In recent years, slope failure disasters accompanying heavy rains and earthquakes have been occurring frequently across many regions. When slopes on mountainsides or alongside roads collapse, the resulting soil and debris can block roads and buildings, causing serious disruption to local transportation networks and residents’ lives. Moreover, collapse sites carry the risk of secondary disasters, requiring prompt restoration responses. It is therefore extremely important to accurately assess the damage during the initial response phase and to develop a rapid and safe recovery plan. This article describes the overview of damage from slope failure disasters and key points of initial response, considers the limitations of traditional surveying methods, and introduces the advantages of the latest 3D surveying (point cloud scanning) technology for on-site assessment. It also explains modeling the current terrain in 3D, calculating the volume of collapsed soil, and remote assistance through data sharing, and concludes by mentioning LRTK’s simplified 3D surveying solution as an example of rapid recovery support using these technologies.

Damage Caused by Slope Failures and the Importance of Initial Response

When a steep slope collapses, a large volume of soil and rock can fall to the foot of the slope in an instant, causing severe damage such as road severance, structural destruction, and threats to human life. In particular, in mountainous or coastal road areas, slope failures can isolate communities or cut off major arteries. At disaster sites, search and rescue and prevention of secondary disasters are top priorities, but at the same time information must be collected to formulate an early restoration work plan. Accurate situational awareness during the initial response is directly linked to establishing a safe working system and considering appropriate restoration measures. If the scale of the collapse is misjudged, it can lead to incorrect arrangements of personnel and heavy equipment and wrong selections of construction methods, causing delays in recovery and additional costs. To advance recovery rapidly and effectively, it is indispensable to accurately determine the damaged area and the extent of damage at the site immediately after the collapse.

As a concrete example, in the large-scale debris flow disaster that occurred in Atami City, Shizuoka Prefecture in July 2021, comparing pre- and post-disaster terrain data (point cloud data) quickly clarified the spread and outflow volume of collapsed soil, which helped in understanding the damage and preventing secondary disasters. If the on-site situation can be grasped quantitatively in the initial stage in this way, subsequent responses can proceed smoothly and safely.

The Need to Accurately Grasp Affected Area, Shape, and Volume

At a slope failure site, it is necessary to accurately determine “which area collapsed,” “how the terrain changed as a result of the collapse,” and “how much soil collapsed or accumulated.” The affected area refers to the area covered by the collapsed slope or the outflow of soil; if this is not accurately identified, it is impossible to properly set safe work zones or restricted access areas. It is also necessary to record in detail the geomorphological shape changes caused by the collapse (height and gradient of the collapsed slope and the shape of deposited soil). These are important clues when considering restoration methods; for example, without knowing the longitudinal and cross-sectional shapes of the collapse site, it is impossible to design slope reshaping or reinforcement works.

Among these, accurately determining the volume of collapsed soil is extremely important. By quantifying the amount of soil lost by collapse or accumulated on roads, you can estimate the volume of soil that must be removed and the amount needed for re-fill for the restoration work. This is fundamental to the restoration plan and directly affects the number of dump trucks, number of transport trips, heavy equipment operating hours, and the amount of materials required. Furthermore, in public infrastructure disaster recovery, there are often reporting obligations regarding the damage, and accurate reporting of collapse scale (volume of collapsed soil and affected area) is indispensable for administrative procedures and applications for disaster recovery subsidies. From the perspectives of safety assurance, restoration design, and administrative reporting, it is required to comprehensively and accurately ascertain the affected area, shape, and volume.

Why Traditional 2D Surveying and Photographic Records Are Inadequate

For information gathering during initial response, planar survey maps and photographic records have traditionally been used. However, in large-scale slope failure sites, these conventional methods are often inadequate. In typical surveying, staff measure heights and distances at points around the collapse site at personal risk and then create plan views and cross sections from those points. Cross sections inferred from a limited number of measurement points have difficulty capturing complex terrain changes completely and are prone to errors in calculating the volume of collapsed soil. In particular, in highly undulating terrain like slope failures, it is difficult to visualize the whole scene from 2D drawings alone, which may lead to overlooking details.

Photography is also important for records, but photos alone cannot accurately measure scale or depth. Photos are visual reference materials and deriving precise dimensions or volumes from them is difficult (and time-consuming unless special photogrammetry techniques are used). Because time is of the essence at a collapse site, conventional methods that provide limited on-site information risk not supplying the data needed for restoration planning.

Moreover, manned surveying involves risk. Immediately after a collapse, the ground is unstable and there is a risk of additional collapse, making it hazardous for workers to approach and measure. There are limits to how much you can measure safely from a distance, and in some cases you may have to give up measuring important locations. As described above, 2D surveying and photographic records alone are insufficient to capture the three-dimensional and quantitative state of slope failures, posing challenges in both accuracy and safety.

Advantages of 3D Surveying (Point Cloud Scanning) at Slope Failure Sites

A promising solution to these challenges is on-site measurement using 3D surveying (point cloud scanning). Point cloud scanning is a method that uses laser scanners or photogrammetry to acquire countless measurement points and record the site’s terrain and structures as a dense collection of points (point cloud data). By performing 3D surveying at a slope failure site, you can capture the collapsed slope and surrounding terrain as a complete digital three-dimensional model. This offers the following major advantages:

• Precision and comprehensive measurement: Point cloud data can capture site details down to the millimeter level (0.04 in). Because it records the irregularities of the collapsed terrain and the shape of deposited soil in full, you can understand the damage three-dimensionally, including hard-to-see areas. Compared to sparse manual measurements, it provides a far higher density of information.

• Highly accurate volume and dimension calculations: From the acquired point cloud, software can freely perform volume calculations and dimensional measurements as described below. Even for complex shapes, accurate soil volume calculations using mesh methods are possible, yielding figures that are more reliable than rough estimates based on experience or intuition. In fact, cases have been reported where soil volume calculations using point cloud data achieved high accuracy with errors contained to around 1–2% compared to traditional methods.

• Significant reduction in work time: 3D scanning is extremely fast. The latest terrestrial laser scanners and UAV (drone) photogrammetry can acquire wide-area terrain data in a short time. For example, at a large-scale site where conventional soil volume measurement and calculation had required a team of four working one week (a total of 28 person-days), switching to point cloud generation and analysis from drone aerial photography reportedly completed the work with 2 people × 1 day (2 person-days). By utilizing point cloud technology, the time and manpower required for initial information gathering can be dramatically reduced.

• Improved safety: Many 3D surveying devices can perform measurements remotely, allowing scanning from safe locations without entering the collapse area. For example, laser equipment can be operated from the opposite bank or a distant high point, or drones can fly overhead, enabling acquisition of terrain data without humans entering hazardous zones. This allows necessary information to be obtained while avoiding the risk of secondary disasters.

• Use of digital records: The 3D models obtained as point cloud data serve as digital disaster records. They preserve detailed damage information that cannot be fully represented on paper maps or photographs, enabling future verification, cause analysis, and post-event reporting materials. Digital data are easy to copy and share, and when combined with cloud services mentioned below, multiple stakeholders can handle the information simultaneously.

In these ways, 3D surveying offers advantages over traditional methods in accuracy, efficiency, and safety. Recently, point cloud scanning has become possible even with familiar devices like iPhones and iPads without expensive specialized equipment, and such accessible 3D surveying technologies are increasingly expected to play a major role in disaster response.

Creating 3D Models of the Current Terrain and Calculating Volume of Collapsed Soil

Using point cloud data obtained by 3D surveying, you can immediately build a three-dimensional model of the damaged terrain caused by slope failure and calculate the volume of collapsed soil accurately. The specific procedure is: first, scan the post-collapse current terrain to obtain high-precision point cloud data. Then, if possible, compare it with pre-collapse terrain data or design-stage ground models to calculate the volume of soil that flowed out (the amount of soil lost by collapse) from the difference.

For example, in cases where a road slope has collapsed, you can measure from the point cloud the volume of the void created by the collapse (the missing portion of the slope) and the volume of soil deposited on the road or at the valley bottom. For the pre-collapse original shape, you can use design drawings or past survey data as the reference surface if they exist, or otherwise estimate it from the shapes of the surrounding intact slopes. By performing differential calculations between the reference surface and the current point cloud model, you can determine the volume of newly created voids and deposited soil to millimeter-level (0.04 in) precision.

Beyond volume calculation, various information can be extracted from the 3D model. You can cut longitudinal and cross sections at arbitrary locations to create cross-sectional drawings, measure the plan-projected area of the collapse, and calculate the height and gradient of the collapsed slope—obtaining all dimensional information necessary for restoration design. Since these analyses can all be carried out on a PC in the office, you can obtain the required data without additional on-site surveying. Regarding soil volumes in particular, it is easy to recalculate by changing the surveyed range from the once-acquired point cloud data. For example, if you want to add another collapsed section to the initially calculated area, you can handle it on the data without new fieldwork. Soil volume calculation from point cloud data is therefore also excellent in flexibility, allowing prompt recalculation in response to changing conditions.

A more advanced application is overlaying the acquired current point cloud model with the design model. During the restoration method review, overlaying planned 3D design data for fill or reinforcement onto the point cloud allows you to intuitively grasp discrepancies with the site. Using systems that color-code the differences between point clouds and design models makes it immediately clear where and how much soil needs to be added to restore the original shape, or how much overly accumulated soil should be removed. This differential review visualizes the required fill and excavation volumes to reflect in the restoration design, improving the accuracy of construction planning.

Using Volume Data for Removal Planning, Quantity Assessment, and Restoration Method Review

Accurate soil volume information obtained from point cloud data is highly useful for creating concrete restoration construction plans. When planning the removal of soil produced by the collapse, you can accurately estimate the required number of dump trucks, the number of round trips, and the capacity arrangements for disposal sites based on the calculated soil volume. Traditionally, the amount of collapsed soil was sometimes estimated by the site supervisor’s experience or visual inspection, but results based on point cloud data allow plans supported by verifiable data. Decisions such as “how many more dump trucks are needed” or “how much residual soil will remain for disposal” can be made with reference to the data, leading to efficient operations.

Similarly, point cloud data is powerful for determining construction quantities needed for restoration (the amount of fill material, quantities for slope stabilization works, etc.). To restore a collapsed slope to its original shape, you can digitally simulate how much fill is required or how large a retaining wall must be. For example, if you perform a hypothetical fill-back on the point cloud model of the collapse, the required soil volume is immediately calculated and any surplus soil generated can be simultaneously identified. Such quantity data are important in judging whether additional soil procurement is necessary and whether temporarily stored soil will be in surplus. Knowing accurate quantities in advance allows appropriate procurement planning and cost estimation for materials and equipment, enabling smooth progress of restoration work.

Moreover, 3D data are useful for reviewing restoration methods. Restoring a slope failure is not simply returning the displaced soil to its original place; it requires stabilization measures to prevent recurrence. From mortar spraying and slope framing to anchor works and retaining wall installation, selecting the optimal measure requires correct understanding of the geomorphological characteristics and scale of the collapsed slope. By viewing the point cloud model, designers can understand the slope’s inclination angles, presence of exposed bedrock, and spatial relationships with surrounding terrain in three dimensions, making proper method selection easier. For instance, the data can support decisions such as “the amount of collapsed soil is large and the entire slope is unstable, so a large retaining structure is required” or “the collapse is small, so early restoration can be addressed with sandbags and simple netting,” backing such choices with data.

As described above, detailed point cloud data supports decision-making at every stage from planning to construction. Data-driven planning reduces site-adaptive rework and is the key to achieving safe and efficient restoration work.

Remote Design, Client Review, and Record Keeping through Cloud-Based Point Cloud Sharing

The benefits of 3D point cloud data do not end with on-site measurement. By sharing acquired data on the cloud, a major advantage is that the situation can be checked and analyzed remotely. In disaster recovery, multiple stakeholders—local government officials in charge of the site, design staff, and the client (project owner)—need to share information and make decisions, and cloud point cloud sharing dramatically streamlines that process.

For example, when a site worker uploads point cloud data and site photos acquired by smartphone or dedicated equipment to the cloud, design teams in the office and remote supervisors or clients can immediately view the 3D model. There are systems that allow manipulation and measurement of point cloud data via a web browser without each participant installing special software or using high-performance PCs. This enables an environment where “you can grasp the damage situation at your desk and discuss restoration policies without going to the site.” For clients, who may have difficulty understanding the site situation from text or still images alone, a three-dimensional model allows intuitive comprehension of the situation, making it easier to rapidly decide on restoration methods and budget measures.

Storing data on the cloud also enables centralized record management. If you save point clouds and photos in chronological order from immediately after the disaster through to completion of restoration, it is useful for post-event verification and report preparation. For example, if you periodically perform point cloud scans and upload updates during daily restoration work, you can later trace terrain changes at each stage—“immediately after the disaster → emergency restoration → final restoration complete.” This is important both as evidence that restoration was conducted appropriately and as lesson data for future similar disasters.

Furthermore, cloud-shared data can be referenced and jointly reviewed by stakeholders simultaneously when needed. It is realistic to hold emergency meetings and rotate the point cloud model on a shared screen to confirm the damage. This avoids the hassle of attaching large files to emails and troubles from format incompatibilities. When everyone refers to a single source of truth—“the latest data centrally managed”—mistakes such as “discrepancies between on-site and designer understanding” or “discussing based on outdated drawings” can be prevented.

In this way, cloud sharing of point cloud data becomes the information foundation that supports disaster response comprehensively, including remote design support, rapid client review, and record storage. Maximizing use of digital data reduces travel and time losses, enabling speedy and accurate restoration activities.

Field Use of Portable and Safe Simplified 3D Surveying

Until not long ago, performing high-precision 3D surveying required bulky equipment and specialized technicians. But now, field engineers can easily acquire 3D point cloud data with portable small devices. Examples include small 3D scanners that connect to smartphones or tablets and point cloud measurement apps that utilize built-in smartphone cameras and LiDAR—literally “surveying instruments that fit in your pocket.” These simplified 3D surveying tools are highly effective for initial response at slope failure sites.

High-portability devices allow rapid arrival at collapsed sites in mountainous areas by carrying equipment on foot. Even where roads are severed and large equipment cannot enter, personnel can walk to a safe distance to take measurements without helicopters or heavy machinery. Once on site, you can start the device and complete a point cloud scan in a matter of minutes, ensuring valuable initial response time is not wasted. The lack of complex setup and advanced operation training means site personnel can perform measurements themselves on the spot, which is a significant advantage.

From a safety standpoint, portable 3D surveying is also excellent. With small devices, you can flexibly measure from just outside the danger zone, avoiding the risk of carrying heavy tripods close to the collapsed slope. For example, with a smartphone you can operate it single-handedly while standing at a safe distance from the collapse site, always keeping yourself in a stance that allows quick evacuation. During measurement, point clouds are displayed on the screen in real time, so you can confirm that the required range is being scanned without entering hazardous areas. If something is missing, you can add inputs from a safe zone—there is no need to enter danger areas unnecessarily.

Additionally, these simplified 3D surveying devices can be carried by each person at all times. Since it is difficult to predict when and where a collapse will occur, having a portable surveying device means you can immediately take it out and start measuring when needed. Even before a specialized surveying team arrives, a technician present at the site can collect basic data as part of the initial response. This directly speeds up disaster response; for small-scale collapses, the acquired data may be sufficient to formulate an emergency restoration plan on-site. The “always-available, anyone-can-use, instant” simplified 3D surveying technology is truly a powerful tool for rapid response at slope failure sites.

Conclusion: Rapid Recovery Support for Slope Disasters Using 3D Surveying Technology

For landslide disasters such as slope failures, initial information gathering and appropriate decision-making are key to preventing further damage and achieving early recovery. 3D surveying technology can accurately and quickly reveal the damage that conventional methods could not fully capture. By correctly grasping the affected area, terrain, and soil volume with point cloud data, restoration plans become more precise, enabling safe and efficient work. Sharing and using that data via the cloud builds collaborative structures that transcend the boundaries between the field and remote locations, dramatically speeding up decision-making. Equipping portable simplified 3D surveying tools makes rapid on-site response possible when needed, which can minimize damage.

One of the solutions that can perform point cloud scanning, volume calculation, and cloud sharing in a one-stop manner is our company’s offering, [LRTK](https://www.lrtk.lefixea.com). With LRTK, you can obtain high-precision 3D point cloud data of a collapse site with simple smartphone operations, calculate the volume of collapsed soil on the spot, and share it via the cloud. For example, scanning a slope failure location from a safe position automatically generates a point cloud consisting of tens of millions of points, and the volume of collapsed soil and the missing volume of the collapsed slope are immediately quantified. Measurement results can be uploaded to the cloud with the press of a button, enabling design staff and clients in remote offices to start reviewing and deliberating in real time. The system is designed so that technicians without specialized knowledge can intuitively handle it on-site, making it truly a tool that supports rapid response at disaster sites. As a preparedness measure for slope failures and to strengthen initial response capabilities in case of emergency, consider utilizing such advanced 3D surveying technologies. Rapid and accurate restoration responses using these tools will greatly contribute to reducing damage and ensuring on-site safety.