What Is Drone Point Cloud Analysis Useful for Slope Management? 6 Use Cases and Benefits of Introduction

Table of Contents

What is drone point cloud analysis

• Use in disaster recovery

• Use in maintenance management

• Use in construction management

• Use in safety inspections

• Use in as-built management

• Use in comparing long-term changes

• Effects of introducing drone point cloud analysis

• Use of high-precision positioning and LRTK

• Summary

What is drone point cloud analysis

Slope management is the set of tasks for understanding the condition of man-made slopes (cut or fill slopes) created along roads or on developed land, and for maintaining their safety and stability. There are countless slopes across Japan that require maintenance, and their inspection and surveying are important work that supports infrastructure safety. The purposes of slope surveying are broadly twofold: one is quality control during and immediately after construction (to confirm that construction was carried out according to the design), and the other is post-completion maintenance and disaster response. Traditionally, slope surveying and inspection were mainly performed by survey technicians measuring a few heights and gradients with total stations or levels, or by visually inspecting dangerous steep slopes by entering them directly. However, this approach has limitations in capturing the shape of an entire wide slope, requires considerable labor and time, and carries safety risks. Also, because the number of measurement points is limited, the overall slope shape could only be inferred from a few cross-sectional data, risking the oversight of fine deformations.

In recent years, "drone point cloud analysis" has attracted attention as a means to solve these issues. Using drones (small unmanned aerial vehicles) to photograph slopes from above, photogrammetry and laser measurement are used to generate three-dimensional point cloud data. Point cloud data are 3D survey data that represent the surface geometry of an object as a collection of countless points, with each point including coordinate information (X, Y, Z). By flying a drone and photographing the entire slope, a high-density 3D model composed of hundreds of thousands to millions of points can be constructed, digitally recording the entire slope shape without omission. Whereas previously only limited points on the slope could be measured, this technology makes it possible to safely and efficiently “measure the whole slope.” On slopes covered by trees, using a drone equipped with a laser scanner makes it possible to obtain ground points through gaps in branches and leaves and understand the terrain beneath vegetation.

By processing the obtained point cloud data with specialized analysis software, various information such as slope gradient, height, and earthwork volumes can be measured, and topographic maps and cross-sections can be created. Combined with high-precision positioning information, analysis overlaying design drawings or existing terrain data is also possible. In other words, drone point cloud analysis is a method of utilizing 3D data obtained by drones to comprehensively understand and analyze slope conditions, and it is expected to be a revolutionary new technology for slope management.

Use in disaster recovery

When a slope collapses due to a disaster, rapid and safe situational assessment is required. Because of this need, municipalities and road managers have increasingly used drones in initial disaster response in recent years. Traditionally, workers had to approach collapse sites despite the danger to survey or estimate the damage visually, but with drones the entire site can be captured from a distance in a short time. For example, even in a slope collapse covering several hectares, a drone can cover almost the entire current condition in about 20 minutes of flight, recording an area that would take more than a day by manpower in a short time.

When a large landslide occurs, photographing the collapse area and sediment accumulation from the air with a drone and generating point cloud data enables accurate calculation of the collapsed soil volume (the volume of soil that has fallen). Obtaining a 3D model of the collapsed area allows one to spatially grasp where emergency measures are needed and where there is risk of secondary disasters, aiding the consideration of restoration methods and the planning of heavy equipment placement. Also, because data acquired on site can be immediately shared with stakeholders, supervisors in distant offices and disaster response headquarters can share the situation in real time, speeding up decision-making. Furthermore, 3D models can be used to simulate restoration work, such as examining the placement of temporary roads and routes for bringing in heavy equipment. Drone point cloud analysis enables obtaining detailed data safely without sending people into dangerous sites immediately after a disaster, greatly contributing to shortening the time to plan recovery and ensuring worker safety.

Use in maintenance management

Drone point cloud analysis is also effective for routine slope maintenance. Traditionally, periodic slope inspections involved inspectors visually searching for anomalies from the ground or measuring only a few dangerous spots. However, scanning the entire slope with a drone captures subtle changes and deterioration that the naked eye might miss in 3D data. For example, slight bulging or cracks on the slope surface and changes in vegetation covering the slope can be objectively detected by analyzing point cloud data. Moreover, routine inspections that used to take several people a full day can be completed by one person in a short time with a drone, making it possible to巡回 multiple locations in a single day. Based on such data, areas that require early repair can be accurately identified, and undertaking remedial work while issues are minor can help prevent large-scale collapses. Accumulating measurement data over multiple years allows comparison with the past to analyze trends of long-term deterioration, aiding the formulation of long-term maintenance plans. By preventing oversight of small anomalies and addressing them promptly, the result can be reduced costs for large-scale repairs and disaster recovery. The use of drone point cloud analysis improves the accuracy and efficiency of routine patrols and periodic inspections, enabling continuous high-level maintenance of slope health.

Use in construction management

Drone point cloud analysis is also used for construction management at sites involving new slope construction or reinforcement work. Periodically aerially photographing a slope under construction with a drone and performing 3D measurement allows continuous grasp of construction progress and terrain changes. For example, when a slope is formed by excavation or embankment, converting the pre- and post-construction terrain into point cloud data and comparing them enables accurate calculation of earthwork volumes—how much soil was cut or filled. This automates and improves the accuracy of work quantity calculation and schedule management, greatly increasing efficiency compared to traditional manual cross-section calculations. Overlaying the acquired point cloud on the planned surface in design drawings makes it immediately apparent whether the current slope gradient and height match the design, allowing early corrections if necessary. This reduces rework during construction, securing quality and shortening construction periods. Sharing the 3D model generated on site among stakeholders allows not only construction personnel but also designers and clients to grasp progress in real time, facilitating smooth information sharing. Some sites perform drone surveys weekly to continuously monitor detailed work quantities. Because there is less need to interrupt work for surveying, current conditions can be safely assessed in parallel with other heavy equipment operations. Construction management using drone point cloud analysis enhances efficiency and productivity on site and is a powerful tool to ensure reliable quality. The application of such 3D measurement technology is also encouraged as part of ICT construction (i-Construction) promoted by the Ministry of Land, Infrastructure, Transport and Tourism, and its adoption in slope works is progressing.

Use in safety inspections

Safety inspections of slopes along roads and hillsides are indispensable after heavy rain or earthquakes. Even on steep slopes where people cannot safely enter, drones enable detailed observation from a distance. Drone point cloud analysis can identify in three dimensions precursory cracks to collapse, small-scale soil sloughing, and the presence of loosened rocks (loose boulders). Combining high-resolution photographs with point clouds allows detection of abnormalities at the top of slopes that are difficult to see from the ground. Drones can freely fly over areas where humans cannot enter, enabling observation from all angles and reducing oversights. Furthermore, because point cloud data obtained by drones can accurately measure the location and extent of hazardous spots, appropriate decisions can be made on reinforcement work or road closures. Road managers can inspect slopes by drone immediately after heavy rain and reopen roads only after confirming safety. Traditionally, specialists sometimes had to climb slopes with ropes and perform precarious visual inspections, but drone use can greatly reduce such dangerous tasks. This protects workers while improving inspection accuracy and contributes to the safety of road users and nearby residents. High-altitude inspections by drone have also begun to be used for regular safety patrols, contributing to more efficient inspections and digital record keeping.

Use in as-built management

Drone point cloud analysis is also highly effective for as-built management, which is the quality confirmation after slope construction is completed. Traditionally, a completed slope was checked by measuring a few cross-sections and comparing them with design drawings to verify gradients and dimensions. However, acquiring point cloud data allows the entire slope to be recorded digitally, enabling comprehensive inspection for deviations from the design shape across the entire slope. For example, on a slope protected by sprayed concrete, comparing the point cloud to the design model can visualize, with a color-coded difference map, where thickness is insufficient or where there are local protrusions or depressions. Even in complex terrains that are difficult to measure manually, point clouds cover every nook and cranny, preventing inspection omissions and improving the reliability of quality control. The government has formulated guidelines (draft) for as-built management using 3D measurement technology and is promoting the use of point cloud data in slope works. Introducing as-built management using drone point cloud analysis enables efficient and accurate inspections and leaves objective data that supports construction quality. Furthermore, this method can speed up inspection processes—cases exist where as-built confirmation that used to take several days can be completed in a short time. Digitized inspection data also smooths the submission of deliverables to clients and information sharing among stakeholders.

Use in comparing long-term changes

Data obtained by drone point cloud analysis can also be used to analyze long-term changes. Historically, accurately grasping terrain changes over many years was difficult and often relied on experience and visual estimates. However, comparing past and present point cloud data provides clear evidence of such changes.

For example, repeatedly scanning the same slope at different times allows quantitative understanding of terrain changes over the years by comparing those 3D datasets. Overlaying point clouds from immediately after construction with those from several years later makes it clear how much soil has been lost due to surface erosion or whether the slope has generally bulged due to earth pressure—changes that are difficult to detect by eye. Visualizing the magnitude of changes as a color-distribution map makes it easy to see which locations have moved and by how much, providing materials for determining where early reinforcement is needed. Even in the event of a large-scale collapse, comparison with the most recent data allows accurate grasp of the collapsed soil volume and the collapse range. For instance, if point cloud measurements are taken every five years and data accumulated, terrain changes after 10 or 20 years can be scientifically evaluated. By storing past point cloud data as an asset, it can be used for future maintenance and disaster response, contributing to more advanced planning and decision-making for slope management.

Effects of introducing drone point cloud analysis

Introducing drone point cloud analysis can be expected to bring the following effects in slope management field operations.

First, it leads to cost reduction. Because surveying work that used to require multiple people and long hours can be made more efficient with drones, labor and equipment costs decrease. Detecting anomalies early and addressing them with small-scale repairs reduces costs associated with large-scale collapse responses. Also, compared to human work that requires erecting scaffolding on slopes or traffic restrictions, non-contact measurement by drone reduces incidental work costs. For example, at sites that previously required road closures for surveying, using drones can shorten or eliminate restriction times, reducing impacts on third parties.

Next is improved work efficiency. Drones can survey large areas in a short time, and software automates data processing, so tasks that used to take days can be completed in hours. Even sites lacking experienced technicians can conduct wide-area surveys with a small crew using drones, addressing labor shortages. Time spent halting construction for surveying is reduced, smoothing the overall site schedule. Also, once point cloud data are acquired, necessary measurement results (such as cross-section creation and volume calculation) can be obtained repeatedly, preventing rework for additional on-site surveys.

Safety improvement is another major benefit. Replacing surveying and inspection work on dangerous steep slopes with drones reduces the risk of workers entering high or collapse-prone sites. After disasters, there is no need to send people to unstable slopes, protecting workers from secondary disasters. Reducing on-road work time also lowers accident risks for third parties.

Improvements in surveying accuracy can also be expected. Point cloud data record the entire slope shape densely, capturing fine irregularities and changes that were previously missed. Averaging and analyzing many points reduces variability compared to single-point human surveys, providing a stable level of accuracy in terrain understanding. With properly placed control points, positional accuracy can be secured at the centimeter level (half-inch accuracy), enabling strict comparisons with design drawings. Whereas previously only dozens of points on slopes could be measured, drones can acquire millions of points, providing an unprecedented level of terrain detail. Because measurement results are stored as digital data, the same results are more likely to be obtained regardless of the operator, reducing subjective errors.

It also contributes to improving report quality. Drawings and visual materials created from acquired 3D data are very easy for stakeholders to understand. For example, content that used to be explained only with paper drawings and numbers can be understood at a glance using 3D point cloud views or cross-sections. Objective, data-based reporting increases trust from clients and residents and facilitates discussions and negotiations. Because data can be shared instantly via the cloud, distant stakeholders can quickly review the same information together. Augmented reality (AR) technologies that overlay point cloud data on site images on tablets have also emerged, making it possible to intuitively share spatial information that is hard to convey with drawings.

Finally, it speeds up decision-making. Recording a site with drones allows immediate sharing of current-condition data, enabling on-the-spot examination of issues and discussion of countermeasures. Matters that used to require waiting for survey results to be processed can be decided the same day by checking the data. Faster information sharing and decision-making help prevent rework and delays in emergency responses. Reporting to senior management and contacting clients can also be done promptly, improving the efficiency of the entire decision-making process.

Use of high-precision positioning and LRTK

To maximize the benefits of drone point cloud analysis, high-precision positioning for control points is essential. LRTK, a high-precision GNSS receiver that can be attached to a smartphone, is useful for this purpose. Attaching an LRTK to an iPhone and performing RTK positioning makes it easy to achieve centimeter-class positioning (half-inch accuracy) that previously required expensive specialized equipment. This device streamlines control point surveying for drone photogrammetry and on-site coordinate checks. For example, before performing aerial photogrammetry of a slope, a few known points (control points) need to be installed on site, and using LRTK lets you obtain accurate coordinates quickly and complete the point installation work. When verifying that the actual slope position matches the coordinates on design drawings during as-built management, you can confirm coordinates on the spot with a smartphone, enabling quick verification. The arrival of LRTK has greatly lowered the barrier to entry for small and medium-sized contractors and municipal staff to perform high-precision surveying with a smartphone, making the introduction of drone point cloud analysis much easier. Introducing such new high-precision positioning tools further enhances the reliability of data obtained by drone point cloud analysis and improves on-site work efficiency.

Summary

This article introduced six use cases and benefits of drone point cloud analysis in slope management. From disaster recovery to routine maintenance, construction quality control, safety inspections, as-built verification, and long-term terrain change analysis, you should now understand that drone point cloud analysis is useful in a wide range of situations. Three-dimensional surveying using drones simultaneously achieves efficiencies, higher accuracy, and improved safety that were difficult with traditional methods, and slope management tasks are undergoing significant change. National and local governments are promoting advanced initiatives that utilize these ICT technologies, and further diffusion is expected. Even sites that have not yet introduced drone point cloud analysis can experience its convenience and benefits by trying it on a trial basis. Moreover, combining drone measurement with smartphone-compatible high-precision GNSS devices (such as LRTK) makes control point installation easier and on-site operations smoother. The use of drone point cloud analysis and the latest technologies dramatically improves the safety, efficiency, and reliability of slope management. Introducing these technologies also contributes to DX (digital transformation) in the construction industry, supporting a shift from management based on experience and intuition to smart, data-driven management. Please consider adopting these new technologies at your sites to help achieve safer, more secure infrastructure maintenance.