In recent years, disasters involving slope collapse associated with heavy rain and earthquakes have occurred frequently across many regions. When slopes along mountainsides or beside roads collapse, soil and rock can bury roads and buildings, causing serious disruption to local transportation networks and residents’ lives. Moreover, collapse sites carry the risk of secondary hazards, demanding prompt recovery measures. For that reason, it is extremely important during the initial response phase to accurately ascertain the damage and develop a rapid and safe restoration plan. This article outlines the scope of damage from slope-collapse disasters and key points for initial response, discusses the limitations of conventional surveying methods, and introduces the advantages of the latest 3D surveying (point cloud scanning) technologies for on-site assessment. It also explains creating three-dimensional models of current terrain and calculating the volume of collapsed material, as well as remote support via data sharing, and concludes with an example of a rapid 3D surveying solution—LRTK—that leverages these technologies for swift recovery support.

Damage Caused by Slope-Collapse Disasters and the Importance of Initial Response

When a steep slope collapses, massive amounts of soil and rock can fall to the foot of the slope in an instant, causing severe damage such as road disruptions, structural destruction, and threats to human life. In particular, on mountain or coastal roads, slope collapses can isolate settlements or sever major arteries. At disaster sites, life-saving operations and prevention of secondary hazards are top priorities, but simultaneously information must be gathered to plan early recovery work. Conducting an accurate assessment during the initial response is directly linked to establishing a safe work system and considering appropriate restoration measures. Misjudging the scale of the collapse can lead to incorrect arrangements of personnel and heavy machinery or wrong choices of construction methods, resulting in delays and additional costs. To advance recovery quickly and effectively, it is essential to accurately determine the affected area and the severity of damage immediately after the collapse.

As a concrete example, the large-scale debris flow disaster that occurred in Atami City, Shizuoka Prefecture in July 2021 used comparisons of pre- and post-disaster terrain data (point cloud data) to rapidly identify the spread and outflow volume of collapsed material, which helped in assessing damage and preventing secondary hazards. In this way, obtaining quantitative understanding of the site in the early stages enables subsequent responses to proceed smoothly and safely.

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

At a slope-collapse site, it is necessary to accurately determine "which area collapsed," "how the terrain changed due to the collapse," and "how much soil and sediment collapsed or accumulated". The affected area refers to the extent reached by the collapsed slope or the outflowed sediment; without accurately defining this, it is impossible to set safe work zones or no-entry areas appropriately. It is also necessary to thoroughly record the shape changes caused by the collapse (height and gradient of the collapsed slope and the accumulation geometry of the collapsed material). These provide critical clues when considering restoration methods—for example, without knowing the longitudinal and cross-sectional profiles of the collapsed area, it is impossible to design slope reformation or reinforcement works.

Among these factors, accurately determining the volume of collapsed material is particularly important. Knowing the amount of soil lost by collapse and the volume of sediment deposited on roads numerically allows estimation of the soil removal and refill volumes required for recovery works. This forms the backbone of recovery planning, directly affecting the number of dump trucks and transport trips, heavy-equipment operating hours, and required material quantities in the construction plan. Moreover, for disaster recovery of public infrastructure there are often reporting obligations, and accurate reporting of collapse scale (volume of collapsed soil and affected area) is indispensable for administrative procedures and disaster recovery subsidy applications. From the perspectives of safety assurance, restoration design, and administrative reporting, it is required to comprehensively and accurately grasp the affected area, shape, and volume.

Why Conventional 2D Surveying and Photo Records Are Insufficient

For information gathering during initial response, planar survey maps and photographic records have traditionally been used. However, at large-scale slope-collapse sites these conventional methods are often inadequate. Typical surveying involves staff risking proximity to the collapse site to measure heights and distances at points around the area, from which plans and cross-sections are derived. Cross-sections inferred from a limited number of survey points make it difficult to fully capture complex terrain changes, and volume calculations of collapsed material are prone to error. Particularly for highly undulating terrain like collapsed slopes, 2D drawings alone make it hard to visualize the complete site and can lead to overlooking details.

Photography is also important for records, but photos alone cannot accurately measure scale or depth. Photographs are visual reference materials and it is difficult to derive precise dimensions or volumes from them (unless specialized photogrammetry techniques are used, which also takes time). With recovery work being a race against time, conventional methods that yield limited, slow information on-site may fail to provide the data necessary for planning restoration.

Furthermore, manual surveying involves danger. Immediately after a collapse, the ground is unstable and at risk of further collapse, making it hazardous for personnel to approach for measurements. Keeping a safe distance limits the ability to measure, and sometimes it is necessary to forgo measuring critical points. As described above, 2D surveying and photo records alone are insufficient to capture slope-collapse damage in a three-dimensional, quantitative manner, presenting challenges in both accuracy and safety.

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

One promising solution to these challenges is on-site measurement using 3D surveying (point cloud scanning). Point cloud scanning acquires countless measurement points using laser scanners or photogrammetry techniques and records site terrain and structures as a high-density collection of points (point cloud data). Performing 3D surveying at slope-collapse sites allows acquisition of the collapsed slope and surrounding terrain as a complete digital three-dimensional model. This offers the following major advantages:

• Precise and comprehensive measurement: Point cloud data can capture site details down to millimeter-level precision. Since the irregularities of collapse terrain and the shapes of sediment deposits are recorded without omission, the damage can be understood three-dimensionally, including areas that are hard to see. Compared to manual spot measurements, point clouds provide far denser information.

• High-precision calculation of volumes and dimensions: From acquired point clouds, software can freely perform volume calculations and dimensional measurements as described later. Even for complex shapes, accurate soil-volume calculation is possible using mesh methods, yielding much more reliable figures than estimates based on experience or intuition. In practice, there are reports where soil-volume calculations using point-cloud data achieve errors as low as about 1–2% compared to conventional methods.

• Dramatic reduction in work time: 3D scanning is extremely fast. Modern 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 soil-volume measurement and calculation previously required four people working for one week (a total of 28 person-days), switching to drone aerial photography to generate and analyze point clouds reportedly completed the task with two people for one day (2 person-days). By using point-cloud technology, the time and manpower required for initial information collection can be dramatically reduced.

• Improved safety: Many 3D surveying devices can measure remotely, enabling scanning from a safe position without entering the collapse zone. For instance, laser equipment can be fired from the opposite bank or a distant high point, or drones can be flown overhead to acquire terrain data without people entering hazardous areas. This provides necessary information while avoiding the risk of secondary hazards.

• Use of digital records: 3D models obtained as point cloud data become digital disaster records. They preserve detailed damage conditions that paper drawings and photos cannot fully represent, enabling future verification and use in post-event reporting. Digital data are also easy to copy and share, and when combined with cloud services described later, multiple stakeholders can concurrently access and work with the information.

In these ways, 3D surveying surpasses conventional methods in accuracy, efficiency, and safety. Recently, even without expensive dedicated equipment, familiar devices such as iPhone and iPad have become capable of point cloud scanning, and such accessible 3D surveying technologies hold great promise for disaster response.

Constructing 3D Models of Current Terrain and Calculating Collapsed Soil Volumes

Using point cloud data obtained by 3D surveying, you can immediately construct a three-dimensional model of the damaged terrain caused by slope collapse and accurately calculate the volume of collapsed soil. The specific procedure is to first scan the post-collapse terrain to obtain high-precision point cloud data. If possible, compare this with pre-collapse terrain data or a design-time ground model to calculate the difference and determine the volume of soil that flowed out (the amount lost by collapse).

For example, when a road slope has collapsed, the volume of the void created by the collapse (the missing portion of the slope) and the volume of soil accumulated on the road or valley floor can each be measured from point cloud data. If pre-collapse original geometry is available from design drawings or past survey data, use that as the reference surface; if not, it can be estimated from the shapes of neighboring intact slopes. By calculating the difference between the reference surface and the current point cloud model, you can obtain the volume of newly created voids or accumulated sediment due to the collapse down to millimeter accuracy.

Beyond volume calculation, various information can be derived from the 3D model: generate longitudinal or cross-sectional views at arbitrary locations, measure the plan-projected area of the collapse, calculate height and gradient of the collapsed slope, and obtain any dimensional data needed for restoration design. All of these analyses can be done on a PC in the office, so the necessary data are available without additional on-site surveying. In particular, for soil volumes it is easy to change the measurement range and recalculate from a single acquired point cloud. For example, if you later want to add another collapsed section to the initially calculated area, you can handle it on the data without new fieldwork. Point-cloud-based volume calculation is therefore highly flexible, allowing immediate recalculation to reflect changing conditions.

As a more advanced use, you can overlay planned design models on the acquired current point cloud. During planning of restoration methods, layering 3D design data for planned fills or reinforcements onto the point cloud makes it intuitive to see discrepancies with the field. Using systems that color-code differences between the point cloud and design model, you can instantly see where and how much fill is required to restore the original shape or how much excess sediment should be removed. This difference analysis makes required fill and excavation volumes visible and informs restoration design, improving the accuracy of construction planning.

Using Volume Data for Removal Planning, Construction Quantities, and Restoration Method Selection

Accurate soil-volume information from point cloud data is extremely useful when creating concrete construction plans for restoration. For instance, when planning the removal of collapsed sediment, calculated soil volumes allow precise estimation of the number of dump trucks required, the number of round trips, and the capacity arrangements for disposal sites. Traditionally, the amount of collapsed soil was sometimes estimated based on the site supervisor’s experience or visual judgment, but calculations based on point cloud data enable plans backed by solid evidence. Decisions such as "how many more dump trucks are needed" or "how much residual soil will remain to process" can be made based on data, leading to more efficient operations.

Similarly, point cloud data are powerful for determining construction quantities for restoration (required fill material, quantities for slope stabilization works, etc.). You can digitally simulate how much fill is needed to restore a collapsed slope to its original shape, or determine the scale of a new retaining wall to be installed. For example, by virtually filling the collapsed terrain on the point cloud, the required soil volume is immediately calculated, and any surplus soil produced in the process is shown simultaneously. Such quantity data are key to decisions about whether additional soil must be procured or whether stored residual soil will be sufficient. Knowing accurate quantities in advance allows appropriate procurement planning and cost estimation for materials and equipment, helping restoration work proceed smoothly.

Furthermore, 3D data are useful for evaluating restoration methods. Slope-collapse recovery is not just about returning soil to its original place but requires stabilization measures to prevent re-collapse. Selecting the optimal measures from options such as mortar spraying, slope-frame works, anchor installation, or retaining wall construction requires correct understanding of the collapsed slope’s geomorphology and scale. By viewing the point cloud model, designers can understand in 3D the slope angle, presence of exposed bedrock, and relationship to surrounding terrain, making it easier to choose appropriate methods. For example, the data can support judgments like "the volume of collapsed soil is large and the entire slope is unstable, so a large retaining wall is required" or "the collapse scale is small, so for rapid recovery we can use sandbags and simple netting measures."

As described above, detailed point-cloud data support decision-making from planning through construction stages of recovery. Data-driven planning reduces ad-hoc rework at the site and is the key to achieving safe and efficient restoration.

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

The benefits of 3D point cloud data do not end with on-site measurement. By sharing acquired data on the cloud, stakeholders can immediately confirm and analyze the situation from remote locations, which is a major advantage. Disaster recovery requires multiple stakeholders—municipal staff responsible for the site, designers, and clients (project owners)—to share information and make decisions, and cloud point-cloud sharing greatly streamlines this process.

For example, when a field worker uploads point cloud data and site photos from a smartphone or dedicated device to the cloud, design teams in the office and distant supervisors or clients can instantly view the 3D model. There are systems that allow manipulation and measurements of point cloud data via a web browser without each participant having to install special software or prepare a high-performance PC. 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 as well, three-dimensional models make it easier to intuitively understand conditions that are hard to grasp from text or still images, helping them make quicker judgments about restoration methods and budget allocations.

By storing data in the cloud, centralized record management also becomes possible. If you save point clouds and photos in chronological order from immediately after the disaster through completion of restoration, the data will aid post-event verification and report preparation. For example, by regularly scanning restoration progress and updating the cloud, you can trace terrain changes across stages such as "immediately after disaster → emergency restoration → final restoration completed." This is important both as evidence that restoration was performed appropriately and as lesson data for future similar disasters.

Additionally, cloud-shared data can be simultaneously referenced and jointly examined by stakeholders as needed. It is realistic to rotate the point cloud model during an emergency meeting while sharing the screen to review the damage. This avoids the hassle of emailing large files or format-compatibility issues. When everyone refers to a single managed up-to-date dataset, mistakes such as "mismatched understanding between the site and designers" or "working from outdated drawings" can be prevented.

Thus, cloud sharing of point cloud data becomes an information foundation that supports end-to-end disaster response: remote design support, rapid client review, and record archiving. Maximizing use of digital data reduces travel and time loss and enables swift, accurate restoration activities.

Field Use of Portable, Safer Simple 3D Surveying

Until not long ago, high-precision 3D surveying required bulky equipment and specialized technicians. Nowadays, however, field technicians can easily obtain 3D point cloud data using portable small devices. Examples include small 3D scanners that connect to smartphones or tablets, and point-cloud measurement apps that use smartphone cameras or built-in LiDAR—literally "surveying instruments that fit in your pocket." These simple 3D surveying tools are highly effective for initial response at slope-collapse sites.

Highly portable devices allow rapid access to mountain-site collapses on foot. Without helicopters or heavy machinery, personnel can walk to safe positions and perform measurements, enabling response at sites where large equipment cannot reach due to road disruption. Once on site, you can start the device and complete a point cloud scan in minutes by walking around the area, so valuable initial response time is not wasted. They require no complex setup or advanced operation training, so field personnel themselves can perform measurements on the spot—another major appeal.

In terms of safety, portable 3D surveying is also superior. Small devices make it possible to measure from the outermost safe edge of a hazardous area, avoiding the risk of carrying heavy tripods close to a collapsed slope. For example, with a smartphone you can operate one-handed and scan from a position that maintains sufficient distance from the collapse, keeping you always in a posture that allows quick evacuation. During measurement, the point cloud is displayed on the screen in real time, so you can confirm whether the necessary area has been scanned without entering dangerous spots. If there is a gap, you can safely add additional scans from outside the hazard zone without venturing in.

Moreover, the fact that these simple 3D surveying devices can be carried by each person at all times is significant. In disaster response, it is unpredictable "when and where" a collapse will occur, but having a portable surveying device means you can immediately take it out and start measuring when needed. Even before a specialized surveying team arrives, an engineer on site can collect basic data as part of the initial response. This directly speeds up disaster response, and for small-scale collapses you may be able to draft an emergency restoration plan on the spot from the acquired data. Truly, simple 3D surveying technology that is "always available, usable by anyone, and ready immediately" becomes a powerful tool for rapid response at slope-collapse sites.

Summary: Rapid Slope-Disaster Recovery Support via 3D Surveying Technology

In slope-collapse and other landslide disasters, gathering information and making proper decisions in the initial stage are keys to preventing escalation of damage and achieving early recovery. 3D surveying technology reveals damage conditions that conventional methods could not fully capture, with accuracy and speed. By correctly understanding the affected area, terrain, and soil volumes through point cloud data, restoration planning becomes more precise, enabling safe and efficient work. In addition, immediate cloud sharing and utilization of that data build collaborative frameworks beyond the site, dramatically speeding up decision-making. Equipping portable simple 3D surveying tools allows rapid on-site response when needed and helps minimize damage.

One solution that can perform point cloud scanning, volume calculation, and cloud sharing in a one-stop workflow is the product our company provides, [LRTK](https://www.lrtk.lefixea.com). With LRTK, simple smartphone-based operation enables acquisition of high-precision 3D point cloud data of collapse sites, on-the-spot calculation of the volume of collapsed soil, and cloud-based sharing. For example, scanning a slope collapse from a safe location can automatically generate point clouds consisting of tens of millions of points, immediately quantifying the amount of collapsed material and the missing volume of the slope. Measurement results can be uploaded to the cloud with the push of a button, allowing designers and clients in remote offices to begin real-time review and consideration. The system is designed so that even technicians without specialized knowledge can intuitively operate it on site—truly a tool to support rapid response at disaster sites. As preparation for slope collapse and to strengthen initial-response capabilities in the event of an incident, consider utilizing such advanced 3D surveying technologies. Rapid and accurate restoration responses will greatly contribute to reducing damage and ensuring safety at the site.