A Must for Beginners! Recommended Way to Easily Start Drone Point Cloud Generation in the Cloud

Table of Contents

• What does generating a point cloud with a drone mean?

• Benefits of drone point cloud surveying

• Advantages of generating point clouds in the cloud

• Steps to start drone point cloud generation in the cloud

• Key points to succeed in drone point cloud generation

• Main use cases for drone point cloud data

• Recommendation for simple surveying with LRTK

• FAQ

In recent years, with advances in drones and 3D technology, the term “point cloud data” has become increasingly common on construction and surveying sites. Photographs taken by drones can be used to obtain terrain and structures as three-dimensional point cloud data, and this is being applied for construction measurements and as-built management. However, beginners may worry, “How do I get started?” or “Do I need expensive equipment or complex software?” In fact, recently, by taking advantage of cloud services, it has become possible to start drone point cloud generation easily without specialized knowledge or a high-performance PC. This article explains, in an easy-to-understand way, the basics of generating point cloud data with drones, the benefits of using the cloud, concrete steps to get started, and tips for success. At the end of the article, we also introduce a noteworthy tool, “LRTK,” that allows even beginners to experience simplified 3D surveying. If you’re interested in drone point cloud measurement but haven’t taken the plunge yet, please use this as a reference.

What does generating a point cloud with a drone mean?

First, point cloud data is three-dimensional data that represents objects in the real world as countless points. Each point contains X, Y, and Z coordinates (positions), and when the collection of points is displayed on a computer, the shape of the object can be reproduced three-dimensionally.

So how can a drone generate a point cloud? The common method is called photogrammetry. A camera mounted on a drone takes many photos from above of the terrain and buildings from various angles, and those photos are analyzed by specialized software or cloud services to generate a high-density 3D point cloud. The system matches common feature points that appear in multiple images and calculates the position of each point from differences in camera viewpoints.

There is also another method in which a lightweight laser scanner (LiDAR) is mounted on a drone to directly measure and obtain a point cloud. Laser measurement has advantages such as being able to capture the ground under trees, but the equipment cost and operational difficulty are high, making it a steeper hurdle for beginners to introduce immediately. In contrast, with photogrammetry, you can work with a commercially available camera-equipped drone and analysis software (or cloud service), so it is an ideal method for first-time point cloud generation.

Benefits of drone point cloud surveying

• Efficiency and labor savings: Drone surveying can measure areas that used to take several people several days in a short time by a single person. Because a drone can acquire a large amount of data at once even on a wide site, “misses” are reduced and the effort of additional surveys is minimized. In the construction industry, which faces a serious labor shortage, the large improvements in efficiency and labor savings are a major attraction.

• High-precision, comprehensive measurement: Point cloud data records objects with countless points, allowing more precise and comprehensive information than traditional point-by-point surveying. Because shapes can be digitally preserved down to millimeter units (millimeter-level (mm (0.04 in))), it is easy to re-measure dimensions at any location later. Even without drawings, accurate 3D models can be produced, helping improve quality control and the accuracy of design and construction.

• Improved safety: Laser measurement and drone photogrammetry are non-contact, so data can be safely acquired in hazardous areas where people cannot enter. High or steep slope surveys can be conducted remotely, reducing the risk of accidents during work. Many tasks that used to require working at height or traffic restrictions can now be minimized, contributing to on-site safety management.

• Smooth consensus building through data sharing: Acquired point cloud data can be shared with stakeholders as 3D models in the cloud. Supervisors or clients in remote locations can view the site three-dimensionally on a PC or tablet, making communication smoother. Information that was hard to convey with drawings or photos becomes obvious in 3D, enabling convincing explanations during as-built inspections or design-change discussions.

Because of these advantages, the Ministry of Land, Infrastructure, Transport and Tourism is promoting the use of ICT such as drone surveying under “i-Construction,” and point cloud technology has become a symbol of digital transformation (DX) in the construction industry.

Advantages of generating point clouds in the cloud

• No need for a high-performance PC: Point cloud generation traditionally requires a high-performance computer to process many images, but cloud services execute heavy computations on the server side. You can operate from a standard laptop or tablet on site, without having to prepare an expensive workstation yourself.

• Easy to get started: There is no need to install specialized software or perform complex configurations. A simple workflow is provided where you upload photos in a web browser and start analysis with a button click. User interfaces that even beginners can use without hesitation are available, greatly reducing the time required to learn software usage from scratch.

• Always access the latest technology: Because the cloud service provider updates algorithms and features daily, users always enjoy the latest versions of the technology. You don’t need to worry about updating software or compatibility. New point cloud processing techniques and AI-powered automatic classification features added on the cloud become immediately available.

• Easy team collaboration: With data in the cloud, it’s easier to share point cloud results among multiple people. If you invite stakeholders to the same project, each person can view and measure 3D data from a browser without installation. Remote members can share the situation in real time, facilitating collaborative work.

• Cost benefits: Cloud services are attractive because they can be started with low initial costs. In the past, software purchases and hardware investments of several hundred thousand yen were necessary, but with the cloud you can use what you need when you need it. Many services operate on monthly fees or pay-as-you-go models, making it easier to manage costs per project. This makes cloud services an economical choice for small operators who don’t use them frequently but still want to take advantage of the latest technology without waste.

Steps to start drone point cloud generation in the cloud

• Prepare equipment and flight plan: First, prepare the drone, camera, batteries, and other necessary equipment. For surveying, a drone equipped with a high-resolution camera is desirable. Plan the survey area and flight course in advance and set a route that efficiently covers the area. Aim for photo overlap rates of 70% or more both front-to-back and side-to-side for good results. Also check weather and wind conditions and choose a safe time to fly. Don’t forget to confirm drone regulations, such as whether the airspace allows flight or whether prior notification is required.

• Drone photography: Fly the drone according to the plan and take photos of the target area. Maintain planned altitudes and camera angles and acquire photos with high overlap evenly. Typically, an automatic flight app is used to follow a set route, flying parallel tracks in a zigzag while photographing the ground. If there are buildings or structures, shooting obliquely as well can reduce blind spots and yield a more complete point cloud. Monitor battery levels and aircraft condition at all times and conduct flights with safety first.

• Upload data to the cloud service: After shooting, access the cloud point cloud processing service platform. Create a new project in a web browser and upload the multiple photos taken on site. If there are many photos, you will be sending a large amount of data at once, so it’s best to use a high-speed, stable internet connection if possible. If the drone used has GPS, location information is embedded in the image files and will be automatically mapped on the cloud side. If you have known coordinate data (such as GCPs), upload them at this stage to help improve accuracy in later processing.

• Cloud point cloud generation (analysis): After uploading the photos, start the point cloud generation process on the cloud. Follow the service prompts and click the button to start; image analysis (feature matching and 3D reconstruction) will be performed automatically on the server side. Even projects consisting of dozens to hundreds of photos can generate point clouds in a relatively short time thanks to the cloud’s high-performance computing environment. Processing time can range from tens of minutes to several hours depending on the data volume, but progress can be checked in the browser. While waiting, users can proceed with other tasks, which is also efficient from a productivity standpoint.

• Check and use the results: When processing is complete, review the generated point cloud data on the cloud. Use the platform’s 3D viewer to rotate and zoom the point cloud and check quality. Confirm whether the target is properly reproduced and whether there are missing parts. Some services provide filter functions to remove unnatural noise points. If everything looks good, download the point cloud data as needed for import into your CAD software, or perform volume calculations and cross-section creation in the cloud. You can also use generated orthophotos (stitched top-down images) and 3D mesh models. Share the finished deliverables with stakeholders on the cloud or attach them to reports to support on-site operations.

Key points to succeed in drone point cloud generation

• Ensure sufficient photo overlap: The quality of point cloud generation is greatly affected by the degree of overlap between photos. Secure 70–80% overlap front-to-back and side-to-side so the same ground areas are well captured in adjacent photos. Insufficient overlap can cause gaps or reduced accuracy in the point cloud.

• Consider weather and shooting conditions: In photogrammetry, it is important to shoot in conditions that produce bright, clear images. Choose times of day with good sunlight and avoid flying in rain or strong winds. Don’t leave camera settings entirely to auto; fix focus and ensure a shutter speed that prevents blur. If exposure varies widely across a set of photos, it can affect analysis accuracy, so shooting in manual mode to keep brightness consistent is effective.

• Improve accuracy when necessary: If elevation and coordinate accuracy are important, use an RTK-capable drone or ground control points (GCPs) to provide a geodetic reference to the data. These give the generated point cloud precise latitude, longitude, and height information, achieving survey-grade accuracy. Although this increases initial investment and effort, it should be considered for applications that require high accuracy, such as public surveys or design work.

• Practice on small areas first: Rather than tackling a vast site right away, start with a small area or a familiar structure. Working with a small dataset lets you experience the entire workflow, verify results, and identify improvements for next time. Gradually expand the scale to improve skills steadily while minimizing the impact of mistakes.

• Thoroughly follow regulations and safety management: Drone flights are subject to legal rules. Always confirm no-fly zones and obtain necessary permits in advance. Also perform checks of batteries and GPS, and ensure a monitoring system to keep third parties out of the site—never neglect safety procedures. On-site, consider those around you and operate cautiously; executing work with zero accidents is most important.

Main use cases for drone point cloud data

• Volume calculations and as-built management: From obtained point cloud data, you can calculate the volumes of fill and excavation or record post-completion terrain as as-built maps. For example, by scanning the ground before and after construction with a drone and comparing them, you can accurately determine the amount of soil moved. You can also take cross-sections from point clouds to verify whether constructed elements meet design dimensions and shapes. Point cloud data makes high-precision as-built management that used to be difficult much easier.

• Creating existing-condition maps and design review: Drone point clouds serve as base data for high-density existing-condition surveys. You can create arbitrary plan views and cross-sections from the acquired 3D point cloud, helping designers understand the site accurately. It’s possible to overlay design models (CAD data) on the point cloud to check for clashes or to simulate the suitability of planned routes. Intuitive 3D data helps find issues that might be overlooked on traditional 2D drawings.

• Progress management and stakeholder sharing: If construction progress is periodically recorded with drone point clouds, site changes can be tracked over time. By overlaying point clouds from each survey, you can immediately see where and how much change has occurred, making the data useful for schedule management. Sharing these data via the cloud with clients and team members lets those who cannot visit the site see realistic conditions. Explaining with a 3D model at regular meetings speeds up consensus building.

• Infrastructure inspection and disaster response: Point clouds from drone-mounted cameras or LiDAR are used for inspection of infrastructure such as bridges, dams, and tunnels, as well as for rapid situational assessment at disaster sites. Because data can be collected safely in places humans cannot enter, they are powerful for monitoring slopes at risk of collapse or measuring topographic changes after floods. The basic approach is still photographing and converting to point clouds, so skills learned in peacetime will be useful in emergencies.

Recommendation for simple surveying with LRTK

LRTK is an innovative solution that allows beginners to easily start 3D surveying. The concept is smartphone + RTK: attach a small positioning device called the “LRTK Phone” to a handheld iPhone, start the dedicated app, and you can perform high-precision point cloud measurement. It realizes cm-level positioning (cm level accuracy (half-inch accuracy); Real-Time Kinematic: RTK) on a smartphone, enabling accurate position information to be attached to acquired photos and LiDAR scans. The simplicity of being able to survey a site alone with a single pocket-sized device is truly deserving of the term simple surveying. Even those without surveying experience can obtain 3D point cloud data by following the app’s instructions and holding up the smartphone, significantly lowering the barrier to field introduction.

Furthermore, LRTK seamlessly integrates data utilization with cloud services. For example, if you upload point cloud data obtained with LRTK or photos taken by a drone to the LRTK Cloud, coordinate-tagged point cloud models are automatically generated and can be edited and shared in a browser. Because you can handle large datasets without a high-spec PC, LRTK consistently supports projects from small sites to large-scale projects. LRTK, which lets you try the latest 3D technology while keeping initial investment down, is a perfect tool for on-site DX promotion based on the “start small and scale up” approach. Beginners interested in point cloud utilization should consider taking an easy first step using LRTK.

FAQ

Q: What equipment and preparations are needed for drone surveying? A: Basically, you need a drone body equipped with a high-resolution camera, a controller to safely fly the drone, batteries, and so on. Also prepare registration for the cloud service (or dedicated software) that will process the captured photos. If you want to align survey results with map coordinates, using high-precision GNSS (RTK-equipped drones or ground reference points) improves positional accuracy. In addition, check legal procedures in advance such as confirming the airspace to be flown, necessary permit applications, and aircraft registration (mandatory for drones of 100 g or more).

Q: Can beginners handle drone point cloud generation? A: Yes. In recent years, automatic flight apps for drones and the interfaces of cloud services have become well-developed, and beginners can obtain point cloud data by following basic procedures. However, safe operation and compliance with regulations are required for flying the aircraft, so it is recommended to practice at first and gain experience with relatively simple projects. Even if things don’t go as planned initially, you can steadily improve by experimenting on small sites and learning the tricks.

Q: Are there disadvantages to using cloud services? A: The main consideration is dependence on the internet environment. Because large photo datasets must be uploaded, unstable connections can slow processing or increase communication costs. Also, cloud service usage fees occur continuously. However, many services use pay-as-you-go models that require no initial investment, and in many cases this can be cheaper than purchasing on-premises software. If data confidentiality is a concern, choose a reputable, reliable service and check the terms of service regarding data handling.

Q: What level of accuracy can I expect from point cloud data? A: It depends on shooting methods and equipment, but with sufficient photo overlap and image quality, photogrammetry generally yields point clouds with horizontal errors on the order of a few cm to several tens of cm (cm level accuracy (half-inch accuracy)) and vertical errors of about 10-20 cm (10-20 cm (3.9-7.9 in)). Using an RTK-enabled drone or ground control points (GCPs) for thorough correction can achieve accuracies within a few centimeters. Note that accuracy decreases in areas with dense vegetation or on water surfaces where feature points are sparse. Depending on required accuracy, consider using RTK, GCPs, or even combining with LiDAR.

Q: Are licenses or permits required to operate a drone? A: In Japan, drone registration for aircraft weighing 100 g or more has been mandatory since 2022. Permissions and approvals from the Ministry of Land, Infrastructure, Transport and Tourism are required for certain flights such as beyond-visual-line-of-sight, night flights, and flights over densely populated areas (DID). A national qualification (license) system for “unmanned aircraft pilots” has also been introduced for some types of flights. However, basic flights within visual line of sight may still be possible without a license in many cases. Because laws and regulations may change, always check the latest guidelines from the Ministry of Land, Infrastructure, Transport and Tourism before flying and follow appropriate procedures.