Soil investigation, which underpins building and civil engineering works, is indispensable for determining ground safety and soil suitability. Traditionally, borehole surveys, plate load tests, and even visual inspections of topography and geology have been performed. These methods are important for obtaining subsurface information, but the areas they can investigate are limited to points or restricted regions, and they have limitations in capturing wide-area surface information and three-dimensional conditions.

For example, borehole surveys only provide columnar data at the drilled locations, and plate load tests are limited to the bearing capacity around the test site. Visual terrain observations by experienced personnel also carry the risk of overlooking subtle elevation changes or long-term variations over wide areas. Relying solely on traditional methods makes it difficult to understand conditions between survey points or the overall terrain, and can fail to capture ground heterogeneity or slight deformations.

Point cloud scanning for on-site 3D visualization has therefore attracted attention. By utilizing laser measurement (LiDAR) and photogrammetry, point cloud scanning technology can capture the terrain as-is in a short time as 3D data composed of a large number of measured points. This provides wide-area, high-density surface information that conventional soil surveys could not obtain, greatly contributing to an objective understanding of ground conditions.

This article explains the innovations point cloud scanning brings to soil investigation from the following perspectives. Now, let’s look step by step at how point cloud scanning specifically revolutionizes soil investigation.

Advantages of 3D Terrain Visualization Achieved with Point Cloud Scanning

The biggest feature of point cloud scanning is that it can capture the site’s shape as-is over a wide area. Terrain data that previously required manual measurement point by point can, with laser scanners or drone photogrammetry, be obtained in a short time as a collection of millions of points. In other words, the entire survey area can be recorded as high-density point cloud data, and cross-sections or dimensions at any location can be extracted later. This yields far more information than traditional surveys that provide only limited points, and significantly reduces the likelihood of oversights.

Because point cloud data contain 3D spatial coordinates (X, Y, Z), displaying them in dedicated software allows three-dimensional observation of terrain and structures. 3D models formed from numerous points look realistic like photographs, enabling immediate recognition of surface irregularities, slopes, and low-lying areas where water is likely to flow. Subtle undulations that are easy to miss in conventional visual inspections can be intuitively understood by viewing colored point clouds. It is, in a sense, like obtaining a digital twin of the entire site, dramatically increasing the objectivity and persuasiveness of terrain understanding.

Because of these advantages of 3D visualization technology, the use of point cloud data is accelerating in the civil engineering and construction sectors, supported by the Ministry of Land, Infrastructure, Transport and Tourism’s “i-Construction” initiative. Digitizing the entire site from surveying through design, construction management, and maintenance is expected to improve productivity and quality control. In soil investigation as well, incorporating point cloud scanning technology makes it possible to achieve more accurate current-condition assessments and planning than before.

Strengths in Before-and-After Records of Excavation, Embankment, and Ground Deformation

Point cloud data are powerful for recording terrain changes caused by construction or disasters because comparing data from different times makes it possible to detail the amount of change. For example, if point cloud measurements are taken before and after construction, differences between the two can be used to accurately calculate excavated volume and fill volume. Previously, it was necessary to create longitudinal and cross sections from survey data and carry out time-consuming volume calculations, but with point cloud data the differences can be automatically analyzed in software to quickly determine soil volumes. Because the entire site is covered, localized missed excavations or insufficient fills are not overlooked.

For instance, in soil contamination removal work on former factory sites, recording the contaminated soil before and after excavation with point clouds allows precise post hoc verification of the removal area and excavation depth. This serves as more reliable evidence than photos alone and provides objective documentation supporting the adequacy of measures.

In construction management, overlaying acquired point clouds with the design model allows immediate verification of whether the finished shape matches the plan. If embankment areas have not reached the required height or some spots have been over-excavated, they can be identified at a glance and corrected early. Such before-and-after comparisons with point clouds improve efficiency and accuracy in as-built (post-construction shape) management.

Point cloud usage is also useful for observing ground deformations caused by earthquakes or heavy rain. Scanning slopes or ground before and after a disaster enables rapid assessment of the extent and magnitude of collapse or deformation. Using the obtained 3D data to calculate collapsed soil volumes, consider restoration methods, and evaluate the risk of secondary disasters allows for more appropriate decision-making.

Moreover, comparing point clouds obtained through regular inspections makes it possible to quantitatively grasp, over time, slope settlement, long-term changes in embankments, and even slight distortions of structures. In the past, staff had to record such changes on-site by visual inspection and simple measurements, but point cloud data visualize changes across the entire site and contribute to early detection of abnormal signs.

Thus, before-and-after records using point cloud scanning can be applied widely—from quality control of earthworks to infrastructure maintenance and disaster response—providing a powerful means to capture terrain changes with higher accuracy and reliability than conventional methods.

Improving Objectivity and Traceability of Investigation Reports

Using point cloud data obtained by digital measurement in investigation reports dramatically increases their objectivity and persuasiveness. Traditional reports centered on textual findings, some photos, and planar drawings, which sometimes failed to convey the whole site or fine details. By using point cloud data, reports can include 3D models of the entire site and detailed terrain maps, serving as verification of the investigation results. For readers, conditions that were hard to grasp from numbers and planar maps become visually clear, greatly enhancing report credibility.

Furthermore, point cloud data become a digital archive that records the entire site at the time of investigation. If later someone wants to recheck the ground conditions at that time or another expert wants to verify the measurements, opening the stored point cloud recreates the site virtually. For example, if unexpected ground settlement is discovered after project completion, one can revert to the point cloud obtained during the initial soil investigation to closely examine whether there were any early signs of terrain or deformation. Details that might have been missed in paper reports or photos can be examined across time with 3D data.

Point clouds are large sets of coordinate data, and with appropriate software anyone can measure the same point’s elevation or distance. Preserving data with such reproducibility is critically important for ensuring traceability (the ability to track) of investigation results. Having objective data that third parties can independently verify increases confidence in reports and facilitates accountability. Investigation reports based on point clouds become evidence-based reports that earn greater trust from clients and stakeholders.

In recent years, cloud services that allow point cloud data to be shared over the Internet have emerged. Stakeholders can view and measure the site’s 3D model in a browser from anywhere, confirming details that reports cannot fully convey. The traditional one-way reporting style from investigators to recipients is shifting toward two-way data verification through data sharing, which also contributes to improved objectivity and transparency.

Improved Efficiency and Versatility by Combining High-precision GNSS (LRTK) with Point Cloud Scanning

To maximize the benefits of point cloud scanning, it is essential to provide accurate positioning information to that 3D data. High-precision GNSS positioning plays a powerful role here. By using RTK (real-time kinematic) GPS in combination, centimeter accuracy (half-inch accuracy) coordinates can be assigned to each point during point cloud acquisition. Traditionally, integrating acquired point clouds into a map coordinate system required setting reference points on-site or performing post-processing against known points. But using RTK-GNSS makes it possible to obtain high-precision coordinates in real time on site, greatly reducing the need for cumbersome reference-point surveying and post-processing. There is no longer a need to call a surveying crew every time point clouds are acquired, allowing small teams to quickly obtain current 3D data.

Recently, technologies that make RTK positioning even more convenient have appeared. For example, LRTK consists of a compact high-precision GNSS receiver that can be attached to a smartphone and a dedicated app, turning the smartphone into a surveying device—an innovative solution. Large stationary equipment and complex setup, typical of the past, are unnecessary; simply starting the device on site enables instant centimeter-level positioning (half-inch accuracy). It also supports the centimeter-class augmentation service (CLAS) of the Michibiki quasi-zenith satellites, allowing reception of correction information directly from satellites to maintain positioning accuracy even in mountainous areas or regions with poor radio coverage. Thanks to such compact and convenient GNSS technologies, surveys combining point cloud scanning with high-precision positioning have become more accessible.

Combining high-precision GNSS and point cloud scanning is expected to improve on-site efficiency and broaden applicability. For example, field surveys that once required a team including a surveyor and took half a day can now, in some cases, be completed in a short time by a single engineer with just a smartphone. Reducing required personnel and equipment lowers costs and makes it possible to acquire current-condition data more frequently with limited resources. High mobility allows surveying across diverse sites—from flat development areas to mountainous farmland and dangerous, post-disaster sites—making the approach highly versatile. Being able to perform in-house 3D site surveys without waiting for specialized contractors enables timely terrain understanding and analysis, speeding up decision-making.

With the latest technologies that combine point cloud scanning and high-precision GNSS, soil investigation is poised for major change. Complex surveying tasks are evolving into simple surveying that anyone can perform, accelerating site digitalization and efficiency. By incorporating these new technologies into conventional methods, not only will survey accuracy improve, but report reliability and overall operational productivity will also increase dramatically. Why not take the next step into next-generation soil investigation using point cloud scanning and LRTK, and realize on-site DX (digital transformation)?