Easily Acquire Georeferenced Point Clouds with Your Smartphone: Start Survey DX with LRTK

Table of Contents

• What is a georeferenced point cloud?

• What does volume calculation from point cloud data mean?

• Challenges of traditional surveying methods and earthwork quantity calculation

• Advantages of point cloud measurement with a smartphone

• Easily obtain georeferenced point clouds with LRTK

• Volume calculations that can be streamlined with point cloud data

• Start survey DX with your smartphone: simple surveying using LRTK

• FAQ

In construction and civil engineering sites, volume calculation of earthworks such as embankments and excavations (earth quantity estimation) is an essential task for progress control and payment management. Traditionally, the common method was to measure terrain with surveying instruments, create cross-sections, and calculate volumes using the average end-area method. However, in recent years, 3D surveying using drones, laser scanners, and even smartphones has been spreading. By using point cloud data obtained with these technologies, it has become possible to determine earth quantities more quickly and with higher accuracy. This article first explains the basics of what a "georeferenced point cloud" is, then the methods and benefits of volume calculation using point cloud data, and finally the latest solutions that allow anyone to perform high-precision point cloud measurements with a smartphone. At the end, we also introduce a simple surveying method using LRTK that can be easily introduced.

What is a georeferenced point cloud?

Point cloud data is a collection of many measured points in space, where each point has X, Y, and Z coordinates (positional information) as three-dimensional data. When buildings or terrain are measured by laser scanners or photogrammetry, you can acquire millions of points on surfaces, and the assemblage of those points can express the shape of the object in detail. Simply put, a point cloud is a 3D model made up of countless points.

A georeferenced point cloud refers to point cloud data in which each point has numerical values based on a real-world coordinate system (for example, a public coordinate system or latitude/longitude). Normally, point clouds obtained by smartphones or conventional 3D scans are placed in an arbitrary local coordinate system (relative coordinates), so their position on a map is unknown as-is. In contrast, a georeferenced point cloud has the entire point cloud aligned (georeferenced) to surveying standards, so by looking at the coordinate values of each point you can know the actual geographical position (absolute coordinates) in real space.

With georeferenced point clouds, multiple point cloud datasets acquired at different times can be easily overlaid and compared, and they are easier to integrate with drawings or GIS data. Because each point is given an accurate scale, measurements of distance, area, and volume can be performed directly in real units (meters). For these reasons, georeferenced point clouds are very useful for as-built management of works and analysis of terrain changes over multiple time points.

What does volume calculation from point cloud data mean?

Calculating volume from point cloud data means using the acquired 3D point cloud model to determine the volume of embankments or excavations (fill volume / earth volume) within a certain area. There are two major representative methods. One is to compare point cloud data of the terrain acquired before and after construction and calculate the amount of earth added or removed from their difference. For example, in land development, by overlaying the pre-construction ground point cloud with the post-construction terrain point cloud and computing the height differences between them, you can automatically determine the amount of soil removed or placed. The other is a method for measuring the volume of an isolated pile of earth or stockpiled material. In this case, you specify the region of the embankment on the point cloud data, consider the surrounding ground as a reference plane (base), and calculate the volume of the portion that rises above it. In short, imagine subtracting the ground portion from a prism that covers the embankment to obtain the volume.

Traditionally, calculating volume required converting point cloud data into a surface model such as a polygon mesh and computing the volume in CAD software. However, recently there are increasing numbers of dedicated point cloud viewers and cloud services that automatically calculate volume simply by uploading point cloud data and specifying the measurement area. Even without complex 3D modeling operations, we are entering an era where you can obtain fill volume and earth quantity with one click as long as you have point cloud data.

Challenges of traditional surveying methods and earthwork quantity calculation

Calculating earth quantities with traditional surveying often required considerable manual effort and time. Survey staff would measure heights at fixed intervals on site, create cross-sections or contour maps, and then calculate volumes from those. Measuring large embankment volumes often took multiple people several days. Because the shape was estimated from limited survey points, fine undulations of the actual terrain were often not fully captured, becoming a source of error. Surveying on steep slopes or unstable soils also carries safety risks.

In recent years, advanced equipment such as laser scanners and drone photogrammetry has appeared, but these also pose barriers in terms of introduction cost and required expertise, so not everyone can use them frequently. High-performance 3D scanners are very expensive and require operator proficiency. Drone surveying is affected by weather and flight restrictions and requires dedicated operators and data processing time. Moreover, when comparing point cloud data obtained by different measurement devices to calculate volumes, they must be unified into the same coordinate system (aligned to reference points). This requires installing sufficient reference points on site or performing point cloud registration in post-processing, adding further effort. In other words, high-accuracy earth quantity estimation has historically demanded advanced surveying skills and labor.

Advantages of point cloud measurement with a smartphone

Modern smartphones are equipped with high-performance cameras and sensors, and using dedicated apps you can scan the surrounding environment to obtain point cloud data. In particular, if you use the LiDAR (light detection and ranging) sensor built into the latest iPhones and iPads, you can instantly 3D scan and generate point clouds of spaces several meters (several ft) ahead. The biggest advantages of smartphone point cloud measurement are its simplicity and mobility. Since you only need a pocket-sized device, you don't have to carry heavy equipment and can measure the site whenever you like. The significantly lower introduction cost compared to dedicated equipment is also attractive, expanding the possibility that anyone can perform everyday 3D surveying.

However, smartphone-only point cloud scanning has some challenges. For example, the acquired point cloud may not be tied to absolute coordinates of the site, leaving the position and elevation references unclear. When scanning while walking over a wide area, small errors in the smartphone's internal sensor-based self-position estimation can accumulate, gradually distorting the ground shape. Also, positioning accuracy (location accuracy) of typical smartphone-embedded GPS has errors on the order of meters, which is insufficient for precise surveying. For these reasons, additional measures were needed to further improve the accuracy and reliability of point cloud data captured by smartphones for surveying and design use.

Easily obtain georeferenced point clouds with LRTK

LRTK has emerged to solve the above issues. LRTK is an ultra-compact RTK-GNSS receiver that attaches to a smartphone and enables centimeter-level high-precision positioning with a smartphone based on satellite positioning information. RTK stands for real-time kinematic, a technique that greatly reduces GPS positioning errors using correction data from a reference station. Combining LRTK with an iPhone or iPad allows you to assign global coordinates (absolute coordinates) in real time to every point in the captured point cloud data. Because you can always track your position with cm level accuracy (cm level accuracy, half-inch accuracy) while scanning, there is no worry that the point cloud will become distorted as you walk.

The usage is simple: attach the dedicated LRTK receiver to the smartphone, launch the app, point the camera, and walk. No special calibration work or expert settings are necessary, and anyone can perform high-precision point cloud scans with intuitive operation. It is revolutionary that a single pocket-sized device can replace the costly equipment and specialized knowledge that were previously necessary for surveying work. For example, with LRTK you can quickly walk and scan terrain even on a large development site, display the acquired point cloud on the smartphone screen in real time, measure the distance between any two points, or calculate the volume of an embankment on the spot. There is no need to bring a heavy laser scanner or laptop PC to the site, and one person can easily collect precise surveying data.

Volume calculations that can be streamlined with point cloud data

Switching to volume calculation using point clouds dramatically improves the efficiency of earth quantity calculations. For example, at a large development site where a survey team of four previously took one week (a total of 20–30 person-days) to perform measurement and calculation work for as-built earth quantities, switching to creating point clouds via drone aerial photography and calculating volumes with dedicated software reduced the task to two people in one day (2 person-days). This is because the intermediate steps in the traditional process—surveying, drafting, and manual calculation—can be greatly reduced when point cloud data are measured and results are obtained immediately in software. Reducing personnel and days not only lowers costs but also directly improves overall construction productivity by enabling rapid progress tracking.

The comprehensiveness (coverage) and high density of point cloud measurement data are also major advantages. While manual surveying estimated shapes from cross-sections spaced tens of meters apart or from limited measurement points, point clouds cover the entire site with millions of points. Therefore, volume calculations can reflect fine bumps and local depressions or rises that were easily overlooked before, leading to improved accuracy. In fact, verification results have reported that earth quantities calculated from point clouds obtained by drones or laser scans differ little from values obtained by traditional methods, often within an error of 1–2%. From a safety perspective, point cloud surveying does not require personnel to enter dangerous slopes, allowing non-contact data collection that reduces worker risk. Additionally, once 3D point cloud data are acquired, they can be reused for other analyses later (creating cross-sections, monitoring deformation, etc.), so they have high asset value as digital records of the site.

Furthermore, point cloud data excel in immediacy of results. Because volumes can be calculated via the cloud within the same day as measurement, you can grasp quantities quickly and speed up on-site decision-making. For example, tasks that used to wait on specialized surveying results can be handled by on-site staff measuring daily point clouds and instantly calculating remaining soil volumes, enabling rapid optimization of the number of dump trucks to arrange or the operation plan for heavy machinery. Point cloud technology allows as-built management, which previously lacked real-time capability, to be completed at the site level, greatly advancing DX (digital transformation) in construction management.

Start survey DX with your smartphone: simple surveying using LRTK

High-precision measurement and volume calculation using 3D point clouds will become indispensable technologies for future site management. That said, historically these required specialized skills and expensive equipment, making them hard to adopt. Smartphone surveying solutions like LRTK greatly lower that barrier, enabling anyone to easily practice surveying DX. In fact, the Ministry of Land, Infrastructure, Transport and Tourism’s i-Construction initiative encourages the use of 3D surveying technologies, accelerating digitalization across the industry. In this trend, LRTK contributes to productivity improvement on site as a tool that balances ease of use and high accuracy.

Now that smartphones and small devices are sufficient, surveying and earth quantity calculations that used to require specialist contractors can be done by the users themselves. As a first step toward surveying DX, why not introduce smartphones and LRTK to your site? Start with simple surveying that anyone can handle and promote DX on the job.

FAQ

Q1. Can I obtain georeferenced point clouds without expensive 3D scanners or drones? A. Yes, it is possible. High-performance laser scanners and drones are certainly convenient for wide-area measurement, but there are ways to utilize point cloud technology even without such equipment. For small areas, recent smartphones (e.g., LiDAR-equipped iPhone/iPad) can easily acquire point clouds. Additionally, if high-precision positional information is required, combining a smartphone with a GNSS device for smartphones such as LRTK can enable georeferenced point cloud surveying with centimeter-level accuracy using inexpensive equipment. Photogrammetry, which generates 3D models from ground-based camera photos without using drones, is also an option. By selecting the optimal method according to site scale and purpose, you can acquire sufficiently practical point cloud data without costly equipment and perform volume calculations from that data.

Q2. Can it be used without specialized knowledge? Is smartphone surveying okay for beginners? A. Yes, modern point cloud measurement apps and viewers are designed to be user-friendly for beginners. Scanning with a smartphone is intuitive—just move according to the on-screen instructions—so no special skills are required. The LRTK app is designed so that positioning and point cloud scanning can be done by pressing a button, and cloud point viewers can be used without complicated settings. While advanced analysis requires experience, basic distance measurement and volume calculation can be learned after a few tries. Manuals and support information are well provided, so starting with small targets and gradually getting accustomed should allow you to use it without issue.

Q3. Can the volumes calculated from point clouds be trusted? How much error compared to traditional surveying? A. If point cloud data are acquired following appropriate procedures, the calculated volumes can be expected to have accuracy comparable to traditional methods. For example, earth quantity calculations using point clouds obtained by drone photogrammetry or terrestrial laser scanning are often reported to be within about 1–2% error compared to traditional cross-section methods. In other words, you can obtain values comparable to carefully measured traditional methods. However, achieving high-precision results requires sufficient reference point calibration during surveying and accurate alignment of point clouds (LRTK can automate this process). Noise or missing data in point clouds can be sources of error, so data cleaning such as removing unnecessary points is also important. Under proper conditions, point cloud surveying can match traditional surveying accuracy, and because it can measure wide areas densely, local oversights are reduced and reliable quantity estimation is achievable.

Q4. Doesn’t it take a long time to produce point clouds and calculate volumes on a smartphone? Isn’t data processing and calculation time-consuming? A. The time required from point cloud creation to volume calculation can be greatly shortened compared to traditional methods depending on the approach. Indeed, in the past, post-processing after laser scanning could take many hours with specialized software. But now there are cloud services that automate point cloud generation from photos and apps that provide immediate results from smartphone scans. For example, with drones you can upload photos to the cloud and receive point cloud models and orthophotos within a few hours; with smartphone scanning you can walk around for tens of seconds to a few minutes to acquire a point cloud, and in some cases the app displays volume calculation results immediately thereafter. Point cloud viewer processing has also been optimized, and for typical earth quantity calculations a computer can provide results almost in real time. This is overwhelmingly faster than manual calculation, so total task time can be drastically reduced. If data volume is large and you are concerned about the load on your own PC, cloud processing lets servers handle it for you.

Q5. Are point cloud survey results accepted as official as-built quantities? A. There is not yet a completely unified operational standard, but point cloud-based as-built management is increasingly being adopted officially. For public works ordered by national or local governments, under i-Construction guidelines the use of quantities calculated from point cloud data for as-built inspections is becoming more common. However, to treat them as official as-built quantities, procedures proving the reliability of the survey are required. For example, for photogrammetry you may need to install known reference points on site to verify accuracy; for laser scanning you should perform instrument calibration and cross-check errors with other methods. When reporting to the client, it may also be necessary to attach documentation showing the point cloud surveying accuracy and calculation methods. Nevertheless, point cloud measurements that meet conditions are expected to be recognized as official records and quantity estimation methods going forward. In fact, there are already sites where inspections were approved based on quantities measured from point clouds, and it is expected that reporting as-built quantities using point clouds will become a standard. It is advisable to initially use them in conjunction with traditional methods while actively leveraging the benefits of the new approaches.