Streamline Slope As-Built Management: Improve Accuracy and Simplify Documentation with 3D Point Clouds

Introduction: Current Challenges in Slope Works and As-Built Management

In slope works (such as slope frame construction and sprayed concrete slopes), controlling the finished shape (as-built management) is essential for quality assurance. On site, measurements are taken after completion to confirm whether the slope and thickness match the design. However, measuring on steep slopes poses challenges in both safety and workload. Traditionally, surveying staff climb the slope and use tape measures or leveling staffs to measure lengths, or pick points with a total station. Manual measurement is hazardous and tends to limit the number of measurable points. In addition, compiling the obtained data into drawings and tables—preparing the submission documents—requires significant effort, placing a burden on construction managers.

As-built management standards require grasping the entire shape of the slope. For example, the Ministry of Land, Infrastructure, Transport and Tourism’s standard requires measuring the entire slope surface, including the slope crest and toe, and confirming the elevation difference from the design surface at all points (the allowable tolerance is generally about ±5 cm) [^1]. In other words, you must demonstrate that no location on the slope deviates from the design by more than 5 cm. In practice, however, due to safety and time constraints, some sites measure only a few representative points. As a result, there is a risk that undetected irregularities exceeding the standard may exist in unmeasured areas.

Moreover, preparing submission documents for the client takes time. Organizing measurement results and creating as-built management charts (comparison tables of design vs. measured values, cross-sections, etc.) was traditionally a manual process. As the number of measurement points increases, data entry into spreadsheets and plotting on drawings grows substantially, raising the possibility of human error. Thus, the current state of slope as-built management presents a dilemma: “We want accuracy, but safety and workload are a concern,” and “We want efficiency, but we still must properly prepare documents.”

Balancing “Accuracy,” “Workload,” and “Documentation” in As-Built Management

For construction managers, balancing accuracy, workload, and documentation is crucial in as-built management. Prioritizing accuracy requires detailed measurement across the entire slope, which demands time and manpower. Conversely, reducing workload by cutting measurement points risks missing defects in unmeasured areas, as mentioned above. No matter how accurately you measure, incomplete documentation can fail inspection. To satisfy clients and inspectors, you must prepare documents that conform to standards (for example, as-built management tables and photographs), and this also consumes effort.

On many sites, experienced technicians select measurement points based on their judgment to strike a practical balance between accuracy and efficiency. However, relying on individuals makes the process subjective, and maintaining the best balance consistently is difficult. Slope works vary widely in terrain and construction methods, making uniform simplification difficult. As a result, instances are common where teams “measure more than necessary to avoid rework” or where document preparation runs late, causing overtime.

What is needed is a system that increases efficiency while maintaining accuracy and automatically produces documentation. Rather than blindly increasing measurement points, it is necessary to innovate the measurement method itself to cover the whole while reducing workload. 3D point clouds have attracted attention for as-built management. Point cloud measurement technology can record slope shapes with an order-of-magnitude greater information density than before, offering the potential to balance accuracy and efficiency.

TS As-Built vs. Point Cloud As-Built: Which Suits Your Site?

Measurement methods for as-built management include the traditional TS (total station) method and the increasingly common point cloud scanning method. Consider the characteristics of each to determine which suits your site.

TS-based as-built management is a familiar method for experienced personnel. Using total stations and leveling instruments, coordinates and elevations are measured at specific points. For slopes, transverse survey lines are often drawn at regular intervals, and representative points on each line (toe, crest, several midpoints, etc.) are measured for position and elevation. TS offers very high precision, with single-point errors in the millimeter range, making it excellent for ensuring point accuracy. However, TS acquires “points” individually, so covering a large area requires many point-by-point measurements. On wide or highly irregular slopes, using only TS to capture the full shape entails tremendous effort. TS surveying typically requires a team of two or more (instrument and prism/staff operator), which also affects efficiency. Recently, one-man robotic total stations and reflectorless modes have made one-person surveys more common, but the basic workflow—aiming the instrument at each desired point and measuring—remains unchanged.

By contrast, point cloud as-built management uses dense sets of measured points (point clouds) obtained by laser scanners or photogrammetry. A single scan can capture millions to tens of millions of points, enabling surface-wide surveying of the entire slope. If TS measures by “points,” point clouds measure by “surface” 【Schematic: Traditional TS vs Point Cloud】. For example, setting a TLS (terrestrial laser scanner) on a tripod and scanning the slope can capture wide-area 3D data non-contact in a few minutes. Likewise, a drone equipped with a camera or LiDAR can survey from the air, allowing measurement of steep or hazardous slopes without personnel entering them. Many devices can be operated by a single person, which is attractive for labor-short sites.

Point cloud measurement has caveats. The upfront cost of laser scanners or drones, required PC processing power, and operator skill were previously high barriers. Because results are a large collection of points, extracting desired dimensions or generating drawings requires specialized software. Recently, however, these issues have been easing. Services that allow point cloud capture with inexpensive mobile devices and increasingly powerful point cloud processing software have created environments where handling point clouds is possible without heavy initial investment or deep expertise.

Which method suits a site depends on slope scale, shape, and required deliverables. For small, simple slopes, TS measurement at representative points may suffice. Conversely, for large, complex terrain or sprayed surfaces with many irregularities, point cloud scanning offers significant advantages. In practice, combining TS and point clouds is common: measure control points or verification points with TS at high precision, and use them to georeference point cloud data so the point cloud can achieve comparable accuracy. This hybrid approach allows point clouds to be used even in GNSS-denied environments like tunnels, compensating for each method’s weaknesses. In short, “point clouds excel at high-density, wide-area measurement; TS is best for ensuring rigorous accuracy at specific points.” Leveraging both strengths enables more efficient and higher-precision slope condition assessment than before.

Strengths of 3D Point Clouds: Measure Surfaces so Irregularities Aren’t Missed

The biggest benefit of using 3D point clouds is that you can measure the entire slope without omission. Traditional methods inevitably leave gaps “between points,” but high-density point clouds fill those gaps with detailed data. For a sprayed concrete slope, variations in thickness applied by workers can create subtle bumps and hollows on the surface; point clouds can record those irregularities in three dimensions. Changes that TS surveying might miss become obvious when you generate color maps or cross-sections from point cloud data. You can check across the entire surface for questions like, “Are there any sections with insufficient thickness?” or “Are there any protruding areas?” This enables early detection and correction of construction defects.

Point cloud measurement is also important because it is non-contact and remote. Personnel do not need to enter steep slopes or soft surfaces immediately after spraying; the shape can be captured safely from a distance. This reduces the risk of occupational accidents and cuts costs associated with scaffolding and safety supervision. There are reported cases where near-vertical rock slopes or high-mounted slope frames that were difficult to measure manually were measured safely and quickly with laser scanners or drones.

Point clouds also excel in efficiency. Because a single scan covers a wide area in a short time, total work time is greatly reduced. In one earthwork site, a survey that took three days with TS for several hectares was completed in two days with TLS and in half a day with drone photogrammetry. Another trial reported that drone-mounted laser surveying required one-sixth the time of traditional methods, halving or better the total project survey days. Point cloud technology dramatically increases surveying productivity and directly contributes to shortened schedules and labor cost savings.

Point cloud measurements can also provide confidence in accuracy. Some may worry that measuring a wide area at once leads to large errors, but advances in laser scanners and photogrammetric analysis now enable point cloud surveys to achieve errors on the order of millimeters to centimeters. With appropriate control point correction, point cloud surveys can easily meet the ±5 cm requirement for as-built management. Comparisons of earthwork volume calculations and as-built measurements with conventional methods have shown quantity differences on the order of about 1% in some cases. In short, point cloud scanning is a technology that can reconcile accuracy and efficiency.

Workflow for As-Built Management Using Point Clouds and Simplified Reporting

Let’s look at the typical workflow for as-built management using point cloud data. The key point is that once digital 3D data are acquired, subsequent processing and report generation can be largely automated. A common procedure is as follows.

• Measurement planning and control point placement: Plan the point cloud acquisition method according to the slope’s shape and extent—scanner setup locations and scan ranges for laser scanners, flight paths for drones, walking routes for mobile devices, etc. If necessary, install and survey known points (control points) so the acquired point cloud can be georeferenced accurately (existing construction control points may be used).

• Point cloud data acquisition: Perform 3D scanning on site according to the plan. For TLS, set up the scanner where it can view the slope and emit laser; for drones, capture aerial photos or laser scans; for mobile devices, walk beneath the slope to perform LiDAR scanning—methods vary by equipment. The important thing is to acquire a point cloud that covers the entire slope in a short time. For example, some smartphones with LiDAR can capture point clouds of tens of meters by simply walking while pointing the camera at the slope.

• Data processing and comparison with design data: Process point cloud data on a PC or in the cloud. Filter out unwanted points (pedestrians, machinery, trees) to retain only terrain and structure point clouds. Then overlay the point cloud with the design model. If you have a 3D model from design drawings or design cross-section lines, align them in the same coordinate system and compute deviations for each point. This is where control point information proves useful. With properly georeferenced point clouds, you can accurately evaluate whether the as-built matches the design by coordinate differences.

• As-built evaluation (pass/fail judgment): Analyze the differences between the point cloud and the design to determine whether values are within the specified tolerance. Specifically, check for each point whether the elevation (or horizontal) deviation from the design surface is within ±◯ cm. Dedicated software can display the differences as a color-coded heat map. For example, areas within design tolerance might be colored blue–green, while areas exceeding the tolerance are red. This makes it intuitive to see which parts of the slope are within tolerance and which are out of tolerance. If everything is blue/green, the site passes; if red areas appear, those parts can be corrected.

• Automatic report generation: After evaluating the as-built with point cloud analysis, summarize the results in the prescribed format. Digital measurement’s strengths are evident here. Point cloud software and linked tools can automatically generate as-built management charts. For instance, lists showing design value, measured value, and deviation for representative points, or cross-sections with pass/fail labels, can be output with one click. Tasks that previously required manual entry into Excel can now be exported directly to Excel or PDF from point cloud data, reducing human errors and cutting work time. The Ministry’s “Guidelines for As-Built Management Using 3D Measurement Technology (Draft)” specifies evaluation methods and submission formats when using point clouds [^2], and software that conforms to these guidelines can produce compliant reports automatically. Point clouds or 3D models are increasingly submitted as electronic deliverables. Submitting digital data allows clients to examine details at any time, covering nuances that paper drawings might miss. This ultimately reduces document volume and smooths the inspection process.

As illustrated above, point cloud-based as-built management digitizes the entire workflow from field measurement to report creation. Because field-acquired data flow directly into analysis and output, there is no need for intermediate manual data entry. This yields major labor savings and contributes both to reducing the burden on surveyors and to improving reliability.

Case Study: Halved Workdays and Auto-Generated Reports at One Site

Here is a case where introducing point cloud as-built measurement dramatically improved efficiency. On a medium-scale slope construction site, measuring the as-built of a sprayed slope several tens of meters long used to require a three-person team and two full days. The first day was spent measuring heights and lengths at various slope locations with TS, and the second day was used for data organization and creating as-built charts. After trialing 3D point cloud measurement, field measurement was completed in half a day and report output was finished with about half a day of office work. Specifically, one worker scanned the entire slope with a laser scanner (about one hour), processed the point cloud in the office, compared it to design data, and printed a heat-map-equipped as-built report the same day. As a result, workdays were reduced by about half, and because only one worker was needed, total man-hours decreased significantly.

At this site, full-coverage point cloud checks also revealed spots with insufficient slope thickness in advance. A slight spraying irregularity (thickness shortfall of about 3 cm) that might have been missed by traditional methods showed up red on the heat map and was remediated by re-spraying before inspection, bringing it within tolerance. The construction manager stated, “Thanks to point clouds, we left no uncertainties and could submit confidently to the client.” They also noted that as-built charts were far easier since there was no need to manually write measurement point names or numbers—the auto-generated Excel sheet only needed printing.

Other examples published by MLIT include a case where as-built compilation days were halved from 12 to 6 using drone photogrammetry, and examples where laser scanners completed surveys in one-sixth the man-hours of conventional methods [^3]. These success stories illustrate the considerable time savings point cloud technology can bring. Beyond speed, the greater data coverage reduces the risk of rework: if you prevent remeasurement or repair due to missed spots or measurement errors, overall project schedules stabilize. Point cloud as-built management takes the “measure thoroughly first” approach: investing in digital measurement early reduces later rework and effort.

Client and Inspector Reactions and the Reality of Digital Inspections

When introducing new technology, concerns often focus on how clients and inspectors will react. Initially, some inspectors questioned using point clouds for as-built management, asking “Is this really accurate?” or “Will a different format from drawings cause problems?” However, with national initiatives promoting ICT in construction (i-Construction), understanding and trust in 3D point cloud use are growing.

A common client reaction is that point clouds are “visually easy to confirm.” Where paper drawings used to show measurement results only at a few points, a point-cloud heat map displays the entire slope’s condition at a glance. If you explain, “The largest deviation from the design is about +3 cm, which is within tolerance,” experienced inspectors often respond that they can readily see the work was executed properly. In many cases, digital data are actually more persuasive.

That said, some field inspections still require paper reports. Older inspectors may prefer printed charts, so it is prudent to attach paper outputs in the prescribed formats. However, because the source data come from point cloud analysis, there is confidence that no transcription or calculation errors exist. If inspectors ask, “Where and how were measurements taken?” you can show placed measurement points and cross-sections on the point cloud, or even present the 3D model on a tablet. Some clients now accept electronic submission of as-built management data, and certain prefectures have procedures for electronic deliverables [^4]. The trend toward digital inspections is likely to accelerate.

Indeed, MLIT-led projects are increasingly applying the principle of CIM (utilizing 3D models), and supervision and inspections are beginning to use tablets to review point clouds and BIM models. Local governments are also conducting training on maintenance and inspection using point cloud data as part of infrastructure DX and recognizing exemplary ICT utilization cases. Against this backdrop, worries that “point clouds will be rejected at inspection” are diminishing. On the contrary, well-collected and well-processed point cloud deliverables are welcomed by clients because they provide abundant evidence to substantiate as-built conditions and make it easier to fulfill quality accountability.

Overall, client and inspector responses are turning positive. That said, being new technology alone does not guarantee acceptance—deliverables must comply with the applicable standards. Using point clouds does not exempt you from submitting required charts and numerical reports. The MLIT guideline (draft) clearly positions point cloud usage, enabling both site technicians and inspectors to handle digital as-built deliverables according to common rules. With standards now in place, sites can more confidently adopt new technologies.

Conclusion: Accuracy and Efficiency Can Be Reconciled

3D point cloud adoption is an effective solution to the challenges of accuracy, efficiency, and documentation in slope as-built management. The key point is that you can “improve efficiency while maintaining accuracy.” Where teams used to choose between accuracy and efficiency, point cloud scanning enables both to be achieved at a high level. Measuring wide areas quickly while capturing fine details reduces overlooked defects, eliminating rework and remeasurement and thus reducing total work time.

Digitizing measurement data dramatically improves the efficiency of report generation and information sharing. If field-acquired point clouds can be directly analyzed and reports automatically output, the manual effort of preparing documents drops. From the perspective of workstyle reform, this is a major benefit. Reducing the long overtime once caused by as-built report preparation lessens the burden on construction managers. Submitting as-built data electronically also reduces client-side document handling, benefiting both parties.

Technical barriers are also falling. High-end 3D laser scanners that were once costly are now available for rental or as services, and small drones or smartphones can obtain point clouds. Under MLIT’s i-Construction initiatives, standardization of ICT construction is advancing and systems supporting the challenge of new technology are being developed (for example, as of 2024 the as-built management guidelines are being expanded to cover all work types, and a streamlined version is planned to further facilitate on-site adoption). In short, overcoming psychological hurdles like “it seems difficult” or “I’m worried about inspections” will likely yield substantial benefits.

Slope works remain an important part of ongoing infrastructure development and disaster prevention. 3D point cloud technology, which can both streamline and enhance quality control, is a strong ally for construction managers. Consider applying this as-built management method that reconciles accuracy and efficiency on your site—you may find that familiar assumptions change and you gain real convenience and peace of mind.

Bonus: Smart As-Built Management with Point Cloud–Report Integration Starting with LRTK

If you’re interested in point cloud as-built management but wonder what to prepare, here is an easy-to-start solution: LRTK. LRTK is a smartphone-based 3D measurement system in which a compact GNSS receiver attaches to a smartphone to enable anyone to easily acquire high-accuracy point cloud data.

For example, attaching an LRTK device to an iPhone with a LiDAR sensor lets you walk along the slope while holding the phone to scan the surrounding area and generate a point cloud model. Because LRTK supports RTK-GNSS centimeter-level positioning, the acquired point cloud is assigned global coordinates (absolute coordinates), enabling alignment with survey maps at survey-grade accuracy. Whereas 3D scanning once required equipment costing hundreds of thousands of dollars and specialist skills, LRTK allows you to start with a single smartphone, greatly lowering the initial adoption barrier.

LRTK offers cloud services and dedicated apps that seamlessly connect point cloud acquisition to as-built report creation. Specifically, you can upload point cloud data captured on a smartphone to the cloud on-site, overlay it with design drawings in a browser, check differences, and measure required dimensions. The aforementioned heat-map display is available with one click, allowing instant judgment of conformity to design. Templates for as-built management reports that conform to MLIT guidelines are also provided, enabling automatic output of as-built management charts (Excel or PDF) from point cloud data. For example, for slope frame works, items such as frame width, frame height, and slope length can be listed in the prescribed format showing the deviation from design values. These outputs are suitable for electronic delivery, eliminating the need to recreate documents.

In short, LRTK enables smart as-built management through point cloud–report integration on your smartphone: “measure with a phone and submit the report as-is.” Because results can be checked and shared in the cloud immediately after acquisition, interim reports to clients and internal checks are faster. The app is designed to be intuitive, so even users unfamiliar with 3D or ICT can start with a few hours of training. LRTK also supports photogrammetry mode, so phones without LiDAR can still generate point clouds from photos. Flexibility to suit site conditions is another advantage.

Thus, LRTK is a groundbreaking tool that brings point cloud–report integration to your handheld device. If you are considering improving accuracy, shortening time, and simplifying documentation for slope as-built management, starting with an LRTK solution that works on a familiar smartphone is a practical first step. By leveraging advanced digital measurement, you can take the first step toward truly smart as-built management.

[^1]: MLIT’s “As-Built Management Standards” require that all measured points on slope works be within ±50 mm of the design value and specify that measurements cover the entire slope surface (including crest surfaces and slope benches). [^2]: The National Institute for Land and Infrastructure Management’s “Guidelines for As-Built Management Using 3D Measurement Technology (Draft) R7.3” details procedures from point cloud acquisition to representative value calculation, evaluation, and chart creation. Using software compliant with these guidelines makes tolerance judgments and report generation easier. [^3]: Reference case: MLIT Kanto Regional Development Bureau i-Construction casebook (2019) reports efficiency gains from UAV photogrammetry for as-built measurement. Lefixea’s comparative experiments also present cases where drone LiDAR surveys were completed in one-sixth the time of conventional methods. [^4]: Example of electronic deliverables: Niigata Prefecture’s “Reference Materials for Electronic Delivery Regarding ICT Utilization” (2020) outlines procedures for submitting as-built management charts as PDFs and delivering point cloud data as electronic deliverables. Procedures vary by municipality, but electronic submission of as-built data is expanding.