How to Create Point Clouds of Buried Pipes: 7 Steps | From Field Measurement to 3D Drafting

After installing buried pipes such as water and sewage lines, gas pipes, and power cables at a construction site, accurately recording their positions and shapes is extremely important for future maintenance and management.

Traditionally, before backfilling the buried pipes, depths and positions were measured with measuring tapes and surveying instruments and recorded on paper drawings and photographs. However, with this method, because measurement points are limited, the route of the buried pipes could not be fully captured, and relying on people for records created the risk of mistakes or omissions.

One technology attracting attention for solving these issues is recording using point cloud data. A point cloud (often called point cloud data) is a collection of many points obtained by laser measurement, and it is data that densely records surrounding structures and terrain in three dimensions. If you perform a 3D scan and save it as point cloud data before backfilling a pipe to be buried, you can accurately reproduce and check the pipe’s position, depth, and inclination on a computer even after it has been hidden underground. When excavating nearby for other work in the future, a digital 3D model allows anyone to identify the presence of buried assets, greatly reducing the risk of accidentally damaging pipes. In addition, point cloud data contains more information than drawings and records the site as it is, making it useful for future renovation planning and asset management.

So, what specific steps should you take to acquire point clouds of buried pipes on site and ultimately use them as 3D drawings? In this article, we explain the method in seven steps so that even beginners can understand. By leveraging smartphone-mounted LiDAR sensors, drones, terrestrial laser scanners, and high-precision GNSS (RTK) positioning technology, tasks that traditionally took specialist surveyors days can now be performed accurately by anyone in a short time. Now, let’s walk through the concrete workflow from field measurement to data processing and 3D drafting step by step.

Step 1: Planning and Preparation

First, it is important to clearly define the purpose and scope of point cloud measurement for buried pipes. Clarify which infrastructure pipelines (e.g.: potable water pipes, sewer pipes, gas pipelines, electrical conduits, etc.) you want to document and to what level of detail, and how the acquired data will be used (construction records, drawing creation, maintenance management, etc.). Once the objectives are set, select the optimal measurement methods and equipment according to site conditions and accuracy requirements. Methods for acquiring point clouds include mobile (including handheld) or tripod-mounted 3D laser scanners (LiDAR), and photogrammetry using drones (a technique that reconstructs 3D models from aerial images). Each method has strengths and weaknesses, so choose based on the length of the pipeline, installation location (outdoor/indoor, line-of-sight availability), and required accuracy. Also, if reference points or coordinate systems are indicated on existing drawings, confirm them and prepare for later data merging. Consider using GNSS (Global Navigation Satellite System) to achieve high-precision positioning on site. In particular, if you want to record in a public coordinate system, using a network RTK-GNSS service or installing known control points on site will provide accurate coordinates to the measured point clouds.

Prepare measurement equipment and related software at this stage as well. Charge the batteries of laser scanners, smartphones, GNSS receivers, and other devices in advance and verify that they operate normally. If scanning with a smartphone, install dedicated 3D scanning apps and point cloud processing apps and become familiar with their use. If using a drone, create a flight plan and be sure to apply for flight permission from the Ministry of Land, Infrastructure, Transport and Tourism and implement on-site safety measures. If possible, conduct a small-scale test scan before the actual operation to confirm the workflow from equipment settings and data acquisition through to processing. Also consider the surrounding environment (traffic conditions, weather, the need for nighttime lighting, etc.) and make arrangements so that measurement work can be carried out smoothly and safely on site. By conducting the preparation stage carefully, subsequent steps will proceed far more efficiently and the quality of the data will improve.

Step 2: Scan the site with smartphone LiDAR

When preparations are complete, perform a 3D scan around the buried pipe on site to obtain point cloud data. If you have a smartphone or tablet equipped with a LiDAR sensor, you can use it as a handheld 3D laser scanner. Launch the dedicated scanning app and, while slowly walking around the trench (excavation trench) or pit where the buried pipe is exposed, point the device’s camera and sensors and capture images. Move the smartphone up, down, left, and right to scan from various angles so the entire pipe is visible. In addition to the pipe surface, include the surrounding terrain and structures (for example manholes, road surfaces, building foundation elements, etc.) in the point cloud, as these will provide reference points when performing alignment later.

When performing smartphone LiDAR measurements, aim to operate slowly and steadily, avoiding abrupt swings and fast movements. Because the sensor is performing self-position estimation (SLAM) while capturing surrounding geometry, excessively fast motion or sudden turns in confined spaces can cause distortion or dropouts in the data. When scanning a large area at once, it can be effective to divide the scan into multiple point cloud data sets as appropriate. For example, for a long pipeline, complete the scan and save the data for each suitable section before moving to the next. For each section’s scan, leaving a small overlapping area (overlap) will make it easier to merge them later.

The effective range of smartphone LiDAR is only a few meters (a few ft), so take measurements as close to the subject as possible. For deep trenches, you can consider attaching the smartphone to the end of a pole or rod and lowering it, or descending a slope to shoot at close range (take adequate safety precautions). Because LiDAR uses laser light, it can measure even when the surroundings are somewhat dark, but since the camera image is also used, a condition with moderate brightness rather than extreme darkness is ideal. If the point cloud is displayed on the smartphone screen in real time during capture, proceed while checking that nothing is overlooked. If you notice any missed areas, it's a good idea to back up a little and perform an additional scan on the spot.

If 3D measurements at the site can be completed using only a smartphone like this, detailed point cloud data can be obtained in a short time. Although accuracy and resolution are somewhat inferior to those of dedicated equipment, the data contain sufficient information to understand pipe routing, gradients, and burial depth. Most importantly, the ease of measuring without special skills is a major advantage, allowing site personnel to record information on the spot. Point cloud data acquired with smartphone LiDAR can also become useful material in terms of accuracy by being integrated with other data and having position corrections applied in later processes.

Step 3: Acquiring Wide-Area Point Clouds Using Drone Aerial Photography

Depending on site conditions, aerial measurements using drones can also be effective. To capture extensive terrain and the overall picture that handheld smartphone scans alone cannot fully cover, photogrammetry using small unmanned aerial vehicles (drones) is used to generate point cloud data. A high-resolution camera is mounted on the drone, which automatically flies along a planned route over the locations of buried pipe installation while capturing numerous photographs of the ground surface. When shooting, it is important to ensure sufficient overlap so that there is 60–80% or more overlap between images, and to include oblique-angle photographs as well to capture the subject three-dimensionally. The multiple acquired image datasets are converted into a point cloud model by photogrammetry (photogrammetric software) in the data processing workflow described below.

The advantage of drone aerial imaging is that it can quickly record wide-ranging conditions that cannot be observed from the ground. Even on long pipeline construction sites, just a few minutes of flight from above can capture the conditions along the entire section as data. For example, in water and sewer pipeline work laid along a road, acquiring an aerial point cloud of the entire excavated trench and the surrounding road and building layout yields a 3D map that allows you to verify the positional relationships of the pipes from an overhead perspective. Combining detailed data obtained with smartphone LiDAR and wide-area data from drones produces a point cloud model that provides both local precision and an overall bird’s-eye view, aiding subsequent drafting and consistency checks.

To obtain high-precision aerial photography results, there are several points to note. First, if possible, install ground control points (targets) on the ground and measure their exact coordinates. By placing these targets so they appear in the aerial photographs, you can correct scale and position when generating point clouds with photogrammetry software, thereby improving absolute accuracy. Recently there are drone models equipped with RTK-GNSS that can capture images with real-time positioning augmentation, but even if you do not have such high-end equipment, accuracy can be sufficiently corrected using ground targets. Also, pay attention to vibration and sudden altitude changes during flight and aim for stable flight. In strong winds, captured images can blur and reduce analysis accuracy, so consider weather conditions. Observe legal rules and safety measures, and conduct aerial photography with all necessary precautions to ensure no harm comes to third parties.

Point cloud data captured by drones (or point clouds generated by the photogrammetry described below) primarily and accurately reflect the shape of the ground surface and the arrangement of aboveground objects. However, underground pipelines themselves are not directly captured, so the detailed geometry of buried pipes needs to be supplemented by the aforementioned ground measurement data (smartphone or laser scanner). By combining aerial point clouds and ground point clouds, an integrated 3D model that unifies aboveground and underground elements is completed.

Step 4: High-precision measurement using a terrestrial laser scanner

There is also a method that uses a dedicated ground-based 3D laser scanner instead of a smartphone. Tripod-mounted laser scanners are equipped with higher-power lasers and more precise rotation mechanisms than smartphones, and can acquire point clouds up to several tens of meters (tens of ft) away with millimeter-level precision (≈0.04 in). This type of equipment is used when more exact records are required or when you want to measure a large area at high density.

When using a ground-based laser scanner, the first step is to select the locations to install the scanner on site. It is common to set it up at multiple points, such as locations where you can view the entire trench carrying the buried pipes and locations where complex piping sections (such as fittings and junctions) can be captured at close range. The scanner can scan 360 degrees around the installed point at once, but it cannot acquire areas that are hidden in the shadow of the terrain and therefore become blind spots. For that reason, scans are repeated several times while appropriately shifting the position to ensure there are no gaps or omissions in the data.

Before starting each scan, level the equipment horizontally and vertically and set the measurement conditions (such as resolution, range, and whether HDR capture is enabled). A scan takes several minutes to a dozen or so minutes per location. Because rain or dusty environments can cause the laser to scatter and lead to measurement errors, determine when to perform the scan by taking weather and site conditions into account. During measurements, take care to prevent site personnel or machinery from crossing the laser lines, and it is also important to restrict access with safety barriers or similar.

To accurately merge multiple scan datasets later, it is effective to take a few measures on site. One is to place registration targets (spherical markers or circular plate markers, etc.) near each scan position. By positioning these targets so they are visible from other scan positions, they become common reference points that link different point clouds. If you survey the exact positions of the targets in advance with GNSS or a total station and assign coordinates, it becomes easy to give the point clouds absolute coordinates during later integration. Also, if you deliberately arrange the setup so that permanent surrounding structures (building corners, paved surfaces, etc.) appear in multiple scans, you can align point clouds by matching those shapes. After completing each measurement on site, check the data on a laptop or tablet to confirm that the required area has been fully captured. If anything was missed, place the scanner additionally on the spot and perform supplementary measurements.

By using terrestrial laser scanners, you can record the topography and structures around buried pipelines in high detail. Not only the pipe itself, but also the slope of surrounding road surfaces and positional relationships with adjacent existing structures can be captured at millimeter-level (mm (0.04 in)), so the accuracy of as-built drawings improves dramatically. However, because the equipment is large and expensive, it may be sufficient to use it selectively at specific spots as needed. Recently, high-precision mobile laser scanners (e.g., handheld or vehicle-mounted) have also appeared, making measurements that balance mobility and accuracy increasingly possible; in any case, point cloud data acquired on site are integrated and analyzed in subsequent processes to turn them into valuable information.

Step 5: Measurement of Control Points and Coordinate Acquisition Using GNSS Positioning

To assign accurate positional information (geodetic coordinates) to point cloud data collected on site, the coordinates of control points are measured using high-precision GNSS positioning. By using a GNSS receiver that supports RTK (Real-Time Kinematic), it is possible to obtain high-precision latitude, longitude, and height for any point on the ground with errors on the order of a few centimeters (about 1–2 in). For point cloud measurement of buried pipes, select several points such as the start and end points of the piping, bend points, and characteristic points around the trench (for example, the rim of manholes or corners of road curbs), and observe those locations with GNSS to obtain coordinates. If necessary, you may also observe markers installed in advance (targets placed during scanner measurement). The important thing is to survey on-site the characteristic points that can be referenced during subsequent point cloud processing.

To perform RTK-GNSS measurements, set the pole with the GNSS receiver vertically at the survey point and conduct measurements for several tens of seconds to about one minute while ensuring a sufficient number of satellites are in view. The receiver, acting as a rover, obtains high-accuracy solutions by receiving correction information from reference stations provided via a network (e.g., Ntrip) in real time, or by communicating wirelessly with a locally installed base station. During measurement, check the receiver’s status and confirm that RTK has been resolved to a “fixed” solution (Fix). Accuracy decreases in locations with poor satellite reception, such as between buildings or under trees, so it is desirable to observe in as open a location as possible. In environments where GNSS absolutely cannot be used, you can obtain coordinates by alternative means—such as performing relative measurements from known points with a total station—and then tie those coordinates to the point cloud data.

The multiple reference point coordinates obtained in this way later serve as a reference when georeferencing (position-aligning) point clouds during data processing. For example, if features corresponding to GNSS-measured known points appear on a point cloud acquired with a smartphone or a laser scanner, assigning accurate coordinate values to those points allows the entire point cloud to be aligned to the survey coordinate system. Similarly, point cloud models generated from aerial photographs can be position-corrected using ground-surveyed reference points. Recently, small RTK-GNSS receivers that can be attached to smartphones have become available, and methods that assign high-precision positions in real time while scanning with a smartphone are becoming practical. This means that, without having to perform a separate alignment to reference points after data collection, it is becoming possible to assign coordinates in the World Geodetic System to the point cloud on site at the time of acquisition.

Step 6: Merging (Integration) and Editing of Point Cloud Data

Multiple point cloud datasets acquired on site are integrated within dedicated point cloud processing software and combined into a single coordinate system. Point clouds obtained by smartphone LiDAR, point clouds generated from drone photos, and point clouds from terrestrial laser scanners—data recorded in separate coordinate frames—are aligned to a common reference. There are several methods for integration, but basically it is achieved by matching points that represent the same locations in overlapping areas. If calibration targets placed on site are visible, designating them in each point cloud and aligning them to the same point allows for high-precision merging. Additionally, if surrounding structures (for example building facades or road surfaces) are commonly included in multiple point clouds, the software can automatically match shape patterns and perform the alignment. Furthermore, by inputting the coordinate values of control points obtained in Step 5 and indicating the corresponding points on the point cloud, the entire dataset can be transformed into real-world survey coordinates. For example, if you provide the coordinates of a manhole cover measured with GNSS to a pipe point cloud scanned with a smartphone, that single point is used as an anchor, pulling the other data in and correcting the offsets.

When multiple datasets are integrated to create an overall 3D point cloud model, the next step is to organize and edit that data. Delete any unnecessary or noisy points, and check that areas with missing data are supplemented by other datasets. In particular, point clouds from drone photogrammetry can contain unnatural outliers (erroneous points) along object edges or in strongly reflective areas, so filter processing should be used to remove such noise. With terrestrial laser scan point clouds, if temporary objects such as vehicles or workers were captured, delete the corresponding point cloud regions. In some cases, separating (classifying) the point clouds into layers for surrounding terrain and for piping can make subsequent drafting work more efficient. For example, if you separate the point clouds of the ground surface and road structures from the point clouds of buried pipes (pipes exposed in excavation), each can be handled as a separate layer and thus be easier to process.

Adjusting data volume is also a key point in the editing process. Highly detailed point clouds have large file sizes and are difficult to handle, so appropriate thinning (sampling) is performed to reduce the amount of data. However, thinning too coarsely can make the pipe diameter and position unclear, so it is kept to a level that does not compromise the characteristics of the original data. The integrated and organized point cloud data contains a vast amount of information about the site's buried pipes. Next, we proceed to the step of creating practical drawings and models from this point cloud.

Step 7: Creating 3D Drawings from Point Clouds and Sharing Information

Based on integrated and organized point cloud data, we create the final 3D drawings and models. The point cloud is loaded into dedicated CAD or point-cloud processing software, and the positions and shapes of buried pipes are drawn onto the drawings. For example, by tracing a polyline (line segment) along the pipe centerline on the point cloud, you can accurately plot the piping route on a plan view. Also, because depth information is included in the point cloud, it is easy to create longitudinal sections (profiles) to show pipe gradients and depths. By extracting cross-sections from the point cloud at arbitrary locations and drawing the ground surface and the pipe cross-sectional shapes on those sections, you can produce materials that intuitively show the pipes’ burial depths and vertical relationships.

In creating 3D drawings, we will consider, as necessary, generating 3D models from point clouds using reverse engineering. For piping, pipe-shaped objects that match the point cloud geometry are placed and modeled with appropriate diameters and curvatures. Surrounding structures (for example, manholes and access ports) should also be modeled to the specified dimensions while referencing the point cloud, producing 3D data that will be useful for future design changes. The completed 3D models and drawings are shared among stakeholders and submitted to the client as deliverables (as-built drawings).

Moreover, the point cloud data itself is preserved and utilized as an important asset. If uploaded to cloud storage or an internal server, even large-volume 3D data can be stored securely, and anyone can access it to view or measure it when needed. When the site is excavated again for later construction, referring to this point cloud data allows you to determine in advance where pipes are buried underground.

In recent years, by combining it with AR technology on tablets and smartphones, it has become possible to overlay 3D models of buried pipes on the live camera view on site. For example, even after construction when only the road surface is visible, holding a tablet at the site will display the underground pipelines on the screen, visualizing buried objects.

By utilizing such digital 3D models created from point clouds, you can greatly contribute to streamlining maintenance work and preventing accidental excavations.

Through the above processes, the entire sequence of work—from on-site measurement to data processing and 3D drafting—is completed. Management of buried pipes, which traditionally relied on paper drawings and experience, can see dramatic improvements in accuracy and efficiency by using 3D point clouds and digital technologies. Finally, let us touch on solutions that further simplify this series of tasks.

Summary

I explained the seven steps for converting buried pipes into point clouds and creating 3D drawings. By following these procedures, you can digitally record underground piping with high accuracy and preserve valuable 3D data assets that can be used over the long term. In the maintenance and management of infrastructure pipelines such as water, gas, and electricity, aspects that previously relied on craftsmen’s experience can be objectively understood by anyone through digital point clouds. By referring to a precise point cloud model, later construction planning can avoid mislocated underground installations and missed unknown pipes, providing significant benefits in both safety measures and efficiency.

Using recently introduced solutions like LRTK, the above process becomes even easier. LRTK consists of a small RTK-GNSS receiver device that attaches to an iPhone and a dedicated app, and its characteristic feature is that it can obtain centimeter-level positioning accuracy (half-inch accuracy) simultaneously with a smartphone LiDAR scan. Because it integrates point cloud measurement and positioning, which were previously performed separately, a single person can produce high-precision 3D records of buried pipes in a short time. Point cloud data acquired on site can be uploaded to the cloud immediately, and by the time one returns to the office 3D models and drawings are automatically generated, enabling an efficient workflow. By leveraging these cutting-edge technologies, the recording and maintenance management of buried pipes will be dramatically streamlined and elevated. Next-generation point cloud surveying that combines smartphones and high-precision GNSS is bringing the field of infrastructure management to a moment of transformation.