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Mastering LiDAR with DJI Enterprise: An Introductory Booklet

 
Unlocking Aerial Mapping and Data Collection: Elevate Your Operations with the Power and Precision of DJI’s LiDAR Technology

Unlocking Aerial Mapping and Data Collection: Elevate Your Operations with the Power and Precision of DJI’s LiDAR Technology

In today’s rapidly advancing technological landscape, LiDAR stands out as a pivotal tool for various applications, from forestry management to infrastructure inspection. Dive into the world of LiDAR with DJI Enterprise’s comprehensive guide. From foundational principles to real-world applications, this booklet equips readers with essential knowledge on LiDAR technology and its transformative potential.

Introduction and Principles of the LiDAR Technology

What is LiDAR?

LiDAR, which stands for Light Detection and Ranging, is a remote sensing technology that uses rapid laser pulses to map out the surface of the target. By sending out a laser beam and measuring the time it takes for the light to reflect back from objects, LiDAR creates detailed three-dimensional point maps.

Imagine you’re in a completely dark room with a flashlight. If you point the flashlight at various objects, the light will bounce back, and by seeing that light, you can get an idea of where things are and how far away they are. The more times you shine your light and from different angles, the better idea you’ll get about the layout of the room. LiDAR works similarly but instead of using visible light like a flashlight, it uses invisible laser light. Here’s how it functions:

  1. Emission: A LiDAR device sends out a rapid pulse of laser light toward an object.
  2. Reflection: The light then reflects off the object and returns to the LiDAR sensor.
  3. Detection: The device measures the time it took for the light to return. Since the speed of light is a constant, this duration time can be used to calculate the distance between the LiDAR sensor and the target object.

LiDAR vs. Photogrammetry

The LiDAR system measures data, whereas the Photogrammetry system calculates it. This key difference makes them better suited for different applications. LiDAR uses laser pulses to measure reality, making it ideal for applications that require absolute data certainty. LiDAR can penetrate through vegetation and is not affected by lighting conditions, making it a great option for mapping forests or other areas with dense vegetation cover. LiDAR is also useful for creating accurate terrain models and topographic maps.

Photogrammetry uses cameras to capture overlapping images of an area, which are then stitched together to create a 3D model or ortho map. It is less expensive than LiDAR and can be used with off-the-shelf hardware like any drones and cameras. This makes it useful for creating highly detailed models of buildings and infrastructure, as well as high-resolution orthomaps for inspection and monitoring applications.

 

Aspect Photogrammetry LiDAR
Definition A technique of obtaining measurements and 3D models from photographs. A remote sensing method using laser light to measure distances, and generate precise 3D models of the Earth’s surface.
Accuracy High accuracy in well-lit and clear conditions after apply GCPs under RTK. Accuracy rely on the initial POS state, not dependent on lighting conditions.
Cost Generally lower cost, more affordable for small-scale projects. Higher cost due to sophisticated equipment and processing requirements.
Terrain Handling Performs well in urban environments and clear landscapes. Excellent in various terrains, including dense vegetation and urban landscapes.
Data Processing Time-consuming processing, especially for large datasets. Processing is faster because the data is captured in spatial coordinates format natively.
Light Conditions Requires good lighting for optimal results. Effective in any lighting conditions, including night.
Vegetation Penetration Struggles with dense vegetation. Capable of penetrating dense vegetation to reach the ground.
Weather Dependency Performance can be affected by weather conditions like clouds and rain. Less affected by weather conditions.
Spatial Resolution High spatial resolution for surface details. Lower spatial resolution compared to photogrammetry.
Application Ideal for cultural heritage documentation, small-scale mapping, and architecture. Best suited for large-scale topographic mapping, forestry, and urban planning.

What are the Components of an Integrated Airborne LiDAR System?

Hardware Components

LiDAR System

  • LiDAR Module: The most important component of the LiDAR system, the laser module generates a pulsed laser beam that is directed at the target surface. The laser module is made up of multiple components, including the laser light source, receiver, optical components, and electronic controller.
    • Laser Light Source: It generates short pulses of laser light that are used to measure the distance between the LiDAR sensor and objects in the environment.
    • Receiver: It detects the reflected laser light and converts it into an electronic signal that can be processed by the LiDAR system.
    • Optical Components: These components are responsible for directing and focusing the laser beam toward the target surface and collecting the reflected light.
    • Electronic Controller: It controls the timing and duration of the laser pulses and processes the signals from the receiver.
  • GNSS (Global Navigation Satellite System) receiver is used to provide accurate georeferencing for scanned LiDAR results. Most UAV LiDAR systems either use their own individual GNSS system for logging satellite data for georeferencing and post-processing or are integrated with DJI PSDK and use the GNSS system from the drone system.
  • IMU (Inertial Measurement Unit)  is a device that measures the acceleration and angular rate of a LiDAR system. By integrating these measurements over time, the IMU can determine the position, velocity, and attitude of the LiDAR system in three-dimensional space. This information is used to correct for any motion or vibrations of the LiDAR system during the data collection process.
  • INS (Inertial Navigation System) uses the raw data from an IMU and integrates it to provide position, velocity, and orientation information of an object relative to a known starting point, orientation, and velocity. INS takes the IMU data and integrates it with GNSS positioning information to provide a continuous estimation of the position and orientation of the LiDAR sensor during the data capture.

UAV System

  • UAV or unmanned aerial vehicle is used to fly the LiDAR system over the area being surveyed, and it can be equipped with its own GNSS and RTK/PPK system for accurate georeferencing of the LiDAR system.

Software Components

  • Flight Mission Planning Software is utilized to plan the flight path of a drone equipped with a LiDAR system. This software enables the user to define an area to be surveyed and then automatically generates a waypoint-based flight route. The user can adjust UAV system parameters and sensor actions for the autonomous waypoint flight. The software then generates a flight path that efficiently covers the area and collects the necessary data for the LiDAR system. This data can be used to create detailed 3D maps or models of the surveyed area.
  • Flight Monitoring and Control Software allows the user to monitor the flight path and status of the UAV and LiDAR system in real-time during data collection. The software can display various parameters such as altitude, speed, and battery level. This information is crucial for ensuring the safety of the UAV and collecting high-quality LiDAR data. Additionally, the flight monitoring software can alert the user in case of any issues or malfunctions during the flight.
  • Raw Point Cloud Processing Software is OEM software developed by sensor manufacturers. It is used to process raw LiDAR data collected from all system components and output the LiDAR data into a manipulable format such as LAS/LAZ for further use.
  • Point Cloud Processing Software refers to computer programs that are designed to manipulate and analyze point cloud data. Depending on the application, point cloud processing software can be used for various tasks such as creating drawings, performing measurements, extracting surfaces, classification, and more.

 

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Key Terminologies and Knowledge

Object Surface Reflectivity

  • Different object surfaces have varying rates of reflectivity.
  • Most object surfaces have a reflectivity of above 10%.
  • Water is a strong absorber, and a typical LiDAR laser with a wavelength of 905nm will be absorbed directly. Unless the LiDAR is of the bathymetric type and the laser wavelength is shorter, it will not penetrate water.

Here are some examples of surface reflectivity rates:

  • Fresh asphalt: 4-7%
  • Dry grass: 15-20%
  • Forest canopy: 5-20%
  • Wet concrete: 30-50%
  • Snow: 60-90%
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                        Point cloud colorized by base on surface reflectivity (Red is high, blue is low)

 

LiDAR Scanning Methods

By changing the rotation method inside the LiDAR sensor, the LiDAR system can achieve two different mechanical scanning modes: repetitive scan and non-repetitive scan.

Repetitive Scanning Method

Repeated scanning only covers the horizontal FOV (70.4°×4.5°)

Advantage: In mobile mapping, objects are only scanned for a very short period of time, because the inertial navigation accuracy drift is very small in a short period of time, so the scanned model is relatively more accurate.

Disadvantage: The vertical FOV is very small and there is almost no vertical surface information. If vertical surface information is required, at least two flight paths need to be planned to compensate for the loss of vertical FOV.

Application: For scenarios with relatively mild terrain and high accuracy requirements, such as terrain measurement, general DEM/DSM generation.

*It is recommended to use repetitive scan in surveying to ensure point cloud accuracy.

: For scenarios with relatively mild terrain and high accuracy requirements, such as terrain measurement, general DEM/DSM generation.

*It is recommended to use repetitive scan in surveying to ensure point cloud accuracy.

             Repetitive Scan Animation (Top-down View)

Non-repetitive Scanning Method

Non-repetitive scanning can quickly cover the entire FOV (70.4°×77.2°)

Advantages: Provides full FOV coverage, can perform vertical scanning, and obtains good vertical information from a single scan without setting a gimbal angle.

Disadvantage: In mobile mapping, objects are scanned at different positions and times, relying on consistent inertial navigation accuracy. If the accuracy of inertial navigation drifts over time, the accuracy of the model will decrease. This results in blurred or duplicated objects, thicker point clouds, and thicker wires. This effect is particularly pronounced in non-repetitive scans, which have a larger field of view.

Application: Suitable for scenarios with relatively low accuracy requirements, high efficiency requirements, and complete elevation information requirements, such as urban 3D modeling, complex three-dimensional structure modeling, power line inspection, emergency rapid mapping, etc.

*In the scenario of power line inspection, if single-line flight is chosen, it is recommended to use the non-repetitive scanning method.