Streamline LiDAR Surveying: 8 Ways to Reduce Work Time by Automatically Assigning Coordinates

In practical LiDAR surveying, speed and detailed data collection are attractive features. However, aligning the acquired point cloud data with the site’s coordinate system can often take significant time. Especially in construction and civil engineering surveying, it is necessary to align control points with point clouds to create cross-sections and plans, which requires considerable effort to set up reference points and adjust coordinates. Doing this manually has repeatedly proven time-consuming and inefficient.

“Automatic coordinate assignment” in LiDAR surveying refers to automatically assigning coordinate values such as latitude, longitude, and elevation to acquired point cloud data and measurement information. Traditionally, surveyors often performed georeferencing of point clouds manually after scanning using control points, which became a burden both in the field and in the office. However, if this coordinate assignment can be automated, human errors are reduced and multiple datasets can be seamlessly integrated. As a result, overall work time is shortened while quality is improved.

Also, the denser the point cloud data, the more important coordinate alignment becomes. Even slight errors can affect consistency with existing drawings, so accurate coordinates need to be assigned from the surveying stage. Various technologies that meet these needs have emerged and are playing a major role in improving field efficiency.

This article introduces eight methods to automatically assign coordinates to point cloud data acquired by LiDAR surveying to shorten work time. From methods practiced in the field to new technologies, each one directly reduces processing time. By using these, even small teams can acquire and process high-precision 3D point clouds in a short time.

Table of Contents

• Method 1: Collect coordinates simultaneously with RTK-GNSS

• Method 2: Automatic reference alignment using known points and targets

• Method 3: Continuous position correction using an inertial measurement unit

• Method 4: Automatic alignment between point clouds

• Method 5: Unify coordinate systems and vertical datums and enable automatic conversion

• Method 6: Combine smartphone LiDAR with high-precision GNSS

• Method 7: Photo and LiDAR surveying with RTK-capable drones

• Method 8: Simplify control point setup by using GNSS reference station services

• Make field surveying smarter and more efficient with LRTK

Method 1: Collect coordinates simultaneously with RTK-GNSS

By combining high-precision GNSS with LiDAR measurement, you can automatically add latitude, longitude, and elevation coordinates to each point as they are acquired. Known as direct georeferencing, this technology enables you to obtain high-precision point cloud data tied to a global coordinate system directly in the field. With the RTK method, you either set up a base station (control point) on site or receive correction information via a network, and the rover GNSS performs real-time positioning. This eliminates the need to later merge separately prepared control point data with the point cloud. The resulting point cloud is already positioned on the same coordinate system as the entire site, saving the effort of matching coordinates for plans and profiles during post-processing.

For example, if you mount an RTK-GNSS receiver on a terrestrial laser scanner, the point cloud captured after scanning will be output already tied to the local coordinates of the installed control points. RTK-GNSS is also effective for mobile LiDAR surveying on UAVs (drones) or vehicle-mounted systems. Because errors can be corrected in real time along the movement path, multipath and drift can be suppressed.

Large-scale airborne LiDAR surveys also utilize GNSS/INS direct georeferencing. By recording position and orientation in real time, extensive point clouds can be plotted in map coordinates without ground control points, significantly reducing ground work. This approach has been applied to ground and mobile systems as well, making it usable even in smaller, lower-cost setups than before.

With RTK-GNSS installed, there is less need to reassign coordinates to point clouds in post-processing; aside from accuracy checks, the data can be used directly for as-built drawing workflows.

Method 2: Automatic reference alignment using known points and targets

In environments where GNSS signals are weak (urban canyons, mountainous areas, indoors, etc.), the conventional method of placing known control points on site and using them to align point cloud data is effective. Place multiple control points (targets) on site and precisely measure their coordinates with a total station or GNSS beforehand. During LiDAR measurement, place the targets so they appear in the point cloud and let post-processing automatically detect them. For example, use highly reflective white spherical targets or coded new-style targets. Because their distinctive shapes are clearly captured in the point cloud, processing software can automatically detect and identify them.

Once targets are identified in the point cloud, associate them with the pre-measured control point coordinates. Using multiple targets and minimizing the overall deviation via least squares allows calculation of a high-precision transformation matrix even for large point clouds. Converting the point cloud to the site coordinate system in one operation then displays the entire dataset accurately in its real-world spatial relationships. Although setting up targets in the field requires some effort, it substantially reduces PC post-processing effort and ultimately shortens total work time. This target-assisted method can also be applied to photogrammetry. When capturing with drones or smartphones, include a few known markers and use photogrammetry software to correct coordinates later so the entire model aligns to the intended coordinate system.

Method 3: Continuous position correction using an inertial measurement unit

Even in areas where GNSS reception is relatively good, movement during scanning can cause intermittent dropouts. RTK-GNSS provides high-precision positions on site, but GNSS data acquisition cycles are about 1 second, which is not high density. A LiDAR sensor acquires a very large number of points in that interval, and GNSS alone cannot accurately depict the trajectory of a moving platform. This is where an inertial measurement unit (IMU) is useful. An IMU can rapidly output and process orientation and displacement relative to coordinate axes while in motion, allowing it to autonomously continue tracking movement during GNSS outages or intervals.

Navigation systems that integrate GNSS and IMU are widely used for mobile LiDAR surveying. For example, LiDAR units mounted on UAVs measure attitude and position during flight with GNSS+IMU. IMUs are also essential for vehicle-mounted mobile mapping systems and backpack mobile mapping. Using this combination allows the system to specify even small perturbations in orientation or position during point cloud collection, reducing the need for adjustment in later processing. High-precision GNSS+IMU data collection systems deliver fast, pre-processed point clouds already on correct coordinates. As a result, point clouds that match a world coordinate system can be used directly from the start, enabling rapid, high-level field operations with fewer personnel.

For example, without an IMU, mobile surveys in urban areas with building shadows or under trees can lose GNSS intermittently, causing positional inconsistencies that require manual correction in post-processing. By combining INS, the sensor’s trajectory is recorded without interruption, so almost no manual adjustment is needed to stitch datasets together.

Method 4: Automatic alignment between point clouds

When integrating multiple point clouds, using automated matching and registration tools is efficient. Even without specifying common shapes or feature points, software can compare overlapping portions of point clouds and align them. A representative algorithm is the ICP (Iterative Closest Point) method, which can align point clouds with very high accuracy. ICP finds corresponding nearby points among multiple point clouds and progressively minimizes differences, automatically correcting small misalignments. For example, you can merge scans of adjacent areas using common elements such as manhole risers or road inclines that appear in overlapping scans.

Beyond ICP, SLAM (Simultaneous Localization and Mapping) techniques and photogrammetry (SfM-MVS) software also provide automatic alignment methods, but the fundamental concept is the same. Even if a large site is surveyed in sections, using automatic alignment at overlapping areas maintains accuracy. As a result, scans done in multiple passes can be automatically integrated, and each set of point clouds is combined into a single dataset in spatial coordinates. This simultaneously achieves higher accuracy for large projects and reduces working time. Previously, operators had to manually align common features of roads or buildings, but automated algorithms greatly reduce that burden. This is particularly beneficial for aligning point clouds of complex terrain or structures, helping prevent human error and save time.

Method 5: Unify coordinate systems and vertical datums and enable automatic conversion

In outdoor surveying and civil engineering measurements, standard coordinate systems such as Japan’s JGD2011/2020 and vertical datums based on geoid heights are commonly used. However, in LiDAR data, parts of the equipment’s GPS or measurement system may use different references. In other words, point clouds may be on WGS84 or a local coordinate system when acquired, and if not corrected they will not match the site’s true positions. For example, internal workplace coordinate systems may differ from global standard coordinate systems.

To resolve this complicated coordinate issue, it is important to unify coordinate systems and scale in advance. GNSS is convenient but does not inherently provide certain reference values, so even RTK data used directly as map coordinates can cause discrepancies. For example, even if your position is accurately obtained in WGS84, it may not be suitable for placement on official drawings. Therefore, determine the coordinate system and vertical datum to be used in surveying ahead of time and incorporate procedures to transform data accordingly. For example, when measuring control points with GNSS, apply parameters to convert to the site’s local coordinates, or specify the output coordinate system in point cloud processing software to perform automatic conversion. For elevation, applying conversion from ellipsoidal height to geoid height in real time or in post-processing eliminates the need to manually adjust elevations. Thoroughly implementing these settings ensures that acquired point clouds already carry coordinates and heights consistent with design drawings and GIS data, removing the need for manual coordinate corrections. Data can be immediately overlaid with other drawings for review, reducing errors and improving efficiency. Note that public surveying in Japan strictly requires conformance to global geodetic systems (JGD2011/2020) and geoid heights. Introducing automatic conversion mechanisms ensures compliance with such standards and allows acquired point cloud data to be used directly for reliable drawing production.

Method 6: Combine smartphone LiDAR with high-precision GNSS

Recently, smartphone cameras equipped with LiDAR functions have made 3D scanning of equipment and structures easy. However, point clouds captured by smartphones often do not represent accurate positions relative to the site coordinate system due to biases in the device’s built-in IMU and sensors. In this case, mounting a small, portable high-precision GNSS receiver to the smartphone and synchronizing it with the LiDAR data is effective. This allows rapid acquisition of point clouds with centimeter-level accuracy (cm level accuracy, half-inch accuracy) even with small equipment.

The biggest advantage of smartphone LiDAR is mobility and ease of use. Without heavy equipment or additional personnel, the field worker can perform small-area 3D surveys with a single device. For example, it is useful for sites with frequent relocations such as horizontal piping works or small installation areas inside factories. The ability to perform high-density 3D scans on demand is becoming available. This eliminates the need for expensive dedicated LiDAR equipment or so-called “high-precision cameras” that were previously necessary for LiDAR surveying, offering new options for team-based field data collection. This smartphone surveying approach is attracting attention under the Ministry of Land, Infrastructure, Transport and Tourism’s i-Construction initiative and is expected to spread further as a convenient field DX tool.

Method 7: Photo and LiDAR surveying with RTK-capable drones

In aerial photogrammetry and LiDAR surveys using drones, using RTK-capable aircraft allows automatic assignment of high-precision coordinates to acquired data. Conventionally, creating accurate terrain models from aerial imagery required placing numerous ground control points (targets) and manually stitching them. However, with RTK-equipped drones, the aircraft’s position can be determined to centimeter-level accuracy during flight, and positioning information is recorded for each photo and point cloud. Consequently, photos and point clouds are automatically placed in the specified coordinate system in analysis software, greatly reducing the number of ground control points required. For example, sites that previously needed more than 10 ground control points may be adequately validated with only 2–3 verification points when using an RTK drone, significantly compressing fieldwork. Especially for large civil engineering sites or hazardous, hard-to-access terrain, drones can quickly acquire data from above and immediately place it into survey coordinates.

To ensure accuracy, operate the drone’s GNSS connected to a base station or network correction service. If real-time correction is difficult, PPK (post-processed kinematic) can correct the flight trajectory after the flight. In any case, leveraging positioning information in drone surveys reduces ground work while efficiently creating high-precision 3D models.

Method 8: Simplify control point setup by using GNSS reference station services

In RTK surveying, you normally set up your own base station (control point) and use its known position for rover positioning. However, setting up a base station and measuring its coordinates at each site takes time and effort. GNSS reference station services (such as nationwide continuous GNSS networks) are useful here. By connecting to these services, you can obtain high-precision correction information via the internet, enabling accurate positioning with the rover alone. In other words, you can obtain coordinates in real time from a permanent network of reference stations without placing physical reference equipment on site. In Japan, approximately 1,300 continuously operating reference stations are deployed nationwide, and many regions offer real-time correction services.

Using this method simplifies preparation for LiDAR measurement. For example, in small urban surveys you don’t have to set up control points each time; connecting your GNSS receiver to network RTK allows immediate positioning. When moving between multiple sites or when there is no suitable place to set up control points, using GNSS reference station services helps maintain efficiency. Ultimately, you can reduce the time spent on control point measurement and obtain coordinates quickly.

Make field surveying smarter and more efficient with LRTK

The LRTK series are compact high-precision GNSS positioning devices that can be attached to an iPhone. They achieve centimeter-level positioning (cm level accuracy, half-inch accuracy) for construction, civil engineering, and surveying sites, greatly reducing the time required for coordinate acquisition and dramatically improving productivity. As a latest technology compatible with the Ministry of Land, Infrastructure, Transport and Tourism’s i-Construction initiative, it is an optimal solution supporting digital transformation in the industry.

By attaching this device to an iPhone, the smartphone instantly becomes a high-precision GNSS receiver. Launch the dedicated app and simply walk while pointing the camera to obtain real-time corrected absolute coordinates with point cloud data and location information. No complicated setup or complex equipment is required, and a single field worker can use it easily. Automatic coordinate assignment reduces post-survey data adjustment work, enabling immediate drawing and analysis.

If you are considering efficient positioning or LiDAR data acquisition in the field, using LRTK can dramatically improve both efficiency and accuracy. Details about LRTK, including case studies and technical specifications, are available on the official website. Try implementing the latest positioning technology to smarten your surveying work. By leveraging automatic coordinate assignment technologies, a new era has begun in which surveying results can be obtained with unprecedented speed and accuracy. Use these latest technologies to improve field productivity, and continue to adopt efficiency measures suitable for your site while keeping an eye on technological innovation.