For some people, the datasheet of a LiDAR scanner can be quite complex. Today, we will introduce you to some common terms found in the specifications sheet, unveiling the mystery behind the LiDAR scanner. We will explain the obscure and difficult-to-understand terms, their meanings, and why they are important.
The "Laser Class" of a LiDAR scanner refers to the classification of the laser used in the scanner, indicating how hazardous the beam is to the human eye or skin. The classification system ranges from Class 1 (safe under all conditions of normal use) to Class 4 (may pose a hazard to the eyes or skin).
Virtually all LiDAR scanners use Class 1 lasers, which is the safest class. That means the scanner is completely harmless, to the point where you (or a passerby) can look directly at it without any eye protection and experience no negative effects.
When evaluating a LiDAR scanner, understanding the Laser Class is crucial for ensuring compliance with safety standards and regulations, as well as implementing the necessary safety protocols during operation to protect users from potential laser hazards.
The "Laser Wavelength" of a LiDAR scanner refers to the specific wavelength of the laser beam emitted by the scanner for data collection. Common laser wavelengths used in LiDAR systems include near-infrared wavelengths such as 905 nm and 1550 nm, which are often chosen for their ability to penetrate vegetation and provide accurate distance measurements.
The choice of wavelength has a big effect on the performance of the laser. A 1550 nm laser is more likely to be absorbed by water in the environment, like fog, rain, or even humidity in the air. To counteract this problem, the laser would need to use more power — meaning shorter battery life. A 905 nm laser won’t lose performance in these conditions and is much simpler to manufacture.
The term "Laser Line Number" in the context of a LiDAR scanner typically refers to the number of individual laser beams or lines emitted by the scanner to collect data. Each laser line contributes to the generation of a point cloud by measuring distance and capturing spatial information.
A higher laser line number usually results in denser point clouds, allowing for more detailed and accurate 3D representations of the scanned environment. This can lead to improved resolution and better coverage of the scanned area.
"Points Per Second" in the context of a LiDAR scanner refers to the number of individual data points that the scanner can capture and process in one second. This metric is a crucial indicator of the scanning speed and data acquisition capability of the LiDAR system.
A higher Points Per Second value signifies that the LiDAR scanner is capable of capturing a larger amount of data points within a given time frame. This parameter is essential for applications that require rapid data collection, such as airborne LiDAR mapping or scanning moving objects. But remember that a higher number of points per second is not always better. Once you have enough points in the cloud for your intended application, capturing more points makes your point cloud bigger and heavier to process.
The Points Per Second metric is influenced by various factors including the scanning mechanism, laser pulse rate, field of view, and scanning range of the LiDAR scanner. Understanding this specification helps in assessing the efficiency and performance of a LiDAR system for specific data acquisition tasks and applications.
The "range" of a LiDAR scanner refers to the maximum distance over which the scanner can detect and measure objects. On the surface, it is simple: Range indicates the distance your scanner can be from an object and still return usable results. But don’t assume that this number indicates the distance a laser scanner can capture and still hit the accuracy levels marked on the spec sheet. Rigorous testing (and field experience) will show that a laser scanner’s accuracy decreases as it moves farther from the object. On top of that, there are a huge number of other factors that can affect the accuracy of a LiDAR sensor, even at a constant range.
The range of a LiDAR scanner can vary significantly depending on the specific model and design. Some LiDAR scanners are optimized for short-range applications, such as indoor mapping or object detection, with ranges typically up to a few hundred meters. On the other hand, long-range LiDAR scanners are designed for applications like aerial mapping, autonomous driving, or topographic surveys, with ranges that can extend to several kilometers.
The "FOV" of a LiDAR (Light Detection and Ranging) scanner refers to the Field of View of the scanner. It represents the angular extent of the environment that the scanner can "see" or capture data from at any given point in time.
The FOV of a LiDAR scanner is typically described in terms of horizontal and vertical angles. The horizontal FOV indicates the extent of the scanning range in the horizontal plane, while the vertical FOV represents the coverage in the vertical plane.
A wider FOV allows the LiDAR scanner to capture data from a broader area in a single scan, while a narrower FOV focuses on a smaller, more detailed area. The FOV of a LiDAR scanner influences the scanning efficiency, coverage, and resolution of the collected data.
The "Relative accuracy" of a LiDAR scanner refers to the precision and consistency of the measurements taken by the scanner within a dataset relative to each other. It describes how closely data points are positioned in relation to one another in the collected point cloud data.
Relative accuracy is a crucial metric in LiDAR scanning as it measures the internal consistency of the data points and their spatial relationships. Higher relative accuracy indicates that the data points are closely aligned and consistent with each other, leading to a more reliable and accurate representation of the scanned environment.
Understanding the relative accuracy of a LiDAR scanner is important for assessing the quality and reliability of the collected data, especially in applications where precise spatial information is critical, such as topographic mapping, infrastructure monitoring, and urban planning.
The accuracy of a point cloud on a local scale. For a mobile scanner, this is the accuracy of measurement between points in a single location like a room.
The accuracy of the point cloud on a global scale. It describes how accurately the collected data points correspond to their real-world positions.
Absolute accuracy is a fundamental metric in LiDAR scanning as it assesses the alignment of the scanned data with external reference points or coordinates, such as GPS data or control points on the ground. High absolute accuracy indicates that the LiDAR scanner can accurately determine the real-world positions of objects and features in the scanned area.
Understanding the absolute accuracy of a LiDAR scanner is crucial for applications that require precise geospatial information, such as land surveying, infrastructure inspection, and urban planning, where accurate spatial positioning is essential for making informed decisions.
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