried pipes and cables, you can display those data in AR during a subsequent excavation to easily avoid them. Showing invisible underground elements in a translucent overlay reduces the risk of accidental damage and enhances safety.

By leveraging LRTK LiDAR’s AR features in these ways, you can realize new workflows that seamlessly link site conditions and design, including drawing-to-site reconciliation, sharing expected completion visuals, and guiding surveying tasks. AR enables intuitive position verification and allows the whole crew to share spatial images that flat drawings or stakes alone could not convey.

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

The emergence of LRTK LiDAR has broadened the range of surveying options available on site. Below is a comparison of representative conventional methods (drone photogrammetry, terrestrial 3D laser scanners, total station surveying, etc.) and smartphone LiDAR, and a summary of their strengths and how to choose between them.

• Drone photogrammetry: For large areas (several hectares or more) or bulk aerial measurements, drone-based photogrammetry is effective. It can quickly generate an overhead terrain model and is suitable for large-scale earthworks or forest surveys. However, it is affected by weather and flight permission constraints and is difficult to use in urban areas or indoors. Achieving high accuracy also requires placing ground control points (GCPs) and performing post-processing. Smartphone LiDAR is limited by the operator’s walking range but can measure locally regardless of weather or location, and can capture fine details. For large projects, an effective approach is to capture the overall site with a drone and supplement details and occluded areas with smartphone LiDAR.

• Terrestrial 3D laser scanners: Tripod-mounted laser scanners are powerful devices that can measure accurately hundreds of meters away. They remain a strong option for precise recording of entire structures or detailed measurements inside tunnels and plants. However, the equipment is large and expensive, and operation and data processing require specialist skills. Post-processing to merge multiple scans is also necessary. In contrast, smartphone LiDAR is a nimble tool focused on routine small-scale measurements. While its accuracy (~2 cm) is behind that of laser scanners (on the order of a few millimeters), smartphone LiDAR provides real-time onsite results and automates data merging and coordinate calculations. Where sufficient accuracy and rapid response are prioritized, smartphone LiDAR excels; for millimeter-level requirements or long-range measurements, traditional scanners remain more suitable. Use both according to needs.

• Total station (TS) surveying: TS measures point-by-point with prisms or reflectors to achieve high precision (millimeter-level) and remains indispensable for setting out structures, foundation positioning, and deformation monitoring. However, obtaining surface-wide 3D shapes with TS requires measuring many points, which takes time. Smartphone LiDAR captures surfaces as point clouds efficiently for broad shape understanding. That said, in GNSS-denied environments like indoors or tunnels, smartphone LiDAR alone cannot obtain absolute coordinates, so you must tie the acquired point cloud to TS or control points afterward. Thus, TS is appropriate for indoor surveys and localized high-precision control, while smartphone LiDAR is preferable for outdoor wide-area 3D capture.

• Handheld SLAM scanners: Recently, handheld 3D scanners using SLAM (simultaneous localization and mapping) have appeared. These devices can create point cloud maps by simply walking indoors or outdoors and are conceptually similar to smartphone LiDAR. However, they are often very expensive and, in many cases, require separate GNSS base stations or targets to georeference the resulting point cloud with absolute coordinates. In contrast, LRTK LiDAR leverages a general-purpose smartphone combined with RTK-GNSS to directly georeference point clouds at lower cost, offering an advantage in obtaining absolute-coordinate point clouds easily.

Considering the above, select and combine methods at the site based on project scale, required accuracy, and surrounding environment. LRTK LiDAR is positioned as a new option that achieves both overwhelming efficiency and sufficient accuracy for daily surveying and small- to medium-scale sites. Meanwhile, retaining the flexibility to combine conventional technologies for ultra-high precision or special conditions remains important. By leveraging each method’s advantages and using them appropriately, you can maximize surveying productivity across projects.

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

Here we outline the overall measurement workflow using LRTK LiDAR. With smartphones, GNSS/LiDAR devices, and cloud services integrated into LRTK, surveying on site through data utilization can be seamlessly connected.

1. Preparation and setup: At the site, attach the LRTK receiver to the LiDAR-equipped smartphone and launch the dedicated app. Even in first-time use, complex settings are not required; just ensure you can receive RTK correction information (reference station data via the Internet or satellite-augmentation signals) to prepare for positioning. (LRTK also supports the Quasi-Zenith Satellite System QZSS’s CLAS augmentation signals in Japan, enabling cm level accuracy (half-inch accuracy) positioning even in mountainous areas out of mobile network coverage.) If necessary, mount the device on a monopod or pole and input the height offset for more stable positioning.

2. Begin positioning and scanning: Select survey mode in the app and start measurement. To acquire a point cloud, press the “Start Scan” button and walk around the area to be measured with the smartphone. The LiDAR sensor captures the surrounding shape while GNSS continuously logs the user’s position. The app visualizes the point cloud in real time so you can confirm coverage and density as you proceed. You can pause and resume as needed, and re-scan immediately if you notice gaps.

3. Save data and sync to the cloud: After finishing the scan, tap “Save” in the app. The acquired point cloud and coordinate data are saved on the smartphone and metadata (time, GNSS accuracy, notes, etc.) are automatically attached. With one tap, you can sync to the cloud, uploading data before leaving the site. Once synchronized, the data can be viewed and shared from an office PC or other stakeholders’ devices via a web browser.

4. Data utilization and analysis: Point cloud data uploaded to the cloud can be analyzed and utilized extensively on LRTK’s web platform. For example, you can inspect the current 3D model in a point cloud viewer, measure distances and elevation differences between arbitrary points, and calculate areas and volumes in the browser. You can also upload design drawings or BIM models and overlay them with the point cloud to analyze as-built deviations. The platform can automatically generate cross-sections from the point cloud for CAD export, and display geotagged photos on the point cloud—providing strong integration of field measurement data with design and reporting workflows.

5. Reporting and sharing: After analysis, compile results such as cross-sections, heatmap images, and earthwork calculation tables into reports. Because LRTK cloud data are always stored as the latest version, stakeholders can view the most up-to-date survey results via shared links. No special software installation or high-performance PC is required—anyone with a web browser can interact with 3D point clouds—making information sharing with clients and subcontractors smooth.

Thus, the workflow combining LRTK and smartphone LiDAR connects data acquisition to processing and sharing in a fully digital chain. Field measurements are uploaded to the cloud immediately and used directly for analysis and reporting, greatly reducing the cumbersome data transfer and post-processing steps between the site and office. As a result, the cycle from surveying to construction management shortens and on-site digital transformation (DX) is strongly promoted.

The 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 report integration. Traditionally, sharing survey data among stakeholders required compiling CAD drawings or PDF reports for distribution. With LRTK, measurement data are centrally managed in the cloud and can be efficiently utilized as follows.

● Instant review via cloud sharing: Point clouds uploaded from the site are instantly viewable from the office or other locations via the Internet. A supervisor or client located remotely can review 3D data immediately after the field staff completes a scan. This real-time sharing accelerates decision-making by allowing checks and approvals without waiting for formal deliverables. Because sharing is done via a web browser, recipients do not need specialized software—simply providing a URL allows anyone to interactively view and inspect the point cloud on a PC or tablet.

● Export to standard formats: Cloud point cloud data and measurement results can be exported to familiar formats as needed. Point clouds can be exported as LAS or PLY for detailed analysis in existing point cloud tools, or as DXF planar and cross-section drawings for CAD import. Survey coordinate lists can be exported as CSV or SIMA formats for electronic submission. This balance of in-system convenience and compatibility with external tools enables smooth integration into internal and external workflows.

● Use in reports: Heatmap images, cross-sections, and measurement tables generated on the cloud can be directly used in as-built reports and internal documents. For example, inserting a point-cloud-based as-built heatmap into a report provides a clear visual of construction accuracy. Cross-sections and numeric tables can be pasted in from automatically calculated data, reducing manual transcription errors and drafting time. Less time spent on report preparation frees staff to focus on higher-value analyses and construction planning.

In this way, LRTK LiDAR data are digitally linked from acquisition to processing, sharing, and reporting. Faster site-to-office communication improves not only the accuracy of survey results but also the speed and quality of reporting, which is highly valuable in modern construction projects.

FAQ

Q. What level of accuracy can be achieved with LRTK LiDAR? A. Under typical conditions, horizontal positioning achieves about ±1–2 cm (±0.4–0.8 in), and vertical accuracy is about ±2–3 cm (±0.8–1.2 in). The relative accuracy between point clouds (absence of shape distortion) is also kept within about 2 cm (about 0.8 in), which is sufficient for most civil surveying and as-built management tasks. However, GNSS positioning quality depends on satellite reception and the surrounding environment, so it is preferable to measure in areas with good sky visibility to ensure accuracy.

Q. Which smartphones are supported? Do I need a dedicated device? A. LRTK LiDAR runs on iPhones or iPads equipped with a LiDAR sensor. Specifically, compatible devices include Apple’s LiDAR-equipped models such as iPhone 12 Pro and later or iPad Pro models from 2020 onward. These Pro models have built-in LiDAR units that the app can control directly to acquire point clouds. As of 2025 there are no known Android implementations, so iOS devices with LiDAR are the supported devices. For high-precision positioning, a separate LRTK GNSS receiver is required, which is provided as a small dedicated device that simply attaches to the smartphone.

Q. Can it be used where cellular service is unavailable? A. Yes. LRTK supports the CLAS correction information broadcast from the Quasi-Zenith Satellite “Michibiki,” enabling positioning even where Internet connectivity is unavailable. If the LRTK receiver is equipped with the dedicated antenna in advance, it can receive satellite-based corrections and maintain cm level accuracy (half-inch accuracy) in mountainous areas or remote islands out of mobile network coverage. However, GNSS signals cannot be received inside tunnels or similar environments, so alternative approaches described elsewhere are required for such locations.

Q. How long does point cloud measurement take, and what range can be measured? A. Measurement time and coverage depend on site size and complexity, but small structures can be scanned in tens of seconds to a few minutes. For instance, scanning a slope with an elevation difference of about 30 m (98.4 ft) from end to end can be completed in roughly one minute. The effective range of the point cloud is generally limited to the LiDAR sensor’s line of sight (a radius of a few meters), but by moving the operator you can capture data for somewhat more distant targets (tens of meters away). LRTK also uses image analysis, and field results have shown point cloud capture of targets up to approximately 50–60 m (164.0–196.9 ft) away. Note that point density becomes sparser at longer distances, so for areas requiring high precision it is recommended to scan from closer range.

Q. Can LRTK LiDAR be used indoors or in tunnels? A. Partially, but with caveats. The LiDAR sensor itself works indoors and in tunnels, so it can capture surrounding shapes as point clouds. However, since GNSS satellite signals are unavailable in these environments, absolute coordinates cannot be assigned in real time; the acquired point cloud will be in a relative (local) coordinate system. Later tying the cloud to outdoor control points is required to georeference the whole dataset. Relying solely on IMU-based dead reckoning during long indoor scans can introduce gradual distortion in the point cloud. If high-precision indoor measurements are needed, we recommend supplementing LRTK’s simple surveys with total station checks at key locations.

Q. Will conventional surveying instruments become unnecessary? A. LRTK LiDAR is versatile and convenient but does not completely replace all traditional instruments. For example, millimeter-level precision required in foundation work still benefits from high-precision total station surveys, and very large-area surveys covering tens of hectares are more efficiently done with drones or aerial photogrammetry. Also, measuring in environments where LRTK has limitations—such as indoor or underground spaces—will still require conventional methods or other 3D scanning technologies. That said, for everyday civil surveying and as-built measurements on small- to medium-scale sites, there are many scenarios where LRTK LiDAR can “complete everything with this one device.” By combining LRTK with traditional tools where appropriate, you can significantly reduce labor and improve efficiency in most surveying tasks.