RTK vs LiDAR: Comparing Strengths and Weaknesses in Drone Surveying

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 technology that uses satellites to acquire position coordinates with centimeter-level accuracy (cm level accuracy (half-inch accuracy)). LiDAR, on the other hand, measures distances to targets using laser light and can convert surrounding shapes into detailed 3D data. Each excels in different areas, and their comparison and methods of use are gaining attention in drone-based surveying and mapping. Understanding the strengths and weaknesses of RTK and LiDAR and when to use each is essential for high-precision and efficient surveying. This article explains the mechanisms and characteristics of RTK and LiDAR in drone surveying and compares their strengths and weaknesses. At the end of the article, we also touch on a new approach for simple surveying called "LRTK." First, let’s look at the mechanisms and characteristics of RTK and LiDAR.

Table of Contents

• How RTK Works and Its Features

• How LiDAR Works and Its Features

• When to Use RTK vs LiDAR

• Simple Surveying with LRTK

• FAQ

How RTK Works and Its Features

RTK is a technology that uses GNSS (Global Navigation Satellite System) to perform high-precision position measurements in real time. Specifically, a reference station with known coordinates and a rover receive satellite signals (such as GPS) simultaneously, and the error information obtained at the reference station is applied to the rover to correct the position down to centimeter-level errors (cm level accuracy (half-inch accuracy)). When a drone is equipped with an RTK receiver, the photos and positioning data acquired during flight are corrected, improving survey accuracy and reducing post-processing effort. In recent years, "network RTK," which receives correction information from national or private continuously operating reference station networks without placing a local base station, has also 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. This is orders of magnitude more precise than standalone positioning (GPS-only), which typically has meter-level errors.

• Position information is in absolute coordinates: Positions measured by RTK are obtained as absolute coordinates on a map, such as latitude/longitude or public coordinate systems. Therefore, coordinates obtained from surveys can be directly used in drawings or map coordinate systems, making comparison with design drawings and management of as-built results easier. For example, in drone surveying, using 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 the current position to be confirmed and recorded immediately during measurement. This makes it possible to assess data quality on site and to use position information for automated machine guidance or unmanned construction control where responsiveness is required.

• Less affected by time of day or weather: GNSS satellite signals can be received day or night, and positioning accuracy does not drop drastically in rain, so RTK positioning maintains stable accuracy. Unlike optical sensors, RTK can be used in dark environments as well.

On the other hand, the weaknesses and challenges of RTK include the following points:

• Constraints on the positioning environment: High-precision RTK positioning requires reception of signals from satellites, so accuracy degrades significantly where the sky is not open. In forests, under bridges, in urban canyons with many tall buildings, tunnels, or indoors, satellite signals can be blocked or reflected, and a fixed solution (cm-level positioning solution) may not be obtainable.

• Dependence on communication infrastructure: Receiving real-time correction information requires communication via radio or cellular networks. Therefore, RTK can become difficult in mountainous areas with unstable radio or in disaster situations. For network RTK, correction data cannot be obtained outside the communication coverage area, which leads to reduced accuracy.

• Equipment and initial cost: Traditional RTK GNSS receivers were large units mounted on tripods or poles, expensive and time-consuming to set up on site. Although devices have recently become smaller and cheaper, high-precision RTK equipment remains more expensive compared to general GNSS receivers, creating a barrier for surveying beginners to adopt easily.

How LiDAR Works and Its Features

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. The mechanism is simple: the distance is calculated from the time it takes for emitted laser pulses to hit an object, reflect, and return. This process is repeated hundreds of thousands of times per second, and the resulting multitude of points (point cloud data) records the space. Drone-mounted LiDAR sensors can scan the ground surface and structures while flying to create detailed terrain models from high-density point clouds. Compared to photogrammetry, LiDAR has the advantage of acquiring terrain data in environments where camera imaging is difficult, such as in forests or at night.

The main strengths of LiDAR are as follows:

• Accurate capture of shape data: Point clouds obtained by laser ranging record surrounding shapes with high resolution. They can detect slight irregularities in terrain or structures on the order of a few millimeters (a few tenths of an inch) and are suitable for recording dimensions and shapes of complex structures. LiDAR can capture thin objects like wires and fine surface undulations that are difficult for camera-based photogrammetry.

• Unaffected by ambient light: LiDAR is an active sensor that emits laser light for measurement and is not influenced by surrounding light. Therefore, it operates well at night or in dark places and enables 24-hour measurement. LiDAR is effective in conditions difficult for optical cameras, such as measurements inside unlit tunnels or nighttime surveys after sunset.

• Data acquisition through obstacles: Because laser beams are narrow, they can pass through gaps in trees to reach the ground. This allows LiDAR to be powerful for obtaining understory terrain in forested areas (which photogrammetry cannot capture). Also, LiDAR can perform relative shape scanning even in forests or indoors where GPS signals do not reach.

• Flexible post-acquisition analysis: Point cloud data from LiDAR contains three-dimensional information, allowing arbitrary cross-sections to be extracted and distances and volumes to be measured in post-processing. Colors can be added to point clouds for visualization as 3D models if needed.

On the other hand, the weaknesses and challenges of LiDAR include the following points:

• High equipment cost: High-performance laser scanners are very expensive. Even lightweight LiDAR for drones can cost several million yen, and LiDAR for ground-mounted or mobile mapping systems can reach tens of millions of yen. The high equipment price requires significant investment.

• Not suitable for positioning: LiDAR alone measures relative distances to objects; point cloud data does not include absolute position coordinates (such as latitude/longitude). To place obtained point clouds in a map coordinate system, GNSS positioning information or alignment with known points is indispensable. LiDAR excels at shape measurement, but adding position information to results requires combining it with other technologies.

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

• Processing burden: LiDAR point cloud data can be very large. Post-processing and analysis require high-performance computers and specialized software, increasing processing time and operational costs compared to photogrammetry. Preprocessing tasks such as noise removal and filtering of unwanted points also require effort.

When to Use RTK vs LiDAR

As described above, RTK and LiDAR excel in different areas. RTK is strong at accurately measuring spatial position coordinates, while LiDAR is strong at capturing the three-dimensional shape of objects and terrain in detail. Therefore, in actual surveying operations, it is effective to assign roles such as "RTK for positions, LiDAR for shapes." The two technologies are complementary, and their combination brings out their full value.

For example, in drone surveying, equipping the drone with a high-precision RTK-GNSS receiver allows automatic tagging of position coordinates to aerial photos or LiDAR point clouds. This enables generation of high-precision orthophotos and DSMs (digital surface models) without installing numerous ground control points that were previously necessary. Recently, RTK-capable drones have become widespread, and methods for obtaining 3D survey deliverables with centimeter-level accuracy (cm level accuracy (half-inch accuracy)) from aerial photos have been put into practical use. Meanwhile, drone-mounted LiDAR is effective for detailed measurement in forested areas or complex structures. Scanning the ground directly from the air can capture ground data that photogrammetry cannot (such as terrain under trees), and LiDAR use is expanding in civil engineering for forest surveys and terrain assessment at disaster sites.

In construction site as-built management, it is common to use RTK for establishing benchmarks and baseline height measurements, and combine ground-based LiDAR scanners or mobile mapping systems to capture the overall terrain and as-built data. For example, accurate earthwork volume calculations may use RTK to measure known point elevations in advance and then align LiDAR point cloud elevation data to that reference.

Using RTK and LiDAR appropriately for each purpose is essential for highly efficient and accurate surveying. Depending on objectives and site conditions, some projects can be completed with only RTK or only LiDAR, but combining both can compensate for each other’s weaknesses. Keep in mind the guideline: position with RTK, shape with LiDAR, and select technologies flexibly as needed. Measurement solutions that combine RTK-GNSS and LiDAR are expected to become increasingly widespread.

Simple Surveying with LRTK

The recently introduced LRTK is a new approach that makes RTK positioning easier to use. LRTK is a palm-sized integrated RTK-GNSS receiver, provided as a small device with antenna, battery, and communication module all in one. 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, enabling an era in which a full set of surveying equipment can be carried around in one hand.

For example, an LRTK Phone device (smartphone-mounted) can be attached to an iPhone or similar device, allowing the other hand to remain free during positioning work. It supports Bluetooth connection, eliminating complicated cabling. After turning it on and completing a short initialization on site, high-precision positioning can begin immediately. Some models also support offline RTK corrections to prepare for being outside communication coverage or infrastructure outages, making them powerful tools for recording disaster sites and other emergency situations.

Furthermore, by integrating LRTK with dedicated apps and cloud services, LRTK enables unprecedented simple surveying. Combining a smartphone camera or LiDAR scanner with LRTK’s high-precision positioning makes it easy for one person to carry out various measurements. For example, photos taken by a smartphone can be automatically tagged with positioning information (latitude/longitude/elevation/heading), or point clouds captured by a smartphone LiDAR can be tied to absolute coordinates to generate high-precision 3D data. As a result, measurement tasks that previously required multiple people and dedicated equipment can increasingly be replaced with just a smartphone and LRTK. If high-precision surveying equipment that anyone on site can take from their pocket becomes available, it will greatly contribute to shorter work times and increased productivity.

LRTK, which combines the cutting-edge technologies of RTK and LiDAR while pursuing portability and ease of use, is a solution to make high-precision positioning more accessible. In many situations, sufficient surveying can be achieved with a small device and a smartphone without using drones or expensive laser scanners. For sites that need high-precision positioning and measurement but face cost or operational constraints, it is worth considering this new option of LRTK. In short, LRTK makes it easy to leverage RTK’s "position" and LiDAR’s "shape." It can truly be called a tool that pioneers a new era in surveying.

FAQ

Below are frequently asked questions related to the content of this article and their 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 obtaining positions. PPK (Post-Processed Kinematic) corrects observation data in post-processing. RTK’s advantage is that high-precision positions are available immediately on site, but it requires a communication environment. PPK cannot provide immediate results on site, but by processing after flight with base station data, it can achieve comparable high precision without requiring communication, enabling stable positioning. Each has advantages and disadvantages, and they are used according to site conditions and operational requirements.

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

Q3. When is a LiDAR-equipped drone effective? A. It is effective when you want to capture surface shapes in detail and efficiently. Especially in forested or vegetated areas, drone photogrammetry cannot capture terrain beneath trees, but LiDAR’s lasers can pass between trees to reach the ground, making LiDAR suitable for forest terrain surveys. LiDAR-equipped drones are also powerful for assessing landslide topography at disaster sites and inspecting fine structures like power lines and towers. However, because equipment costs are high and operation is specialized, LiDAR can be excessive for small sites or tight budgets.

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 accuracy (cm level accuracy (half-inch accuracy)) with proper processing. LiDAR is not inherently always more accurate. However, LiDAR’s high point density better reflects surface detail, making it advantageous for measuring dimensions of complex structures and for height measurements where photogrammetry tends to have larger errors. Photogrammetry, when using high-resolution camera images, can secure good planimetric accuracy and is strong in obtaining planar information via orthophotos. Each method has different strengths in terms of achievable accuracy, so select based on the survey objective.

Q5. Can a smartphone LiDAR scanner be used for surveying? A. It is possible for small areas. Recent smartphones (for example, higher-end iPhone models) include LiDAR scanners that can capture surrounding shapes as point clouds up to several meters away. While standalone smartphone LiDAR can perform simple 3D measurements, its positioning accuracy is limited and not suitable for wide-area surveys. However, combining it with a high-precision GNSS device like LRTK enables assignment of absolute coordinates to point clouds captured by smartphone LiDAR, yielding more practical survey data. For example, smartphone + LRTK surveying is increasingly useful for indoor dimension measurement or for assessing confined sites where drone flight is not possible.