3D Display and Sharing of Point Cloud Data on Maps! Easy Visualization Realized with LRTK

Table of Contents

• What is a browser-based point cloud viewer?

• Visualizing point cloud errors with heat maps

• Advantages of no-installation & cloud sharing

• Simple high-precision surveying with a smartphone: using LRTK

• FAQ

When you want to easily share and display high-precision 3D point cloud data, many people first think, “Can’t I display point clouds on Google Maps?” Indeed, Google Maps is convenient for sharing information on a map, but unfortunately it does not provide a function to directly display a user’s point cloud data in 3D. One might consider converting point clouds to KML and loading them into Google Earth, but that is not practical performance-wise for datasets with millions of points.

In recent years, the use of 3D point cloud data (point clouds) on-site has rapidly expanded, especially in civil engineering and construction. Sites are being scanned in their entirety using laser scanners or drone photogrammetry, and these data are being applied to as-built management and terrain surveying. However, sharing acquired point cloud data with people off-site or analyzing it intuitively is not easy. It often requires installing dedicated software, and the data volume can be massive and hard to handle, so the valuable 3D information obtained is often not shared sufficiently.

For example, point cloud data generated by drone photogrammetry can reach millions to tens of millions of points, and file sizes can be several GB. Such large files are difficult to share via email attachments, and even opening them on a typical PC can be a challenge.

This is why cloud-based 3D data sharing and visualization using a browser-based point cloud viewer is attracting attention. If point cloud data are uploaded to the cloud and made viewable in a web browser, 3D data can be exchanged easily without dedicated software. Furthermore, by overlaying point cloud data with design data to create a heat map (a colored error distribution map), you can immediately determine whether the as-built site shape matches the design. This article explains the latest trends in browser-based point cloud viewers and heat map utilization. At the end, we also introduce LRTK, a solution that allows anyone to perform simple high-precision surveying by combining a smartphone with a compact GNSS receiver. If you are interested in on-site DX, please refer to this.

What is a browser-based point cloud viewer?

First, let’s cover what a browser-based point cloud viewer is. Traditionally, displaying and processing 3D point cloud data required dedicated desktop software or high-performance CAD software. However, recent advances in browser technologies such as WebGL have made it possible to render 3D graphics directly in web browsers. This has led to the emergence of online point cloud viewers that load point cloud data via the Internet and display and manipulate them directly in the browser.

The biggest advantage of using a browser-based point cloud viewer is that there is no need to install dedicated software. Anyone who wants to view the data only needs a web browser; without special software or an expensive workstation, they can display 3D point clouds by simply clicking a shared URL link. Whether on Windows or Mac, from an office PC or a tablet in the field, the same data can be checked regardless of environment. Operations such as displaying, rotating, zooming, slicing cross-sections, and measuring distances can all be done intuitively in the browser, so even without specialized knowledge, users can navigate 3D space using only mouse or touch operations. Supervisors or clients who have never visited the site can easily visualize the site’s 3D data via the browser.

Moreover, browser-based point cloud viewers pair well with cloud data sharing. If massive point cloud data collected on site are uploaded to a cloud server and viewed with a browser viewer, there is no need to exchange files individually. With the latest data always on the cloud, multiple members can access and check it at their convenience. This enables real-time sharing of site conditions across geographically separated locations, and inspections or meetings that formerly required on-site attendance can be conducted remotely (remote on-site attendance). In fact, the Ministry of Land, Infrastructure, Transport and Tourism has been promoting institutionalization of remote on-site confirmation, and cloud sharing of point cloud data is expected to support this new remote inspection style.

With the momentum generated by the ministry’s promotion of i-Construction, open platforms and viewer technologies for handling point cloud data in the cloud are emerging one after another. From open-source viewing libraries to commercial cloud services, there are various options depending on use and budget. For example, standard LAS/LAZ formats and other datasets with tens of millions of points are made responsive in browsers through techniques such as spatial indexing and LOD (level of detail). Even without a dedicated in-house CAD operator, on-site staff can scan with a tablet, upload to the cloud, and instantly share 3D data with office personnel, making such workflows realistic.

Visualizing point cloud errors with heat maps

Next, let’s look at heat map visualization of point cloud data. Simply looking at a 3D point cloud does not make it easy to intuitively grasp “which parts match the design and which are off.” Heat map analysis, which compares point cloud data with design data and color-codes deviations, is used to address this. A heat map overlays the measured post-construction point cloud with the design model (or a reference plane created from drawings) and uses color to represent the vertical deviation at each point. For each point in the point cloud, it calculates differences such as “this point is ○ mm higher than the design surface” or “○ mm lower,” and colors the points red, yellow, green, blue, etc., according to the error magnitude.

For example, in earthfill works, areas where fill exceeds the design height or in cut areas where excavation is insufficient and the surface is higher than the reference will appear in red or orange on the heat map. Areas finished nearly as designed are shown in green to blue tones, allowing quick distinction between defective (nonconforming) and satisfactory areas. The color gradient visually indicates the magnitude of errors, making it easy to grasp trends in construction accuracy such as “overall slightly higher” or “a specific area is lower than others.”

By using heat maps, small irregularities and unevenness that were previously overlooked can be detected. Traditional as-built inspections compared values at limited measurement points against design values for pass/fail judgments. With heat maps, however, you can perform holistic surface-based pass/fail checks across the entire site. The results are easy to interpret, and because everyone from field workers to clients can intuitively understand the colored 3D information, it becomes easier to share necessary correction points with the whole team.

Recently, AR (augmented reality) technology has emerged that overlays heat maps onto tablet or smartphone camera images. By downloading heat map data from the cloud to a mobile device and overlaying it in real time on the actual structure or ground at the site, you can verify on the spot “which locations need how much correction.” Previously, workers had to mark defective areas discovered by heat maps on-site again, but with AR display, the location and deviation amount of repair points can be intuitively understood through the screen, enabling immediate corrective action. Combining point cloud heat maps and AR is transforming as-built evaluation from mere documentation into a real-time quality improvement tool.

Advantages of no-installation & cloud sharing

As described above, using browser-based point cloud viewers and heat map analysis dramatically streamlines and enhances on-site 3D data operations. Finally, let’s summarize the concrete advantages.

• Rapid measurement of large areas and reduced working time: Using 3D laser scanners or drones, you can acquire high-density point clouds over large sites in a short time. A single scan can collect millions to tens of millions of points, covering areas that previously would have taken a whole day to measure.

• Prevent missed areas through surface-based measurement: Point cloud data measure object surfaces thoroughly, so partial unevenness or distortion will not be missed. Tiny bumps and depressions that could not be noticed with traditional representative-point measurement can be detected by heat maps.

• Measure hazardous areas safely without contact: Laser scanners and photogrammetry can remotely measure steep slopes, high places, and narrow spaces that people cannot enter, eliminating the need for dangerous manual work and improving site safety.

• Streamlined record keeping and information sharing: As-built inspection results in point clouds can be digitally recorded in the cloud and shared immediately with stakeholders. The burden of creating paper photo albums and massive reports is reduced, and information can be exchanged in real time between the office and the field. Because no dedicated software is required and anyone can view 3D models from a browser, explanations to clients and internal sharing are smooth.

By incorporating 3D point clouds and heat maps into site management, inspections become more accurate, faster, safer, and less labor-intensive. Reducing rework due to overlooked measurements and enabling all stakeholders to share the same visual information are major advantages over traditional methods. Point cloud data are not merely pass/fail records but valuable 3D assets useful for future maintenance. If data are accumulated in the cloud after project completion, they can be used later for renovation work or inspection tasks as current-condition reference materials.

Point cloud visualization and sharing are expanding beyond the construction field. They are valued in factory equipment maintenance and plant inspections, digital archiving of cultural properties, and accident scene recording and analysis. Environments where anyone can view 3D models without specialized software are a powerful tool for promoting DX across industries.

Simple high-precision surveying with a smartphone: using LRTK

Finally, as a modern tool for easily acquiring point cloud data, we introduce LRTK. LRTK is a series of compact high-precision GNSS receivers developed by a venture originating from Tokyo Institute of Technology. By attaching them to smartphones or tablets, anyone can achieve centimeter-level positioning that previously required specialized equipment. Combined with the LiDAR scanner functions built into the latest iPhones and iPads, a smartphone can effectively become a high-precision 3D scanner.

In practice, simply walking around a site with LRTK attached to a smartphone can record terrain and structure point cloud data with an accuracy within several cm (within several in) in some cases. With a dedicated app, a single button press uploads the positioned coordinate data and acquired point clouds automatically to the LRTK Cloud. Even in areas without Internet coverage, such as mountainous regions or underground spaces, LRTK can achieve real-time cm level accuracy (half-inch accuracy) by using high-precision positioning signals from Japan’s quasi-zenith satellite system “Michibiki” (CLAS, etc.). The obtained 3D data can be shared immediately via the cloud, enabling seamless workflows like on-site measurement → immediate cloud sharing → remote heat map checking.

LRTK has attracted attention on TV programs and at tech exhibitions, and its adoption by local governments and construction companies is growing. For example, in emergency surveying of terrain after heavy rain disasters, smartphones with LRTK enable rapid current-condition assessment without waiting for heavy machinery. It also performs well in mountainous or remote island surveys where communication is limited, making 3D measurement easy in situations that were previously difficult.

Thus, the smartphone + LRTK combination is attracting attention as an easy one-device-per-person surveying solution. Without heavy tripods or specialized equipment, anyone can record sites in 3D and share them via the cloud, allowing newcomers to point cloud utilization to start with simple smartphone-based methods. The barrier to on-site DX is greatly lowered. Using LRTK, you can speedily and smartly execute the entire process from acquiring point cloud data to visualizing and sharing it in a browser viewer.

FAQ

Q: Is it difficult to implement a browser-based point cloud viewer on my own?

A: No, it’s relatively easy nowadays. You can obtain open-source point cloud viewer libraries and integrate them into your company server, or you can use services that allow you to use a 3D viewer simply by uploading data to the cloud. With the latter, you can start by just registering an account without specialized knowledge, so it’s a good idea to try small-scale free plans first.

Q: What data formats can browser-based point cloud viewers handle?

A: Most viewers can read common outputs from laser scanners and photogrammetry as-is. For example, support for standard point cloud file formats such as LAS, LAZ, PLY, and E57 is increasing. Even proprietary formats can often be read via dedicated conversion tools or plugins.

Q: Can large point cloud datasets be displayed smoothly?

A: Recent viewers are engineered to visualize tens of millions of points smoothly. Streaming technologies that spatially partition data and load only the necessary parts, and LOD (level-of-detail) processing that reduces point detail based on display distance, enable responsive browser operation. WebGL also leverages GPUs built into PCs and tablets for fast rendering, so a typical notebook can handle large point clouds without stress. However, for extremely large datasets, pre-subsampling or tile partitioning will make viewing even more comfortable.

Q: Do I need design data to perform heat map comparisons?

A: To rigorously analyze as-built errors, you need reference data such as design drawings or BIM models. Prepare 3D design data or a reference plane to compare with the point cloud and generate heat maps. If reference data are not available, you can still create pseudo heat maps by color-coding the point cloud itself by elevation. For example, mapping surface elevation by color visualizes terrain undulations. Use the approach appropriate for your purpose.

Q: Can smartphones perform high-precision point cloud surveying?

A: Modern smartphones are equipped with LiDAR sensors that can easily acquire millions of points at short range. Even smartphones without LiDAR can generate 3D point cloud models from multiple photos using photogrammetry (SfM) techniques. With dedicated apps or cloud services, you can obtain high-density point clouds from photo data alone. However, a standalone smartphone has limited positioning accuracy (the positional correctness of each point), so some measures are necessary for serious surveying. This is where high-precision GNSS auxiliary devices like LRTK are useful. Combined with a smartphone, they provide accurate coordinate references to acquired point clouds, bringing centimeter-level surveying within reach.

Q: Is the data uploaded to the cloud secure?

A: Many cloud services ensure data security through encrypted communications and access permission settings. Data you don’t want to make public can be protected with password-protected viewing or time-limited share links. For confidential point cloud data, choose a trusted platform and consider data encryption and contractual confidentiality measures as needed. Some argue that centralized cloud management reduces the risk of loss or leakage compared to carrying data on physical media like USB drives.

Q: Can browser viewers measure distances, areas, and volumes?

A: Many point cloud viewers include basic measurement tools. You can measure the distance between two points on the screen, extract arbitrary cross-sections from the point cloud to calculate areas, or estimate earthwork volumes for enclosed regions. However, formal quality inspections may require precision measurements with dedicated instruments, so treat browser-based measurements as approximate references.

Dramatically improve surveying accuracy and work efficiency on site with LRTK

The LRTK series enables centimeter-level high-precision GNSS positioning in construction, civil engineering, and surveying, significantly reducing surveying time and greatly improving productivity. It supports the Ministry of Land, Infrastructure, Transport and Tourism’s i-Construction initiative and is an ideal solution for promoting DX in the construction industry.

For more details about LRTK, please see the links below.

• [What is LRTK｜LRTK Official Site](https://www.lrtk.lefixea.com)

• [LRTK Series｜Device List Page](https://www.lrtk.lefixea.com)

For product inquiries, quotes, or consultation on introduction, please feel free to contact us via this [inquiry form](https://www.lrtk.lefixea.com/contactlrtk). Let LRTK evolve your site to the next stage.