New Common Sense at Survey Sites! Managing Survey Point Lists Becomes This Easy with CSV Export of Point Cloud Data

目次

• 点群データのCSV出力とは？

• 従来の測点一覧管理と課題

• CSV出力で広がる測量DXのメリット

• 点群データをCSV形式で出力する方法

• 点群データ管理とCSV活用のポイント

• まとめ：LRTKによる簡易測量のすすめ

• FAQ

In recent years, digital technologies have been increasingly introduced at surveying sites, and a new common sense is emerging: exporting point cloud data to CSV makes management of survey points (measurement points) dramatically easier. Traditionally, surveyors measured each point one by one for every survey and manually entered coordinates into paper field books or Excel to create a coordinate list (survey point list). But now we live in an era where three-dimensional point cloud data can be used to instantly output a coordinate list in CSV format on site. This article explains what CSV export of point cloud data is, its advantages and methods, and the benefits it brings to field operations. At the end of the article, we introduce LRTK, which enables anyone to perform high-accuracy surveying easily with a smartphone, and propose a step toward new surveying methods.

点群データのCSV出力とは？

First, what is "CSV export of point cloud data"? Point cloud data are three-dimensional data that digitally record an object or terrain as a set of many points. Each point has X, Y, and Z coordinate values (and sometimes attributes such as RGB color values or reflectance intensity), so the data itself can be regarded as a "collection of coordinates." CSV format is a text format that lists various data separated by commas. In other words, exporting point cloud data to CSV means writing out the coordinate information of each point that composes the point cloud in a tabular form like "X coordinate, Y coordinate, Z coordinate, ...".

Point cloud data exported in CSV format are, so to speak, a "list of survey points." For example, if you extract the coordinates of major feature points from a point cloud obtained at a site and save them to a CSV file, you can use it as a survey point list for that site. CSV files can be opened in Excel, making it easy for people to directly check and edit the contents. The advantage of "CSV export" is that coordinate data can be made usable by anyone even without dedicated CAD software or point cloud viewers.

It is also possible to save the entire point cloud directly as CSV, but exporting millions of points to text results in very large file sizes and is not practical. In many cases, only the necessary survey points are selected and converted to CSV, or the point cloud itself is saved in a lightweight binary format (such as LAS or PLY), and CSV export is used when a specific coordinate list is needed. CSV is fundamentally a general-purpose format for human reading or passing data to other software, and dedicated formats are generally used for raw point cloud data management.

従来の測点一覧管理と課題

Before the widespread use of point cloud data, managing survey point lists in surveying was a laborious task. In traditional methods, surveyors used total stations (TS) or GPS survey instruments to measure points one location at a time, recording observations in notebooks or field books each time. Measuring a wide area required repositioning equipment or dividing tasks among multiple people, and because the number of points that could be obtained was limited, it was common to take representative samples rather than comprehensive measurements.

As a result, the resulting survey point lists (coordinate lists) often included only a small portion of the site, and later on it was common to find that "we should have measured another location," but by then the site visit was over and additional measurements were difficult. When recording coordinates by handwriting or manual entry, there is also a risk of recording or transcription errors due to human error. When delivering coordinate values as survey results, even minor mistakes such as typographical errors in symbols or incorrect unit notation can cause serious troubles, so double-checking was indispensable in traditional methods.

Furthermore, because traditional surveying captured only a small number of points, it was difficult to grasp the overall shape of terrain or structures. For example, in verifying the shape of embankments or slopes, measuring only a few key elevations and comparing them to design values risks overlooking irregularities in the surface or variations in gradient. Ideally, surface- or volume-based measurements would be performed, but traditional constraints often forced compromises by reducing the number of points.

CSV出力で広がる測量DXのメリット

The new surveying workflow that solves these issues is point cloud measurement × CSV export. By obtaining point cloud data and exporting coordinates in CSV format, the management of survey point lists gains the following advantages.

• 包括的なデータ取得: Point cloud measurement records the site in surface and three-dimensional detail, so necessary locations can be measured without omission. If you later decide "I want to know this point too," there is no need to re-survey on site. Because coordinates can be obtained by selecting arbitrary points from the point cloud, you get the same effect as having measured the entire site.

• 効率とスピードの向上: A single scan can acquire thousands to millions of points, enabling a large area’s coordinate data to be obtained in a short time. By exporting only points of interest to CSV, a detailed survey point list can be created quickly. This is overwhelmingly more efficient than traditional point-by-point measurement and can drastically reduce time spent on field work and deliverables.

• 精度と信頼性の確保: Digitally outputting coordinates prevents human recording errors. When a positioning device or app directly outputs CSV, meta-information such as date/time, coordinate system used, and measurement conditions are automatically recorded. This eliminates misreading of handwritten notes or transcription omissions, allowing you to obtain an accurate survey point list immediately. If needed, further accuracy verification can be performed by comparing with known control points or integrating multiple point cloud datasets, ensuring reliability comparable to traditional methods.

• データ活用と共有の容易さ: CSV coordinate lists are a general-purpose format that many software packages can import/export. You can organize them as tables in Excel, import them into CAD software to create drawings, or bring them into GIS systems to display on maps. Being a text format, CSVs are easy to attach to emails or share via the cloud, so all stakeholders can quickly check the same survey point data. This reduces the need to hand over paper forms or transfer files via USB, speeding up information sharing.

In this way, CSV export of point cloud data strongly promotes surveying DX (digital transformation). With initiatives like the Ministry of Land, Infrastructure, Transport and Tourism’s *i-Construction*, the use of 3D survey data is spreading from large to small construction sites. The combination of point clouds and CSV makes it possible for anyone to practice data-driven construction management where "measuring is just the beginning" rather than "measuring and that’s it." It is fair to say this is becoming established as the new common sense at survey sites.

点群データをCSV形式で出力する方法

So how do you actually export point cloud data to CSV format? Generally, the equipment or software used for point cloud measurement has an export function that you can use. Below is an example of basic steps.

• 点群データの取得: First, measure and acquire the site’s point cloud data using a laser scanner, drone photogrammetry, or a smartphone’s LiDAR function. Not only conventional instruments but also mobile measurement using a smartphone + small GNSS receiver can now easily collect point clouds.

• 座標データの補正・位置合わせ: Next, assign positioning coordinates to the acquired point cloud. If you scan while measuring positions with high-precision GNSS (RTK), you obtain a point cloud with global coordinates on site. Even if RTK is not supported, you can perform post-processing such as referencing control points or registering multiple scans to associate an appropriate coordinate system with the point cloud.

• CSVエクスポートの実行: Use the “export” or “coordinate output” function in the software or app that manages the point cloud data to save it as CSV. For example, to export only specific points, select those points on the screen and output them to CSV. Some measurement devices automatically list all measured points and can output a CSV file with a single tap.

Among the steps above, step 2—high-accuracy alignment—is the key to effectively using CSV export. Until now, standalone smartphone LiDAR scans recorded point clouds in the phone’s internal local coordinate system (arbitrary unit), making it unclear where exported CSV coordinates were located on a map. However, if you combine RTK-GNSS centimeter-level positioning (half-inch accuracy) as with small devices like LRTK that attach to smartphones, you can assign accurate world coordinates (latitude, longitude, elevation) to all acquired point cloud points. In other words, you can produce a point cloud with absolute coordinates on site and then generate a coordinate list in CSV with one button press.

A practical note: as mentioned earlier, converting the entire huge point cloud to CSV is inefficient. It’s better to extract and export only needed points or thin the data on a grid to output one point per interval, balancing file size and practicality. Also, the columns output to CSV vary by software. The basic items are coordinate values, but some tools may include point IDs, RGB, intensity, etc. Be clear about what information you want to list and set the export format appropriately.

点群データ管理とCSV活用のポイント

When leveraging CSV export of point cloud data, there are several points to keep in mind. Check tips for handling massive 3D data and ways to make the most of CSV format.

• 必要に応じてフォーマットを使い分ける: Binary formats like LAS/LAZ or PLY are suitable for managing entire point cloud datasets. For human-readable or easily editable survey point lists, CSV is convenient. Use “master data in dedicated formats, lists or extracts in CSV” as appropriate to leverage the strengths of both.

• ExcelやGISソフトと連携: Coordinate lists exported as CSV can be pasted into Excel to create observation tables or graphs for trend analysis. Importing into GIS software lets you plot points on a map and visualize spatial distribution. For example, you can color-code measured point elevations or arrange points along a cross-section to draw a terrain profile.

• CADデータとの併用: After exporting survey coordinates as CSV, you can convert them to DXF to use as base data in CAD drawings. Alternatively, prepare a design coordinate list and a point-cloud-derived existing-condition coordinate list as CSV and compare them to calculate differences. Since CSV is text-friendly and good for numerical processing, it’s useful for automating difference calculations or creating report tables.

• クラウドサービスの活用: If storing and managing large point cloud datasets locally is difficult, consider cloud services. Cloud-based point cloud management services often provide browser-based 3D viewing and the ability to extract parts and download CSV. A workflow where you upload data to the cloud immediately after field measurement and export desired coordinates to CSV from the office browser is possible. Since data sharing can be completed over the Internet, the hassle of passing USB drives or transferring huge files is reduced.

By keeping these points in mind, you can use CSV export of point cloud data more effectively. The important thing is to balance "a system that makes measuring easy on site" with "a system that fully utilizes the data." Recently, all-in-one surveying solutions that achieve both have appeared. The next section touches on LRTK, a new simple surveying tool gaining attention.

まとめ：LRTKによる簡易測量のすすめ

Surveying methods that can export point cloud data to CSV are truly becoming the new common sense at sites. Rapidly recording many points and instantly listing necessary information has markedly improved the efficiency of surveying work and as-built management that used to take days. Data-driven construction management directly contributes to quality improvement and becomes a powerful tool for understanding the site safely and accurately even with limited personnel.

To fully enjoy these benefits, introducing easy-to-use simple surveying tools is recommended. Among them, the small surveying device “LRTK,” which attaches to a smartphone, is attracting attention as an innovative solution that combines point cloud measurement and high-precision positioning. Weighing only a few hundred grams, pocket-sized, it leverages a phone’s LiDAR and RTK-GNSS to achieve 3D surveying with centimeter-class accuracy (half-inch accuracy) and can obtain point clouds with coordinates on site. With the dedicated app, you can export CSV files or share to the cloud with one tap, so you can immediately list results and share them with stakeholders right after measuring.

With LRTK, even technicians without deep surveying expertise can obtain sufficiently accurate survey results in a short time. There is no time-consuming equipment setup, and its ease is truly "smartphone-like." If your current site suffers from "surveys taking too long" or "recording work being cumbersome," consider adopting the latest smart surveying technology such as LRTK. LRTK, which enables fast, simple, and high-accuracy "simple surveying," will likely expand the possibilities of surveying and become a reliable partner on your site.

FAQ

Q. 点群データのCSV出力とは具体的に何をするのですか？ A. It means extracting the coordinate information of each point from three-dimensional point cloud data and saving it as a tabular text file. The many points’ X, Y, and Z coordinates are listed and written out to a CSV file that can be opened with Excel. This allows survey points recorded in a point cloud to be handled as a human-readable list.

Q. 手元にある点群データをCSVに変換したい場合、どのような手段がありますか？ A. Use export functions in point cloud processing software or the native apps of each measurement device. For example, laser scanner software can output coordinate values for selected points from a point cloud. Some free point cloud viewers or plugins also support CSV conversion. Specific operations differ by software, but in many cases, selecting "Export" or "Save" and choosing CSV format is sufficient. Note that in modern smartphone surveying systems like LRTK, the app can directly output a CSV file immediately after measurement.

Q. スマートフォンだけで点群のCSV出力はできますか？ A. CSV export is possible from point clouds obtained with LiDAR-equipped smartphones, but by default the coordinate system will be local values (the phone’s temporary coordinates). Converting to map coordinates requires additional alignment with control points. On the other hand, methods like LRTK that pair a smartphone with a high-precision GNSS receiver can provide world geodetic coordinates from the moment of measurement, enabling immediately practical CSV coordinate lists. In short, it is possible with a smartphone alone, but ensuring positioning accuracy for practical CSV output requires correction positioning or similar measures.

Q. CSV形式の座標リストはどのような用途に使えますか？ A. CSV coordinate lists have many uses. Typical applications include attaching the coordinate table directly to survey reports as a "coordinate table," inputting points when plotting survey points on design drawings, or loading into Excel for comparison calculations and statistical analysis. If you accumulate multiple measurement results in CSV, you can manage them as monitoring data for long-term changes. CSV is a general-purpose format, so it offers high flexibility for sharing and secondary processing.

Q. 点群データをCSV出力するとファイルサイズが大きくなりませんか？ A. When the number of points is very large, CSV files tend to become large. Storing numeric data as text increases data volume compared to binary formats, so saving millions of points to CSV can result in sizes of hundreds of MB or more. Effective measures include exporting only needed points or thinning the data to reduce point count. If you must store large-scale data entirely, use efficient formats like LAS or LAZ rather than text, and convert parts to CSV as needed. With appropriate selection, practical issues from CSV export can be minimized.

Q. 点群計測で取得したデータを公式な測量成果として使えますか？ A. If measurements are performed with appropriate procedures and accuracy verification, point-cloud-derived data can be used as official survey deliverables. In fact, the Ministry of Land, Infrastructure, Transport and Tourism’s guidelines encourage the use of 3D surveying technology, and examples of point cloud measurement used for as-built management are increasing. What matters is confirming that required accuracy is met through comparison with control points and verification against known points. Point cloud surveying using LRTK has been demonstrated to keep errors relative to existing control points within centimeter levels, yielding accuracy comparable to traditional TS or level measurements. Therefore, CSV coordinate lists output from point cloud data can be submitted as reliable survey results.