Evolution of Slope Greening As-Built Management with Point Cloud Surveying

Slope greening works are construction activities that stabilize and revegetate slopes along roads, land development sites, and the like by covering the slope surface with vegetation. By activities such as spraying seeds or installing vegetation mats, the slope is covered with plants to prevent soil erosion and to improve the landscape. In slope greening, an important task is the verification of the post-construction slope shape to ensure it matches the design—this is known as "as-built management." It is necessary to check whether the greening material has been sprayed to the specified thickness and uniformly, and whether the slope gradient and shape are free of irregularities to guarantee quality. However, measuring slopes—targets that are inherently inclined and curved—is difficult with traditional methods, requiring significant manpower and time. This article explains how those challenges can be addressed using the latest point cloud surveying (3D measurement) and introduces how as-built management for slope greening can evolve.

Purpose of as-built management in slope greening and issues with traditional methods

The purpose of as-built management in slope greening works is to confirm that the slope has the planned shape and dimensions, thereby ensuring safety and construction quality. Specifically, this involves verifying that the topsoil or seeds sprayed on the slope surface have been applied at the design thickness and uniformly, and that the gradient and curvature from the slope shoulder to the slope toe are formed smoothly as drawn in the plans. The results of as-built management serve as reporting material to the client and inspectors and are important evidence that appropriate construction was performed.

Traditionally, this verification has mainly been done by manual surveying using tools such as tape measures, staffs (leveling rods), and levels, measuring key dimensions and comparing them to design values. For example, representative cross-sections might be selected from across the slope, and thicknesses and inclinations would be measured with a scale along those lines, then cross-sections would be drawn and compared with the designed sections. However, these traditional methods have many issues. Especially for wide, uneven targets like slope greening, the following problems are prominent:

• Difficulty measuring inclines and curved surfaces: It is not easy to measure accurate thicknesses and shapes on steep slopes or complex curved surfaces. Tape measures and staffs are hard to hold against the surface, and there are limits to how accurately these tools can capture surface irregularities.

• High manpower and time requirements: Measuring multiple points across a wide slope requires not only surveying staff but also assistants, and securing access and safety measures takes time. In some cases, confirming the as-built condition of a single slope could take a whole day or more.

• Lack of coverage and potential oversights: The number of measurable points is limited, making it difficult to inspect the entire slope exhaustively. Even if sampled spots meet the criteria, there may be areas in between that deviate from the design. Traditional methods risk overlooking subtle surface irregularities or insufficient thickness.

• Workload and safety issues: Manual surveying on steep slopes is a heavy burden for workers and carries safety risks such as falls. Measuring at high places or on unstable footing is dangerous, and working in awkward postures can lead to human error.

Thus, as-built management for slope greening has faced significant challenges in terms of accuracy, efficiency, and safety. A solution gaining attention in recent years is as-built management using three-dimensional point cloud data.

Advantages of surface and volumetric data obtained by point cloud surveying

Point cloud surveying is a method that digitally records an object as a collection of countless points (a point cloud) using laser scanners or photogrammetry. The obtained point cloud data represents the entire slope surface as XYZ coordinate points and can be regarded as a full-scale 3D model that faithfully captures the site. It records details that cannot be fully captured in drawings or photographs and can store the post-construction state as a digital twin.

Unlike conventional single-point measurements, point cloud surveying provides surface-based and volumetric data. Specifically, it covers the entire slope area with a dense set of points and retains topographic information including undulations and irregularities as a three-dimensional form. This makes it possible to comprehensively grasp the as-built condition of the entire slope. Small steps or depressions that manual methods would miss can be revealed in the point cloud, leading to a dramatic improvement in accuracy of as-built management.

In addition, any required measurement information can be freely extracted afterward from point cloud data. Once scanned, you can measure dimensions at arbitrary locations on an office PC, create longitudinal and cross sections, and calculate areas and volumes as desired. There is no worry of “forgetting to measure” a location on site, and the need to return for additional measurements is reduced. Since point cloud surveying acquires a large amount of data in a single measurement, tasks that previously required several people and long hours to measure slope as-builts can be greatly streamlined. In fact, a Ministry of Land, Infrastructure, Transport and Tourism survey reported that the introduction of ICT construction (3D surveying and machine guidance, etc.) reduced total earthwork man-hours by about 30% on average. The non-contact and high-speed measurement enabled by point clouds also reduces machine idle time and rework, contributing to shorter schedules and improved productivity.

By leveraging point cloud surveying, which provides surface and volumetric data, as-built management of slope greening evolves to become more accurate and efficient. The next section shows how point cloud data can be specifically used to verify post-construction slope conditions and sprayed thickness.

Visualizing post-application condition of greening materials and verifying sprayed thickness with point clouds

In slope greening, it is important to properly verify the finished condition after seeds or mortar have been sprayed onto the slope. Using point cloud data, the post-application state of the slope can be understood both visually and quantitatively.

For example, if the pre-construction slope terrain or the design ideal shape is known, you can overlay that with the post-construction point cloud to calculate the thickness of the sprayed material. Specifically, subtract the pre-construction terrain model (or design model) from the post-construction point cloud to obtain elevation differences. Displaying these differences as a color map (heat map) makes it possible to visualize at a glance how thick the greening material is at each location on the slope.

For instance, if the specified sprayed thickness is 5 cm (2.0 in), areas where the thickness is insufficient will appear red or yellow on the point cloud, while locations meeting the design thickness will appear green or blue. This enables detection of areas lacking sufficient thickness. You can also select arbitrary points to check thickness numerically, or calculate the average thickness for a specific area—detailed quantification is possible. In situations where previously one could only estimate thickness by sticking a scale into various parts of the slope, point cloud data allows accurate thickness measurement across the entire area.

Point cloud data can also be obtained as textured models with color photos applied. This makes it possible to visually confirm surface conditions such as uneven application of greening material or uncoated areas. By rotating and zooming a colorized point cloud model, you can spot slight un-sprayed spots on the screen that would be missed by the naked eye. As described above, leveraging point clouds enables visualization of post-application as-built conditions while also obtaining quantitative thickness data, making quality verification far more reliable.

Concrete example of as-built evaluation by 3D difference comparison with the design model

Point cloud data also shows its strengths when overlaid with a three-dimensional design model or drawing data created during design. Here is a concrete example of as-built evaluation for slope greening using 3D difference comparison with the design model.

In one slope greening project, a design model was created to produce a gently curved final surface. After construction, the site slope was scanned and the resulting point cloud compared with the design model. Most areas matched the model, but some locations were found to have excessive buildup or depressions. The differences were displayed as a heat map: portions protruding above the design surface were shown in red, and areas depressed below the design were shown in blue, making it intuitive to identify where deviations occurred.

Such a 3D difference heat map immediately shows where corrective work is needed on the slope. For example, if areas where the greening material is overly thick exceed the design line and appear red, the decision might be to trim those parts or adjust the blending with adjacent areas. Conversely, locations shown in blue below the design indicate possible thickness shortages and may require additional application.

The information obtained from difference comparison is not limited to visual cues. In point cloud software, you can inspect elevation differences between the design model and the current point cloud on cross sections, and read the deviation amounts as numerical values. For example, by displaying several vertical cross sections of the slope and overlaying the design profile line with the point cloud, you can measure local thickness errors as if placing a ruler on the section. This enables quantitative evaluation such as “a +3 cm (1.2 in) bulge at the slope center relative to the design” or “a −2 cm (0.8 in) deficit near the slope shoulder.”

Furthermore, using the difference data between the point cloud and the design, it becomes easy to calculate the volume of material required for repairs or additional work. For example, you can instantly compute by volume comparison how many cubic meters of topsoil are needed to reach the design surface, or conversely how much excess has been piled up. As-built evaluation that was difficult to perform manually can be accomplished quickly and with high accuracy using point cloud data.

Immediate on-site confirmation and evaluation combining point cloud data with AR

A new trend in point cloud utilization is combining on-site AR (augmented reality) technology. By overlaying the 3D design model or the measured point cloud in real time onto the actual site view, you can intuitively confirm as-built conditions while on site.

For example, when viewing the slope through a tablet or smartphone, a translucent design completion line may be displayed, or a current point cloud model may be overlaid like CG. This allows you to confirm on the spot which parts are as-designed and which parts deviate. If a colorized heat map is displayed in AR, red or blue highlights appear on the actual slope, intuitively indicating deviating areas.

This point cloud × AR on-site confirmation is also useful for having the client and the contractor evaluate and share as-built conditions from the same viewpoint. Where previously the acceptability of as-built work was difficult to explain with drawings or numerical reports alone, overlaying the information on the real object with AR makes it immediately clear. This smooths communication among stakeholders and helps prevent disputes arising from differing interpretations. During construction, AR can also overlay the completion image or design line onto an unfinished slope so that the finish goal is shared on site, enabling real-time confirmation and instructions that help prevent rework and improve quality.

Instant sharing and streamlined as-built inspection through cloud integration of point cloud data

Handling point cloud data on a cloud platform further streamlines the as-built management workflow. Uploading measured 3D data to the cloud enables instant sharing with stakeholders in the office or at remote locations. For example, a slope point cloud scanned on site can be reviewed the same day by the client or inspection staff at their desks.

Using cloud-based point cloud viewers and analysis tools, all stakeholders can review the same 3D data, check as-built conditions, and exchange comments and instructions in real time. This opens up the possibility of remote substitution for inspection steps that previously required personnel to travel to the site for visual checks. Especially for slope works in mountainous or remote areas, online sharing of as-built data reduces travel time and enables prompt inspection responses.

Cloud integration also enables automated processing of point cloud data to reduce effort in creating as-built management documentation. For example, the system could automatically determine differences from the design and generate reports, or submit 3D models as electronic deliverables in place of photo logs. If data are accumulated in the cloud, you can quickly respond to later verification or additional requests, easing the burden of inspection preparation. Smooth information sharing among stakeholders will help streamline the entire as-built inspection process.

One-person measurement and safe work on slopes using smartphones and lightweight equipment

Point cloud surveying may conjure images of expensive specialized equipment and expert operators. However, recently lightweight and labor-saving point cloud measurement using smartphones, compact laser scanners, and drones has become possible. This has increased cases where slope as-built measurement can be performed easily by a single person.

For example, recent smartphones are equipped with LiDAR sensors that can be used to scan nearby slope shapes and generate point clouds. With dedicated apps or attachments, a smartphone itself becomes a 3D measuring instrument. Combining handheld mid-size 3D scanners and small drones for photogrammetry can turn tasks that previously required a team into work that is performable by very few people.

The benefits of enabling quick one-person measurement extend beyond reducing personnel. A major advantage is improved work safety. With small equipment, mobility is high, and the measurer can scan from a safe position without needing to physically press against the slope. For dangerous steep slopes, there is no need for the measurer to cling to the slope and work for long periods; if necessary, a drone can be flown at a safe distance to collect data. Avoiding carrying heavy equipment while traversing unstable slopes and enabling non-contact measurement reduces the risk of on-site accidents.

Moreover, as-built measurement that previously required experienced technicians has become easier with many of the latest devices offering intuitive operation. Some smartphone apps automatically acquire point clouds simply by walking according to on-screen guidance, and allow immediate on-site verification of results, making the tools accessible even to non-specialists. In construction sites facing severe labor shortages, easy-to-use point cloud surveying technologies that anyone can operate are becoming a lifesaver not just for slope greening but for various construction management tasks.

Reducing site burden with an integrated surveying, AR, and cloud solution using LRTK

As shown above, point cloud surveying and its associated technologies (AR and cloud integration) drastically improve the efficiency of as-built management for slope greening and greatly contribute to enhanced accuracy and safety. These approaches significantly reduce traditional effort and risk while reliably guaranteeing the slope finish, and their use is likely to continue expanding.

In this context, our LRTK supports on-site ICT by integrating point cloud surveying, AR display, and cloud sharing into a single solution. With LRTK, anyone can easily acquire high-precision slope point cloud data using just a smartphone, and immediately perform comparisons with design data or conduct on-site checks using AR. Acquired data can be uploaded to the cloud instantly and shared with stakeholders, enabling a seamless as-built management workflow.

For example, LRTK provides a one-stop solution from surveying to difference analysis, heat map display, volume calculation, and AR-based as-built checks. This eliminates the need for personnel to switch among multiple devices and software, significantly reducing on-site workload and post-processing effort. The all-in-one system that links point cloud, AR, and cloud delivers user-friendly operation even for first-time users, providing an environment where anyone can perform accurate as-built verification in a short time.

To achieve both quality assurance and operational efficiency in slope greening works, utilizing such advanced technologies is key. If you currently face challenges with as-built management, introducing a solution like LRTK may remarkably simplify surveying and inspection tasks. We hope that LRTK, which fuses smartphone point cloud surveying with AR and cloud, can help reduce on-site burdens while ensuring reliable as-built management.