7 Common Problems When Sharing Point Cloud Viewers | Pitfalls of File Size, Permissions, and Viewing Environments

Table of Contents

• Characteristics of point cloud data and ways to share it

• Point 1. The barrier of large-volume data: file size and transfer time

• Point 2. Pitfalls of permission settings: risks of inaccessibility and information leakage

• Point 3. Inadequate viewing environments: issues with supported browsers, OS, and PC specs

• Point 4. File format and compatibility issues: various formats centered on LAS/LAZ

• Point 5. Difficulty viewing in offline environments: countermeasures for sites without network connectivity

• Point 6. Delays in information sharing due to insufficient cloud integration

• Point 7. Innovation in field operations: new point cloud sharing enabled by smartphone + LRTK

• Summary

On construction, civil engineering, and surveying sites, point cloud data acquired by laser scanners, drones, and the like are handled on a daily basis. The 3D data, composed of countless points, is an indispensable information resource for design, construction, and maintenance, but its sharing and viewing involve unique difficulties. In particular, point cloud files typified by the LAS/LAZ formats tend to be very large, and choosing the wrong sharing method can hinder on-site operations. This article explains concretely seven "pitfalls" that site personnel tend to face, after covering the characteristics of point cloud data and common sharing methods. It addresses typical troubles such as exceeding capacity, incorrect permission settings, and viewing environment issues, and delves into precautions when viewing on Windows and web browsers (Chrome, Edge), as well as practical advice on offline handling and cloud integration. Finally, it also touches on how these issues can be resolved through the use of high-precision GNSS devices (LRTK) that can be attached to an iPhone.

Characteristics and Sharing Methods of Point Cloud Data

First, we will organize what point cloud data is, its basic characteristics, and means of sharing. Point cloud data (point clouds) are collections of numerous points that make up objects or terrain, with each point containing X, Y, and Z coordinates. They are acquired by laser scanner surveying or photogrammetry, and, as needed, each point may have attributes such as intensity (Intensity), color information (RGB), or classification information. For example, in airborne laser survey point cloud data published by the Geospatial Information Authority of Japan, the ground surface and buildings are measured at a density of 4 or more points per 1 m^2 (10.8 ft^2), and each point is assigned, in addition to coordinates, reflectance intensity and a simple classification code. This detailed 3D information is considerably richer than conventional planar surveying results, but it is characterized by an extremely large data volume.

Because a typical point cloud file contains millions to hundreds of millions of coordinate points, file sizes can reach hundreds of MB to several GB. If you try to send point cloud data collected on site as an email attachment, it is usually too large to transmit. For that reason, it has often been common to copy the data to physical media such as external hard drives, USB flash drives, or SD cards for transfer. However, sharing via physical media involves the time and cost of shipping or carrying, and carries the risk of damage or loss in transit. If transfers take time, sharing up-to-date data between remote sites can incur time lags, which may hinder coordination between the field and the office.

It is also worth noting that viewing point cloud data often requires dedicated viewer software and a high-performance PC. Unlike ordinary text or photographs, smoothly displaying and manipulating 3D point clouds demands large amounts of memory and graphics processing power. Not all stakeholders on site necessarily have such high-spec environments, and situations where “the data exists but cannot be viewed” have tended to occur. Against this background, methods for sharing point cloud data include direct sharing via physical media, using cloud storage, and leveraging point cloud viewer systems, but each has its own advantages and disadvantages. Now, let’s look in order at seven points where on-site personnel tend to get “stuck” in these sharing situations.

Point 1. The barrier of large datasets: file size and transfer time

"The file is too large to share!" — The first problem you encounter when sharing point cloud data is exactly this. Point cloud files often reach sizes from several GB to several hundred GB, and issues caused by exceeding storage capacity are all too common. For example, even in the publicly available data from the Geospatial Information Authority of Japan, it is reported that a single point cloud file can be on the order of several hundred MB to several GB. Email attachments are, of course, impossible, and even if you try to place files on an internal file server or cloud storage, you can run into storage limits or face extremely long upload times. Even when trying to share the latest data within the limited time available on site, cases where "the file transfer took half a day" are not uncommon.

An important response to this storage-capacity problem is the compression of point cloud data and efficient data management. Even raw data of several gigabytes in LAS format can have its size dramatically reduced by converting to the lossless compressed LAZ format. In fact, compressing LAS files to LAZ is said to reduce the size to about one-tenth while preserving the original data precision. The Geospatial Information Authority of Japan also provides LAS point clouds in LAZ format when distributing results of airborne LiDAR surveys. For example, a 500 MB LAS file becomes roughly a 50 MB LAZ file, making cloud distribution a practical size (the recipient will need LAZ-compatible software, but this point will be discussed later). In the field as well, it is best practice to compress acquired point clouds before sharing them whenever possible. In some cases, it can also be effective to split data by area so that the file sizes handled at any one time are kept small. To overcome the barrier of exceeding storage capacity, you can use the measures “compress, split and send, and provide only the necessary parts.”

Furthermore, thanks to large capacities, data that used to be transported on physical media can increasingly be shared online by using large-capacity cloud storage. Reliable cloud services offer plans that can store files of tens of GB or more, and sharing via a link is faster than mailing a USB. If the service allows direct viewing on the cloud, recipients can check the data in their browser without downloading, which helps eliminate transfer waiting time. Although the capacity barrier remains high, combining compression and cloud usage can gradually reduce its impact.

Point 2. Pitfalls of permission settings: risks of access denial and information leakage

"Can't access the file," "People who shouldn't see it were able to see it" — problems caused by incorrect permission settings when sharing point cloud data cannot be overlooked. When sharing data in internal shared folders or cloud storage, if access permissions are not set correctly, the people who need it may not be able to view it, and conversely, the data may end up being shared with people who don't need it.

For example, you might upload point cloud data collected on site to the cloud and send a sharing link to your team, but leave the link permission set to "Only I can view," so other employees cannot open it—such basic mistakes are surprisingly common. On busy sites, checking permission settings is often neglected, and it may only be noticed after inquiries like "You do not have access" start coming in. Conversely, you might accidentally make the link publicly accessible so that point cloud data that should be limited to internal stakeholders can be viewed externally—this kind of close call can also occur. Because point cloud data can include sensitive information such as construction plans and terrain data, incorrect permission settings can directly lead to information leaks.

Permission settings are not easy to see on the screen and may seem like a mundane task at first glance, but they are so important that people say "a small mistake can become a major entry point." There have also been reported cases in which data was taken out by third parties due to permission mistakes in cloud storage. Point cloud data handled on site is no exception, and appropriate access control is required.

As concrete measures, it is fundamental to use the cloud service’s features to set viewing and editing permissions for each user in detail, controlling access so that data cannot be seen by anyone who is not authorized. When sharing links, you should also take steps to prevent them from spreading to an unspecified large audience, such as restricting them to specific users within the organization or using password-protected links. In addition, it is desirable to review access rights regularly after sharing and to remove permissions that are no longer needed when a project ends. Formalizing permission management rules within the company and conducting regular audits of “who can access which data” can also be effective. You should also have recovery procedures ready in case you discover a permissions mistake. It is reassuring to confirm in advance how to change settings in each cloud service — for example, stopping link sharing, removing a mistakenly invited user from the access list, or lowering permission levels to view-only.

Point 3. Inadequate viewing environment: Issues with supported browsers, operating systems, and PC specifications

"Visible on some computers but not on others..." One common pitfall when sharing point cloud viewers is shortcomings in the recipient's viewing environment. Even if you go to the trouble of sharing the data, it will be wasted if the recipient's PC or software environment doesn't support it. On site, I think it's common to check point clouds on Windows laptops, but there are several points to be aware of.

First, the OS and application compatibility. Many professional point-cloud viewer applications are provided only for Windows, and quite a few do not run on Mac. Also, 32-bit versions of Windows may not have enough memory address space to process large point clouds, causing the software to fail to run. Basically, keep in mind that a 64-bit OS and sufficient RAM are required (if viewing point clouds on the order of several tens of GB, 16 GB or more is recommended). Regarding the GPU, a dedicated graphics card or a high-performance integrated GPU is desirable to comfortably render point clouds of several million points or more. On older laptops, rendering can become extremely slow, or in the worst case the software may crash.

Below are points to note when viewing in a web browser. Recently, browser-based point cloud viewers (using WebGL technology) have become widespread, but they are not万能. First, a WebGL-compatible browser is an absolute prerequisite. The latest versions of Chrome, Edge, and Firefox generally support WebGL, but older browsers such as Internet Explorer will not work. Also, it is not enough for the browser itself to be up to date—the PC’s GPU drivers and settings running behind the scenes also have an impact. In some cases, corporate security policies disable WebGL in browsers, so you need to check this in advance. Therefore, support is required to have viewers use the latest Chrome/Edge and to update their graphics drivers.

Furthermore, the issue of PC specifications still remains. Even if you use a cloud point-cloud system that can be viewed in a browser, you cannot say it will be completely lightweight at the scale of tens of millions of points. On low-spec PCs, interactions in the browser can become sluggish, so depending on the case you might prepare a local lightweight viewer (e.g., an open-source point cloud viewer) and consider extracting and providing a subset of the data. In this way, it is important for the sender and receiver to align their assumptions about system environments. On site, to avoid the situation where "I could view it on my PC, but the other party cannot open it," it is considerate to notify in advance the "software name, supported OS, required specs, recommended browser," etc. If the other party does not have the dedicated software, guide them to install a free viewer or switch to web browser sharing.

Point 4. File formats and compatibility issues: Various formats centered on LAS/LAZ

"It's also common on-site for files not to open because the format doesn't match, or for conversions to be troublesome. Point cloud data exists in a variety of file formats — including LAS/LAZ, E57, PLY, XYZ, and manufacturers' proprietary formats — each with different characteristics and compatibility. When sharing data on-site, you must also pay attention to whether the recipient can use the format."

The most widely used general-purpose format is LAS (.las). LAS is a binary format developed by the U.S. ASPRS and has become the de facto standard format for airborne and terrestrial laser surveying. It can store various information such as each point’s coordinates, intensity, classification codes, and RGB color (optional), and is widely adopted for terrain and urban point cloud data published by national and local governments. LAS’s specification has been extended across versions (the latest is 1.4, while 1.2 and 1.3 are still common in the field), and although compatibility is generally high, older software may not be able to read newer versions.

LAZ (.laz) is the losslessly compressed form of LAS. Its advantage is that it can greatly reduce file size while preserving the original data’s precision, making it suitable for distributing and storing large-scale point cloud data. It is also highly compatible with LAS, and support is progressing so that existing analysis tools and GIS software can read it. However, some older software still does not support LAZ, so depending on the recipient’s environment you may need to "decompress LAZ back to LAS." Before sharing, it’s courteous to ask, "Can your company open LAZ files?"

Let's also cover the E57 (.e57) format. E57 is a vendor-neutral open format defined by ASTM (the international standards organization), a general-purpose binary format designed to exchange point cloud data between different manufacturers. Its characteristic is that it can store not only the point cloud itself but also abundant metadata—such as measurement conditions, sensor position and orientation, and captured images—as well as 360° images. You may not often choose E57 yourself on site, but it’s good to know because a design consultant may sometimes specify, "Please provide it in E57."

PLY(.ply) is the Polygon File Format originally developed at Stanford University; although intended for 3D mesh models, it is a flexible format often used to store point cloud data. Colored point cloud data generated by drone SfM (Structure from Motion) is sometimes provided in PLY format. The XYZ format, as the name implies, is a simple text format that lists the coordinate values of each point; while highly versatile, it tends to bloat file size compared with binary formats and is therefore unsuitable for large-scale point clouds. What matters is compatibility with the recipient, so to avoid the needless detour of "the format is different and I can’t open it," make it a habit to include a quick format check when sharing data.

Point 5. Viewing difficulties in offline environments: Measures for sites without network connection

"The site is out of range and can't connect to the cloud..." While digitalization is advancing, attention must also be paid to operating point cloud data in offline environments. Especially when working in mountainous areas, underground tunnels, or remote locations without cellular reception, you may be unable to connect to the internet and access point clouds stored in the cloud. Also, even if you comfortably view point clouds in a cloud-based viewer at the office, there is a pitfall: if the laptop you take to the field is offline, you won't be able to view the same data.

What matters for field personnel is to prepare so they can reference point clouds offline. Specifically, possible measures include downloading the necessary point cloud data to a local PC in advance and installing viewer software that runs standalone. For example, free, open-source point cloud viewers or desktop viewers that can open local files operate without a network connection, so if installed on a PC beforehand you can check point clouds even at sites outside network coverage. Even if you use a cloud-based point cloud sharing service, making it a habit to export the latest data before heading to the site provides insurance in case of an emergency.

One more thing: watch out for license activation. Some commercial software performs an internet-based license check at startup. Even if it works fine in the office, there are not-so-funny stories of software failing to launch at sites with no network. As a countermeasure, if the software supports offline activation, complete the procedure in advance, or adjust operations so that on-site you only use free software for viewing. The point is to prepare with the assumption that "the site is not always online." Digital tools are convenient, but in the end they depend on power and communications. To prevent work from being disrupted by power outages or being out of coverage, also prepare low-tech backups—for example, jot important measurement points on paper drawings—this can be called the practical wisdom of a field-first approach.

Point 6. Delays in information sharing caused by insufficient cloud integration

Traditionally, sharing point cloud data among stakeholders required the hassle of handing over physical media or using file transfer services, and information sharing between remote sites inevitably experienced time lags. Even if the latest survey was conducted on site, engineers at headquarters might not see it until the next day at the earliest, or in the worst case several days later. During that time, site conditions could change, leading to communication breakdowns and errors in judgment.

To eliminate such delays, real-time sharing through cloud integration is effective. By centrally managing point cloud data in the cloud and sharing a URL with stakeholders, anyone can access the latest 3D data from anywhere at any time as long as they have an internet connection. There is no need for each person to provide expensive specialized software or a dedicated workstation; a standard PC or tablet web browser alone can provide an environment to display and measure large-scale point clouds. If data scanned on site are synced to the cloud with a single click, office and remote team members can immediately grasp the situation, and the speed of reporting and issuing instructions will improve dramatically.

Furthermore, as data accumulate in the cloud, it becomes easier to compare and utilize point clouds over time—such as before and after construction and during inspections. For example, by overlaying point clouds acquired periodically you can track the progression of cracks or calculate cut-and-fill volumes from terrain differences before and after construction, making applications in maintenance and quality control promising. The historical data stored in the cloud functions as a living archive that stakeholders can refer to at any time. In addition, many cloud services offer security features such as access permission settings, communication encryption, and automatic backups, so the advantage of securely and reliably storing and sharing point cloud data over the long term should not be overlooked.

In short, not leveraging the cloud for point cloud sharing itself is increasingly becoming a major pitfall. Traditional handoffs and local storage alone cannot keep up with the speed demanded in the DX era. Actively embracing cloud integration while supplementing it with offline methods as needed—that balance is the smart form of information sharing required on sites going forward.

Point 7. Innovation in on-site operations: New point cloud sharing enabled by smartphone + LRTK

The final point to introduce is the adoption of cutting-edge technology that can swiftly resolve the challenges discussed so far. In recent years, a trend has emerged of combining the LiDAR sensors built into smartphones—particularly iPhones and iPads—with high-precision GNSS to easily perform point cloud measurement and sharing on site. A representative example of this is the use of LRTK (Lightning RTK) devices that can be attached to an iPhone.

LRTK is a pocket-sized, ultra-compact RTK-GNSS receiver that, when attached to an iPhone or iPad, provides centimeter-level (half-inch-level) high-precision positioning. Because this LRTK device continuously provides highly accurate position coordinates to the point clouds acquired by the iPhone’s LiDAR, anyone can obtain 3D point clouds in which every point is assigned global coordinates (latitude, longitude, height). Traditionally, point clouds captured by the iPhone’s built-in LiDAR scanner are produced in a local coordinate system, and when scanning while walking around the point cloud can become distorted. However, by using LRTK, because the device continuously determines its own position with cm-level accuracy (half-inch accuracy), the point cloud will not distort during scanning, making coordinate-attached point cloud scanning possible even without specialized knowledge.

What is particularly noteworthy is that the acquired point cloud data can be shared to the cloud instantly. Point clouds measured with LRTK’s dedicated app can be uploaded to LRTK Cloud with a single tap, and office staff can immediately view that 3D data via the internet. In other words, the real-time workflow—scan on site → cloud sync → remote viewing—can be completed with just a smartphone. No viewer software is required; recipients can view and measure the point cloud from a standard PC web browser. Furthermore, on LRTK Cloud you can overlay photos onto the point cloud and measure distances, areas, and volumes at any point, providing end-to-end functionality from field surveying through analysis.

This combination of a smartphone + high-precision GNSS + the cloud is precisely a comprehensive solution that addresses the pitfalls described so far. Regarding data volume, because you scan only the necessary area on site and upload it to the cloud, waste is minimized, and permission settings can be strictly managed within the cloud. The viewing environment only requires a browser, and no format conversion is necessary. In terms of price, the LRTK Phone is set very reasonably, making an era of one device per person realistic. Each person carrying a pocket-sized 125g surveying instrument, taking it out quickly when needed to perform high-precision point-cloud measurement and sharing—that new on-site workflow has already begun.

Summary

Sharing and viewing point cloud data involves many pitfalls, such as file size, access permissions, and compatible software and hardware. The seven points discussed in this article — the barrier of large-volume data, permission setting mistakes, viewing environment issues, format compatibility, offline support, lack of cloud integration, and leveraging the latest technologies — are typical examples of troubles and inefficiencies that commonly occur on site. Fortunately, there are countermeasures and improvements for each. Resolve capacity issues through compression and splitting, and ensure information security by enforcing strict permission management. Confirm environmental requirements in advance so the recipient can reliably view the data. Wisely combine cloud and offline operations to establish a timely and dependable sharing system. Also consider adopting new tools such as smartphones combined with high-precision GNSS. These efforts will steadily lower the barriers to point cloud data sharing and lead to improved productivity in field operations.

In an era where leveraging 3D data becomes commonplace, on-site personnel themselves are expected to "master" point cloud data. Keep the points raised here in mind and review the shared use and operation of your point cloud viewer so that it fits actual on-site conditions. Doing so will resolve the various problems that have been "stuck" until now, and point cloud data will truly become a weapon in the field.