New Common Sense in the Surveying DX Era: Drone Point Cloud Generation Is Easy and High-Precision on the Cloud

Table of Contents

• What does it mean to generate point clouds with drones?

• Benefits of drone point cloud surveying

• Advantages of generating point clouds on the cloud

• Steps to start drone point cloud generation on the cloud

• Key points for successful drone point cloud generation

• Main use cases of drone point cloud data

• Recommendation: Simple surveying with LRTK

• FAQ

In recent years, the construction and surveying industries have advanced their DX (digital transformation), and with the development of drones and 3D technologies, you’re increasingly likely to hear the term “point cloud data” on site. Photos taken by drones can be converted into three-dimensional point cloud data representing terrain and structures, and this is increasingly used for construction measurements and as-built management.

However, beginners who want to start drone surveying might worry, “How do I get started?” or “Don’t I need expensive equipment or difficult software?” In fact, by utilizing cloud services, it has become easy to start generating drone point clouds even without specialized knowledge or a high-performance PC. The fact that high-precision point cloud models can be obtained easily on the cloud is truly the new common sense of the surveying DX era. This article clearly explains the basics of generating point cloud data using 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 the notable tool “LRTK,” which allows even beginners to easily experience 3D surveying. If you’re interested in drone point cloud measurement but haven’t taken the step yet, please use this as a reference.

What does it mean to generate point clouds with drones?

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

There is also a method of acquiring point clouds by mounting a lightweight laser scanner (LiDAR) on a drone and obtaining point clouds through direct laser measurement. 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, photogrammetry can be undertaken with a commercially available camera-equipped drone and analysis software (or a cloud service), making it an ideal method for first-time point cloud generation.

Benefits of drone point cloud surveying

• Efficiency and labor savings: Drone surveying allows what used to take many people many days over wide areas to be done by one person in a short time while collecting a large amount of data at once. Even on large sites, “missed spots” are reduced and the need for additional surveys can be cut. This major efficiency and labor reduction is very attractive in the construction industry, where labor shortages are a serious issue.

• High precision and comprehensive measurement: Because point cloud data records objects as countless points, it provides far more precise and comprehensive information than conventional surveys that measure only specific points. Shapes down to the millimeter level can be retained as digital data, making it easy to remeasure dimensions at any location later. Even without drawings, accurate 3D models can be produced, which helps improve quality control and the accuracy of design and construction.

• Improved safety: Laser measurement and drone photogrammetry are non-contact methods, so data can be safely obtained in hazardous areas where people cannot enter. High places and steep slopes can be surveyed remotely, reducing the risk of accidents during work. Many cases minimize the need for previously required high-altitude work or road traffic control, greatly contributing to on-site safety management.

• Smoother consensus building through data sharing: Acquired point cloud data can be shared with stakeholders on the cloud as 3D models. Supervisors or clients located remotely can view the site in 3D on a PC or tablet, facilitating smooth communication. Information that was hard to convey with drawings or photos becomes obvious in 3D, enabling persuasive explanations during as-built inspections or design change discussions.

Because of these benefits, the Ministry of Land, Infrastructure, Transport and Tourism is promoting ICT utilization such as drone surveying under the “i-Construction” initiative, and point cloud technology is becoming a symbol of DX in the construction industry.

Advantages of generating point clouds on the cloud

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

• Easy to introduce: There’s no need to install dedicated software or perform complex settings. A simple workflow—upload photos via a web browser and click a button to start analysis—is available. With UIs designed for beginners, the time required to learn software operations from scratch is greatly reduced.

• Always use the latest technology: Because the cloud service provider updates analysis algorithms and features daily, users always benefit from the latest technology. You don’t need to update software or worry about compatibility. New point cloud processing techniques and AI-based automatic classification features become immediately available on the cloud when added.

• Easy for team use: With data stored on the cloud, it’s easy to share the results of point cloud generation among multiple people. Invite stakeholders to the same project and they can view and measure 3D data from a browser without installing software. Remote team members can share the situation in real time, making collaborative work smooth.

• Cost advantages: Cloud services are attractive because they can be started with low initial costs. Previously, software purchases and hardware investments could cost hundreds of thousands of yen, but the cloud allows you to use only what you need when you need it. Many services use monthly fees or pay-as-you-go models, making it easy to manage costs per project. Small-scale contractors who don’t use the service frequently can economically leverage the latest technology without waste.

Steps to start drone point cloud generation on the cloud

• Equipment preparation and flight planning: First, prepare the drone body (preferably equipped with a high-resolution camera), controller, batteries, and other necessary equipment. Plan the target survey area and flight course, and set routes that efficiently cover the site. Aim for photo overlap (both front-back and side-to-side) of 70% or more to obtain high-quality point clouds. Also check weather and wind conditions and choose a time when safe flight is possible. Don’t forget to confirm relevant drone regulations in advance, such as whether the area is a no-fly zone or whether permission applications are required.

• Drone photography: Fly the drone autonomously according to the plan and photograph the target area. Maintain the planned altitude and camera angles and capture the ground thoroughly. Generally, fly in parallel flight lines and take nadir (straight-down) photos to cover the entire surface. If there are buildings or structures, also add oblique shots to reduce blind spots and obtain a more complete point cloud. During the flight, always monitor battery levels and the condition of the aircraft, and operate with safety as the top priority.

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

• Point cloud generation (analysis) on the cloud: After uploading the photos, start the point cloud generation analysis on the cloud. Follow the service instructions and click the button; the server side will automatically perform image analysis (feature point matching and 3D reconstruction). Even projects composed of dozens to hundreds of photos will generate point cloud data 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 data volume, but progress can be monitored in the browser. Users can work on other tasks while waiting, which is efficient for productivity.

• Check and use the results: Once processing is complete, check the generated point cloud data on the cloud. Use the platform’s 3D viewer to rotate and zoom the point cloud and inspect quality. Verify that terrain and structures are properly reproduced and that there are no missing parts. If there are unnatural noise points, some services offer filter functions to remove them. If everything is fine, download the point cloud data as needed to import into CAD software, or perform earthwork calculations and cross-section creation on the cloud. You can also use generated orthophotos (composite images viewed from directly above) and 3D mesh models. Share completed deliverables with stakeholders on the cloud or attach them to reports to support on-site work.

Key points for successful drone point cloud generation

• Ensure sufficient photo overlap: The quality of point cloud generation is greatly affected by the degree of overlap between photos. Ensure 70–80% overlap in front-back and side-to-side directions so the same ground area appears clearly in adjacent photos. Insufficient overlap can cause point clouds to be fragmented or reduce accuracy.

• Consider weather and shooting conditions: For photogrammetry, it’s important to shoot in conditions that produce bright, sharp images. Choose times with good sunlight and avoid flights in rain or strong wind. Don’t leave camera settings entirely to auto—fix focus and secure a shutter speed that prevents blur. To prevent extreme exposure variation across a set of photos, shoot in manual mode to keep brightness consistent when effective.

• Improve accuracy as needed: If elevation and coordinate accuracy are especially important, use RTK-capable drones or ground control points (GCPs) to improve positioning accuracy. These allow strict latitude, longitude, and height information to be attached to the generated point cloud, achieving accuracy comparable to surveying. Although initial investment and effort increase, consider this for applications that require high precision, such as public surveying and design work.

• Practice on small areas first: Rather than tackling vast sites right away, start with a small area or familiar structure. By experiencing the entire workflow with a small dataset and verifying results, you’ll see points for improvement for next time. Gradually expanding the scale reduces the risk of failure while steadily improving skills.

• Thoroughly observe regulations and safety management: Drone flights are governed by laws and regulations. Always check for no-fly zones and obtain any necessary permissions in advance. Also maintain safety procedures such as checking battery and GPS status and ensuring surveillance to prevent third parties from entering the flight area. Be considerate of the surroundings on site, operate carefully, and prioritize zero accidents above all.

Main use cases of drone point cloud data

• Earthwork calculations and as-built management: From acquired point cloud data, you can calculate volumes of fills and excavations and record completed terrain as as-built maps. For example, by scanning the ground before and after construction with a drone and comparing the results, you can accurately determine the amount of earth moved. You can also cut cross-sections from point clouds to verify whether constructed elements have the design dimensions and shapes. Point cloud utilization makes high-precision as-built management, which used to be difficult, much easier.

• Creation of current condition maps and design review: Drone point clouds can serve as base data for dense current condition surveys. From acquired 3D point clouds, you can create arbitrary plan views and longitudinal/cross sections, aiding designers in accurately understanding site conditions. You can overlay design models (CAD data) on point clouds to check for clashes or simulate the suitability of planned routes. Intuitive 3D data helps discover issues that might be missed on traditional 2D drawings.

• Progress management and stakeholder sharing: Periodically recording construction progress with drone point clouds allows you to track site changes over time. By overlaying point cloud data from different survey times, you can instantly see where and how much changes occurred, which is useful for schedule management. Sharing these data with clients and team members via the cloud conveys real site conditions to those who can’t visit. Presenting 3D models in regular meetings helps accelerate consensus building.

• Infrastructure inspection and disaster response: Point cloud data from drone-mounted cameras or LiDAR is used for inspecting infrastructure such as bridges, dams, and tunnels, and for quickly assessing disaster sites. Because data can be collected safely in areas where people cannot enter, it’s effective for monitoring slopes at risk of collapse and measuring terrain changes after floods. Skills in photogrammetry learned during normal times will be valuable in emergencies.

Recommendation: Simple surveying with LRTK

LRTK (pronounced “L-R-T-K”) is an innovative solution that lets beginners easily start 3D surveying. With the “smartphone + RTK” concept, you attach a compact positioning device called the “LRTK Phone” to a handheld iPhone and launch a dedicated app to perform high-precision point cloud measurements. It achieves centimeter-class positioning (cm-level accuracy (half-inch accuracy))—which previously required specialized equipment—on a smartphone, allowing you to attach accurate position information to photos and LiDAR scans. The convenience of a single pocket-sized device enabling one person to survey a site is truly worthy of being called “simple surveying.” Even those without surveying experience can obtain 3D point cloud data simply by following the app’s instructions and pointing the smartphone, greatly lowering the barrier to on-site introduction.

Furthermore, LRTK seamlessly supports data utilization in combination with cloud services. For example, if you upload point cloud data acquired with LRTK or photos taken by drone to the LRTK cloud, coordinate-attached point cloud models are automatically generated and can be edited and shared in a browser. Because large datasets can be handled without a high-spec PC, LRTK supports everything from small sites to large-scale projects. LRTK is an excellent tool for promoting on-site DX with the approach of “start small and gradually expand,” letting you try the latest 3D technologies while keeping initial investment low. If you’re a beginner interested in point cloud utilization, why not take 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 and the controller, batteries, etc., to fly the drone safely. Also prepare registration with the cloud service (or dedicated software) that will process the photos. If you want survey results aligned to map coordinates, using specialized high-precision GNSS (RTK-equipped drones or ground reference points) will improve position accuracy. In addition, confirm legal procedures in advance, such as checking the flight area, applying for necessary permissions, and registering the aircraft (registration is required for aircraft weighing 100 g or more).

Q: Can beginners handle drone point cloud generation? A: Yes; in recent years, drone autopilot apps and cloud service UIs have improved, and beginners can obtain point cloud data by following basic procedures. However, aircraft operation requires safety management and compliance with regulations, so practice at first and gain experience with relatively simple projects. Early on you may not get everything right, but by experimenting on small sites you’ll steadily improve.

Q: Are there disadvantages to using cloud services? A: The main consideration is dependence on the internet environment. Because you need to upload many photo files, an unstable connection can increase processing time or communication costs. Also, cloud service usage fees are incurred continuously. However, many services use a pay-as-you-go model, avoiding upfront investment; in many cases this can be cheaper than purchasing on-premises software. If you are concerned about data confidentiality, choose a reputable, proven service and check the terms of use regarding data handling.

Q: What level of accuracy can be obtained from point cloud data? A: It varies depending on shooting method and equipment, but with sufficient overlap and image quality in photogrammetry, you can generally obtain point clouds with horizontal errors on the order of several centimeters to more than ten centimeters, and vertical errors of about 10–20 cm (3.9–7.9 in). By using RTK-capable drones or ground control points (GCPs) for careful correction, centimeter-level accuracy is also possible. Note that accuracy decreases in areas with dense vegetation or surfaces with few feature points, such as water. Consider using RTK, GCPs, or LiDAR in combination depending on the required accuracy.

Q: Are qualifications or permissions required to pilot drones? A: In Japan, aircraft registration for drones weighing 100 g or more has been mandatory since 2022. Permission and approval applications to the Ministry of Land, Infrastructure, Transport and Tourism are required for certain flights, such as beyond-visual-line-of-sight flights, nighttime flights, and flights over densely populated areas (DID). Additionally, a national qualification (license) system for “unmanned aircraft pilots” has also begun for some flight types. However, basic flights within visual line of sight can still be conducted without a license in many cases. Laws and regulations may change in the future, so always check the Ministry’s latest guidelines before flying and follow proper procedures.