RTK (Real-Time Kinematic) and LiDAR (Light Detection and Ranging) are advanced technologies that each play important roles in drone surveying and construction. RTK is a positioning technique using satellites that can obtain position coordinates with centimeter-level (cm level accuracy (half-inch accuracy)) precision. LiDAR, on the other hand, measures distances to targets using laser light and can convert surrounding shapes into detailed three-dimensional data. Each excels in different areas, and their comparison and use in drone-based surveying and mapping have attracted attention. Understanding and appropriately using the strengths and weaknesses of RTK and LiDAR is essential for achieving high-precision and efficient surveying. This article explains the mechanisms and features of RTK and LiDAR in drone surveying, compares their respective strengths and weaknesses, and finally touches on a new approach called “LRTK” for simplified surveying. First, let’s look at how RTK and LiDAR work and their characteristics.

Table of Contents

• How RTK Works and Its Characteristics

• How LiDAR Works and Its Characteristics

• When to Use RTK vs LiDAR

• Simplified Surveying with LRTK

• FAQ

How RTK Works and Its Characteristics

RTK is a technology that uses GNSS (Global Navigation Satellite Systems) to perform real-time, high-precision positioning. Specifically, a base station with known coordinates and a rover (mobile station) receive satellite signals (such as GPS) simultaneously; by applying the error information obtained at the base station to the rover, positions are corrected to centimeter-level (cm level accuracy (half-inch accuracy)) errors. When an RTK receiver is mounted on a drone, corrections are applied to the positioning data and to photo metadata acquired during flight, improving survey accuracy and reducing post-processing effort. In recent years, “network RTK,” which receives correction information from national or commercial reference station networks without placing a local base station, has become widespread, making high-precision positioning more accessible on site.

The main strengths of RTK are as follows:

• Very high positioning accuracy: RTK positioning with dedicated equipment yields horizontal and vertical errors on the order of a few centimeters (cm level accuracy (half-inch accuracy)). This is orders of magnitude more precise compared to standalone positioning (GPS-only), which can have errors of several meters.

• Obtained position information is in absolute coordinates: Positions measured by RTK are obtained as absolute coordinates on maps, such as latitude/longitude or public coordinate systems. Therefore, coordinates obtained in surveying can be used directly in drawings or map coordinate systems, making alignment with design drawings and management of as-built data straightforward. For example, in drone surveying, RTK allows acquired data to be tied to known reference coordinates without installing many ground control points.

• Real-time results: As the name implies, RTK enables real-time positioning, allowing instant confirmation and recording of current positions during measurement. This lets operators assess data quality on site and is useful for tasks requiring immediacy, such as guidance for automated machinery or control of unmanned construction.

• Small influence from time of day or weather: GNSS satellite signals can be received day or night, and accuracy does not typically degrade drastically in rain, so RTK can maintain stable precision. Unlike optical sensors, RTK can also be used in dark conditions.

On the other hand, RTK has the following weaknesses and challenges:

• Constraints on the positioning environment: High-precision RTK requires reception of satellite signals, so accuracy degrades significantly in environments without clear sky view. In forests, under bridges, in urban canyons surrounded by buildings, inside tunnels, or indoors, satellite signals can be blocked or reflected, and a fixed solution (cm-level positioning) may not be obtainable.

• Dependence on communication infrastructure: Receiving real-time correction information requires communication via radio or cellular networks. RTK can be difficult in areas with unstable communications, such as remote mountains or during disasters. For network RTK, being out of network coverage means correction data cannot be obtained and accuracy deteriorates.

• Equipment and upfront costs: Traditional RTK GNSS receivers were typically large, tripod- or pole-mounted devices that were expensive and required time-consuming setup. Although miniaturization and cost reduction have progressed, high-precision RTK equipment remains more expensive than general GNSS receivers, posing a barrier to entry for surveying beginners.

How LiDAR Works and Its Characteristics

LiDAR (Light Detection and Ranging) is a remote sensing technology that uses laser light to measure distances to targets and capture surrounding shapes in three dimensions. Its mechanism is simple: the time it takes for an emitted laser pulse to hit an object, reflect, and return is used to calculate distance. This is repeated at very high frequencies—tens to hundreds of thousands of times per second—and the resulting multitude of points (point cloud data) records the space. Drone-mounted LiDAR sensors scan the ground and structures during flight and can create detailed terrain models from high-density point clouds. Compared to photogrammetry, LiDAR is advantageous for acquiring terrain data in environments where camera imaging is difficult, such as under forest canopy or at night.

The main strengths of LiDAR are as follows:

• Precise acquisition of shape data: Point clouds from laser ranging record surrounding shapes at high resolution. They can detect subtle surface irregularities on the order of a few millimeters and are suitable for recording dimensions and shapes of complex structures. LiDAR can capture thin objects like power lines or fine ground undulations that are difficult for photogrammetry to detect.

• Not affected by ambient light: As an active sensor that emits its own laser, LiDAR is not influenced by surrounding light. It operates reliably at night or in dark conditions, enabling 24-hour measurements. LiDAR is effective in situations challenging for optical cameras, such as inside unlit tunnels or night-time surveys after sunset.

• Data acquisition through obstacles: Laser beams are narrow and can pass through gaps in vegetation to reach the ground. This makes LiDAR powerful for acquiring understorey terrain in wooded areas (which photogrammetry cannot easily capture). Also, LiDAR can perform relative shape scanning even in areas where GPS signals cannot reach, such as inside forests or indoors.

• Flexible post-acquisition analysis: Point clouds from LiDAR contain three-dimensional information, allowing arbitrary cross-sections to be extracted and distances or volumes to be measured during post-processing. Point clouds can be colorized and visualized as 3D models as needed.

Conversely, LiDAR has the following weaknesses and challenges:

• High equipment cost: High-performance laser scanners are very expensive. Even lightweight drone-mounted LiDAR systems can cost several million yen, and LiDAR for terrestrial or mobile mapping systems can reach tens of millions of yen. High equipment prices require significant investment to introduce.

• Unsuitable for absolute positioning by itself: LiDAR alone obtains relative distances to objects; point cloud data do not inherently include absolute position coordinates (e.g., latitude/longitude). To place point clouds into a map coordinate system, GNSS positioning information or alignment with known points is indispensable. LiDAR excels at shape measurement, but combining it with other technologies is required to add position information to measurement results.

• Influence of weather conditions: Laser light is easily scattered by particles in the atmosphere, so dense fog or heavy rain reduce the measurable range and accuracy. In low-visibility conditions, point density drops and data may have gaps or increased noise.

• Data processing burden: LiDAR point clouds are very large. Post-processing and analysis require high-performance computers and specialized software, and processing time and labor costs tend to be higher than for photogrammetry. Preprocessing, such as noise removal and filtering of unwanted points, also requires effort.

When to Use RTK vs LiDAR

As described above, RTK and LiDAR excel in different areas. RTK is superior for accurately measuring spatial position coordinates, while LiDAR is superior for obtaining detailed three-dimensional shapes of objects and terrain. Therefore, in actual surveying workflows it is effective to divide roles: RTK for positioning, LiDAR for shape measurement. The two technologies are complementary, and their combined use brings out their true value.

For example, in drone surveying, mounting a high-precision RTK-GNSS receiver on the drone automatically tags aerial photos and LiDAR point clouds with positional coordinates. This reduces or eliminates the need for numerous ground control points and allows generation of high-precision orthophotos and DSMs (digital surface models). RTK-capable drones have become widespread in recent years, and methods to obtain 3D survey results with centimeter-level (cm level accuracy (half-inch accuracy)) precision from photos are already in practical use. Meanwhile, drone-mounted LiDAR is effective for detailed measurements in forested areas or of complex structures. By directly scanning the ground from above, it can acquire ground data unavailable to photogrammetry (such as terrain under trees), and has been increasingly used in civil engineering for forest surveying and surveying disaster sites.

In construction site as-built management, it is also common to use RTK for establishing reference points and baseline elevation measurements, combined with terrestrial LiDAR scanners or mobile mapping systems for overall shape capture and as-built data acquisition. For example, accurately calculating earthwork volumes may involve measuring heights of known points with RTK beforehand and then aligning LiDAR point cloud elevation data to that baseline.

In this way, using RTK and LiDAR appropriately where they are most suitable is indispensable for efficient and high-precision surveying. Depending on the purpose and site conditions, surveys may be completed with only RTK or only LiDAR, but combining both can compensate for each other’s weaknesses. Keep the principle “RTK for position, LiDAR for shape” in mind and flexibly select technologies as needed. Measurement solutions that combine RTK-GNSS and LiDAR are expected to become increasingly widespread.

Simplified Surveying with LRTK

A recent newcomer, LRTK, is a new approach that makes RTK positioning easier to use. LRTK is a palm-sized integrated RTK-GNSS receiver that bundles the antenna, battery, and communication module into a small device. It can be attached to a smartphone or tablet, miniaturizing RTK equipment that used to be mounted on tripods or long poles down to pocket size. As a result, portability on site has dramatically improved, and it is now possible to walk around carrying a complete set of surveying equipment in one hand.

For example, an LRTK Phone device (smartphone-mounted) can be attached to an iPhone and used while leaving the other hand free during positioning tasks. It supports Bluetooth connection, eliminating complicated cabling. Once powered on and initialized within a short time on site, high-precision positioning can begin immediately. Some models also support offline RTK corrections for use when out of network coverage or when infrastructure is down, making them valuable for recording disaster sites in emergencies.

Furthermore, by integrating with dedicated apps and cloud services, LRTK enables a new form of simplified surveying. Combining a smartphone camera or LiDAR scanner with LRTK’s high-precision positioning allows a single person to perform a variety of measurements easily. For instance, photos taken with a smartphone can be automatically tagged with positioning metadata (latitude, longitude, elevation, orientation), and point clouds acquired by a phone’s LiDAR scanner can be tied to absolute coordinates to generate high-precision 3D data. This has made it possible in many cases to replace traditional measurements that required multiple people and specialized equipment with just a smartphone plus LRTK. If everyone on site can carry high-precision surveying tools in their pocket, it could greatly shorten work time and improve productivity.

LRTK, which combines the cutting-edge technologies of RTK and LiDAR while prioritizing portability and ease of use, is a solution that “brings high-precision positioning closer.” In many situations, sufficient surveying can be performed with a small device and a smartphone without drones or expensive laser scanners. For sites that require high-precision positioning and measurement but struggle with cost or operations, it is worth considering LRTK as a new option. In short, LRTK makes it easy to leverage RTK’s “position” and LiDAR’s “shape.” It is truly a tool that could open a new era in surveying.

FAQ

Below are frequently asked questions related to the content of this article, with answers.

Q1. What is the difference between RTK and PPK? A. RTK (Real-Time Kinematic) is a method that corrects positioning errors in real time while deriving positions. PPK (Post-Processed Kinematic) corrects observed data in post-processing. RTK has the advantage of providing high-precision positions on site instantly, but requires a communication environment. PPK cannot provide immediate results on site, but by processing after flight with base station data it can achieve equivalent high precision without communications, allowing stable positioning. Each has pros and cons, and they are chosen based on site conditions and operational requirements.

Q2. Is RTK mandatory for drone photogrammetry? A. It is not mandatory, but it is very useful for improving accuracy. Even drones without RTK can achieve high-precision survey results if a sufficient number of ground control points (GCPs) are installed. However, RTK-equipped drones automatically tag photos with high-precision position information during flight, reducing the number of control points needed or, in some cases, eliminating the need to install them. This shortens work time and improves confidence in data accuracy. Therefore, for photogrammetry that requires high precision, using RTK-capable platforms is recommended.

Q3. When is a LiDAR-equipped drone effective? A. It is effective when you want to obtain detailed and efficient measurements of ground surface shapes. Especially in forested or vegetated areas, drone photogrammetry cannot capture terrain under trees, but LiDAR can reach the ground through tree gaps, making it suitable for surveying terrain in wooded areas. LiDAR-equipped drones are also powerful for assessing collapsed terrain at disaster sites and inspecting fine structures like power lines and towers. However, equipment costs are high and operation is specialized, so for small sites or tight budgets LiDAR may be excessive.

Q4. Which is more accurate: LiDAR surveying or photogrammetry? A. It depends on conditions, but in open areas both aerial photogrammetry and LiDAR surveying can achieve centimeter-level (cm level accuracy (half-inch accuracy)) accuracy with proper processing. LiDAR is not inherently always more accurate. However, LiDAR tends to reflect surface details well due to high point density, which can be advantageous for measuring complex structures or vertical measurements where photogrammetry may have larger errors. Photogrammetry can provide strong planar accuracy if image resolution is high and is effective for obtaining area-based information via orthophotos. Each method has different precision strengths, so choose based on surveying objectives.

Q5. Can smartphone LiDAR scanners be used for surveying? A. For small areas, yes. Recent smartphones (e.g., high-end iPhone models) include LiDAR scanners that can capture surrounding shapes as point clouds up to a few meters away. Standalone, they can perform simple 3D measurements but have limited positioning accuracy and are not suited for wide-area surveys. However, when combined with high-precision GNSS devices like LRTK, point clouds from smartphone LiDAR can be given absolute coordinates to produce more practical survey data. For example, measuring interior dimensions or documenting conditions in confined sites where drones cannot fly is increasingly feasible with smartphone + LRTK surveying.