Terrain surveying is an essential process in infrastructure development and construction planning. Traditionally, surveying was conducted by a two-person team using total stations (TS) or levels, but in recent years, the use of point cloud data through 3D scanning technology has become a major trend. Total stations, which became widespread in the 1980s, are surveying instruments capable of measuring angles and distances with high precision in a single device, and they have been used in various fields such as terrain surveying and site layout for construction. On the other hand, with the promotion of i-Construction (ICT construction) by the Ministry of Land, Infrastructure, Transport and Tourism, 3D surveying using sensors mounted on drones and mobile devices is becoming more prevalent on construction sites.

In this article, we will compare total stations with point cloud data surveying and explain the benefits of utilizing point cloud data in various aspects of construction management, as-built management, and planning/design.

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Total Station vs. Point Cloud Surveying

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Differences in Accuracy and Measurement Methods: Total stations (TS) are specialized in measuring specific points one by one. They direct light waves at targets such as prisms and calculate distances and angles based on the reflected signals to determine coordinates. On the other hand, point cloud surveying using laser scanners or photogrammetry captures a large number of measurement points over a wide area in a short amount of time. While a total station measures "points," point cloud surveying captures a "surface" all at once. This difference allows for the non-contact measurement of complex terrains and large structures that were previously difficult to measure with traditional methods.

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Comparison of Efficiency and Speed: One of the main advantages of point cloud data surveying is the significant improvement in work efficiency. For example, in terrain surveying for a land development area of several hectares, work that would typically take about 3 days using a total station can be completed in about 2 days with a ground-based laser scanner, or in just half a day using UAV (drone) photogrammetry. In fact, a comparison experiment using laser scanner-equipped drones showed that surveying was completed in 1/6th of the time compared to traditional methods, reducing the overall work time by more than half. From an efficiency standpoint, laser scanners have a clear advantage, contributing significantly to reduced labor costs and shortened schedules.

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Cost Comparison: When considering surveying costs, it is important to take both equipment investment and labor costs into account. High-performance 3D laser scanners and drone surveying equipment require significant initial investment, but they can acquire large-scale data in a short period, offering cost benefits through reduced overall work volume. On the other hand, total stations are relatively low-cost and can make use of existing assets, making them still effective for small-scale measurements or known point surveys. Choosing the appropriate method is crucial for balancing accuracy and cost.

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Accuracy Comparison: Total stations offer high measurement accuracy for each point, obtaining angles and distances with millimeter-level precision. Point cloud data, in recent years, has also seen improvements in accuracy due to advancements in laser scanner performance and photogrammetry algorithms, with cases achieving accuracy from several centimeters to millimeters. However, to ensure measurement accuracy, proper reference point calibration and post-processing are essential. Hybrid methods, which use reference points obtained by total stations to assign position coordinates to point clouds, are also common. This allows for high-precision 3D measurements even in areas where satellite positioning cannot be used.

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Weaknesses of Each Method: Point cloud surveying also has its drawbacks. In the case of laser scanners, objects such as black surfaces, glossy materials, and glass tend to poorly reflect laser light, resulting in missing data (such as noise or holes). Additionally, while point clouds capture large areas at once, they are not suitable for measuring a single specific point directly. Blind spots or areas that cannot be seen, such as behind obstacles, cannot be captured, so total stations (TS) may be used to complement the measurement of fine details. On the other hand, total stations require manual effort to gather data points, limiting the number of measurement points, making it difficult to get an overall view of the site. Without photos or notes, it can also be challenging to determine "where measurements were taken" later on. Therefore, in practice, it is ideal to use both methods effectively: quickly capturing wide areas with point clouds and performing precise checks at key locations with total stations, creating a hybrid approach.

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Utilization of Point Cloud Data

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In Construction Management

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In construction management, it is essential to monitor the progress and accuracy of the work in real time. By utilizing point cloud data, it is possible to regularly capture 3D progress records of the entire site and visualize and compare the work completed at each stage. For example, by scanning the site weekly with drones or ground-based laser scanners, point cloud data can be overlaid over time to instantly show "which areas are completed and which are not yet started." This allows for the objective sharing of progress, which would be difficult to grasp through verbal communication or photos alone, and supports decision-making for revising construction plans or arranging materials.

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Additionally, by overlaying point cloud data with design BIM models, it becomes possible to verify on-site whether the construction is proceeding according to the design in terms of position and shape. Software such as FARO's BuildIT allows for the comparison of scanned site point clouds with design data, displaying discrepancies in a heatmap with color-coded shifts. By scanning immediately after steel framing or concrete pouring, and checking the differences from the design model, any errors or construction mistakes can be promptly identified and corrected. Compared to the traditional method of checking measurements at specific points using a total station (TS), this approach offers significantly faster and more comprehensive construction accuracy management.

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Moreover, the use of point cloud data is also effective for safety management. Dangerous areas and high places, which are inaccessible to people, can be scanned remotely, reducing the risk to surveying workers. For instance, by using remote-controlled robots or drones to check for slope deformations or measure inside tunnels, necessary data can be collected without workers entering hazardous zones. As demonstrated, point cloud data contributes to visualizing progress, ensuring construction accuracy, and improving safety in construction management.

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Utilization in As-Built Management

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As-built management (as-built measurement) is the process of verifying whether the completed structure or terrain matches the design dimensions and shape. Traditionally, the method involved using total stations or tape measures to measure representative points and comparing them with the dimensions on the drawings. However, with point cloud data, the entire completed structure can be scanned and captured, and compared seamlessly with the design 3D data or reference cross-sections. For example, when checking the as-built condition of roads or dam embankments, displaying the difference between the completed point cloud and the design model as a color map allows for an instant understanding of any discrepancies in elevation or thickness. Point clouds can also be used to assess the shape of curved or complex structures (such as spherical tanks), which are difficult to measure by hand, allowing for a comprehensive evaluation of the entire surface.

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Specifically, in point cloud processing software, the design surface and as-built point clouds can be overlaid, with areas exceeding the allowable error color-coded for easy identification, or cross-sectional views can be automatically generated. This greatly improves the efficiency of as-built inspections. Previously, points measured on-site were compared one by one with the drawings to make pass/fail decisions. Now, verification can be done in a surface and 3D manner on the software, reducing oversight and improving the quality management standards. Furthermore, the use of heatmaps to visually highlight problematic areas makes it easier to explain to clients or inspectors, providing clear and effective documentation.

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The use of point clouds in as-built management is also powerful in volume management. In excavation and embankment work, the comparison of pre- and post-construction terrain point cloud data automates the calculation of the volume of work completed (soil volume). Without the need for manual calculations like the average cross-section method, embankment and excavation volumes can be accurately determined from the differences between point clouds, speeding up volume management and the creation of as-built drawings. In this way, point cloud data contributes to improving the efficiency and reliability of quality inspections in as-built management.

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Utilization in Planning and Design

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Point cloud data serves as a valuable information foundation during the planning and design phases as well. First, by acquiring point cloud data of the existing terrain and surrounding structures before construction begins, interference checks and consistency verifications with the design model become much easier. For example, in renovation projects, when evaluating the integration with existing structures, overlaying the point cloud scanned on-site with the 3D model of the new structure can help identify potential conflicts or design issues before construction begins. This allows for the prevention of design errors and the reduction of rework after construction.

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A major advantage of using point cloud data is the ability to quickly respond to design changes. If design adjustments are necessary during construction due to changes in ground conditions, the latest point cloud data can be used to immediately simulate the redesigned model. By experimenting with the new structure layout on the point cloud data and predicting the as-built conditions, the impact of design changes can be evaluated swiftly. This is a significant efficiency improvement compared to the traditional process of re-surveying and redrawing the plans for any changes.

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Furthermore, in urban and civil planning, detailed 3D terrain models can be created from point cloud data and used for route planning and land development planning. On the digital terrain model created from the point cloud, it is possible to examine road alignments or simulate the layout of residential complexes, refining the plans in a virtual environment. In the context of the increasingly popular concept of digital twins, point cloud data functions as a precise replica of the real-world environment, enabling consistent use from planning to maintenance. For example, in post-construction maintenance, point cloud data from regular inspections can be accumulated to track the aging of structures, and in disaster situations, comparing point clouds from before and after an event can quickly calculate the extent of damage.

As shown, using point cloud data in the planning and design phases leads to enhanced site understanding and greater flexibility in the design process, resulting in safer and more optimized designs and construction.
 

Specific Use Cases

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As concrete examples of point cloud data utilization, here are several project areas.

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• Road Construction: In new road construction and improvement projects, the use of drones for photogrammetry to acquire point cloud data of the surrounding terrain before construction is becoming increasingly common as a basis for design. During construction, the subgrade and embankments are scanned and compared with the design model, allowing for continuous checks to ensure the required height and slope are maintained. For as-built management, after paving is completed, the road surface is scanned, and its flatness and cross slope are evaluated using a heatmap. This approach allows for comprehensive quality verification across long stretches of road without missing any sections.

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• Dam and Flood Control Projects: In dam construction, large-scale earthworks, including excavation and concrete pouring, are involved. Point cloud measurements provide a 3D view of excavation and embankment shapes, allowing for continuous comparison with design cross-sections. This enables early correction of excavation excesses or shortages and deformation in concrete pouring. In river improvement projects, point clouds of the riverbed and embankments are scanned before construction, which helps in comparing with planned flood levels and verifying as-built conditions. Since point cloud data allows for precise volume calculations, managing the order of embankment materials and progress payments becomes smoother.

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• Urban Development and Land Development: In urban redevelopment and land development projects, point cloud data of large areas, including existing buildings and terrain, is acquired and used in design considerations. For example, in a building construction project, acquiring the location of surrounding buildings via point cloud data can aid in crane placement planning and temporary enclosure planning. In urban areas, in addition to aerial photogrammetry, using ground-based LiDAR or mobile mapping to capture building facades creates a 360-degree, obstruction-free model of the current state. This allows for designs that harmonize with the surrounding environment and the use of landscape simulations for public consultations during the planning phase, using point cloud data as a tool for information sharing.

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• Tunnels and Bridges: In tunnel construction, the shape of the excavation surface is scanned after each advance, and the differences from the design cross-section are checked, allowing for immediate identification of over-excavation or under-excavation. In bridge construction, point clouds are used to measure the as-built conditions of piers and beams, verifying that they are within the acceptable range of design height and tilt. In particular, for large bridges, an attempt has been made to scan the entire bridge and compare it with the BIM model to evaluate the as-built conditions of all elements in one go. Additionally, point cloud data is also applied in post-construction maintenance, with research underway to detect cracks and displacements from point clouds scanned during regular inspections.

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As seen in these examples, the use of point cloud data is advancing in various civil engineering and construction fields, such as roads, rivers, dams, and urban development, contributing to improved efficiency and quality on-site. In fact, in Yamanashi Prefecture, the point cloud processing system has been deployed at all construction offices in the area. As a result, the extraction of cross-sections from terrain models and as-built management has been streamlined, significantly improving the safety and productivity of road management and river construction projects.

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Additionally, in a tunnel construction project collaborated on by a major construction company, LiDAR-equipped quadruped robots and drones were used to measure both inside and outside the tunnel. The acquired point cloud data was transmitted in real time to remote locations. This system enabled the immediate verification of construction progress and as-built conditions from the headquarters, making remote construction management a reality. Point cloud data is thus enabling new construction management methods, such as large-scale measurements and remote monitoring.

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Introduction to LRTK
(Latest Technology for Point Cloud Measurement)

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Finally, we will discuss LRTK, a groundbreaking solution in point cloud measurement that is gaining attention. LRTK (developed by Lefixea) is a series of revolutionary surveying devices that combine GNSS-RTK (Real-Time Kinematic) positioning technology with high-resolution 3D scanning capabilities. Here, we will introduce some of its key features.

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• Easy High-Precision Surveying with iPhone + LiDAR: The product known as LRTK Phone is a compact RTK-GNSS receiver that attaches to iPhones and iPads, transforming the smartphone into a versatile surveying device with centimeter-level precision. By integrating the iPhone’s built-in LiDAR scanner with RTK positioning, mobile point cloud measurement, which typically has an error of several meters on its own, is significantly improved in accuracy. This allows for high-precision point cloud data acquisition on-site with just a smartphone, enabling the immediate measurement of distances and elevation differences between any two points. Through a dedicated app and cloud service, the data can be shared instantly, and comparisons with survey drawings or design plans can be done on-site, enabling real-time surveying and inspection with just one device per person. The fact that 3D surveying, which traditionally required large equipment and specialized operators, can now be done with a palm-sized device will directly contribute to improved site productivity.

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• High-Precision 3D Scanning Without Markers: The LRTK LiDAR is a ground-based laser scanner device that integrates RTK-GNSS. Its strength lies in its ability to automatically assign absolute coordinates (global coordinates) to measurement points simultaneously with the scan, without the need for complex target setup or guiding to known points. By combining centimeter-level positioning via GNSS-RTK and high-density laser scanning, it can capture highly detailed data even up to 200 meters away. Large-scale sites can be covered with just a few setups, and the acquired point cloud can be displayed and reviewed on a smartphone or tablet with millions of points in real time. If any data gaps are detected, rescanning can be done immediately, ensuring efficient and complete measurements.

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• Cloud Integration and Data Sharing: Point cloud data acquired with LRTK is automatically uploaded and centrally managed on the cloud service "L Cloud." Without the need to install dedicated software on a PC, coordinate verification, distance, and slope measurements can be completed via a browser, allowing data to be shared online with stakeholders. The workflow of scanning on-site, sending the data to the cloud, and having the design team verify it in the office can now be done in real time, facilitating smooth collaboration with remote locations. Compared to the days when large point cloud data had to be sent via hard disk, this is a groundbreaking simplification of processes.

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• Integration with Drone Surveying: LRTK technology is highly compatible with drone-based photogrammetry and LiDAR, and when used complementarily, it enables further efficiency gains. For example, in large land development projects, drones can capture a general point cloud of the terrain from the air, while LRTK LiDAR can be used for detailed ground measurements around structures and specific areas. By integrating both point clouds, a high-precision and high-density 3D model, combining aerial overview data and detailed ground data, can be created quickly. In fact, as seen in the tunnel construction example, there are cases where ground-based robot LiDAR and drones are used together, and this multi-platform surveying approach is likely to become mainstream in the future.

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As shown above, LRTK is a solution that enables anyone to easily perform high-precision RTK surveying and 3D scanning, bridging the gap between specialized equipment and mobile devices. The evolution of surveying technologies, represented by keywords such as "point clouds," "RTK," "total stations," and "3D scanning," is steadily transforming the way work is done on construction sites.

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The use of point cloud data in terrain surveying inherits the precision and reliability of total stations while significantly expanding its convenience and expressive capabilities. Point cloud data will continue to spread and will be increasingly powerful in construction management, as-built management, and planning/design across all stages. By referring to the methods and examples discussed in this article, as well as to cutting-edge technologies like LRTK, we encourage you to incorporate 3D point cloud utilization into your own projects. This will undoubtedly improve the efficiency and quality of surveying and management tasks, leading to the creation of new value.