Steps to Conducting a LiDAR Drone Survey

In a LiDAR drone survey, a drone equipped with a LiDAR system is employed to gather precise data from a specific area. This powerful combination of LiDAR technology and drones allows surveyors to obtain detailed and reliable information for various purposes, such as creating topographic maps or conducting thorough infrastructure inspections.

The process of conducting a LiDAR drone survey can be broken down into four key steps. Each step is crucial for ensuring the accuracy, efficiency, and reliability of the survey data. These steps cover planning, precise calibration and installation of equipment, thorough data acquisition, and comprehensive analysis. By following these steps, surveyors can adopt LiDAR technology to obtain highly accurate and detailed data, which can be instrumental in various applications such as urban planning, environmental monitoring, infrastructure management, and disaster response.

The first step is mission planning, which includes defining the survey area using Geographic Information Systems (GIS) software. This helps delineate the boundaries and identify key features that need to be captured. Flight parameters must be calculated, including the optimal flight altitude based on the LiDAR sensor range and desired data resolution, and the overlap percentage between flight paths to ensure complete coverage and data consistency. Additionally, it's essential to review local airspace regulations, obtain necessary permissions or waivers, and monitor weather forecasts to identify potential hazards like tall structures or wildlife habitats.

Next, LiDAR payload installation and calibration involves choosing a suitable mounting mechanism to ensure the LiDAR sensor's stability during flight and conducting weight and balance checks to maintain the drone's flight characteristics. The calibration process requires aligning the LiDAR sensor settings with the drone's flight control system and performing tests to verify sensor accuracy and functionality. Functional checks include validating the sensor output through test scans and confirming data acquisition settings, such as scan rate and resolution.

During the data acquisition and processing phase, the drone operates in autonomous flight mode based on the predefined flight plan. Real-time data acquisition is monitored to ensure proper sensor operation and data capture. High-capacity, secure storage devices are used to store the raw LiDAR point cloud data, and robust backup procedures are implemented to prevent data loss. Noise filtering techniques are applied to remove noise, outliers, and artifacts from the raw data, optimizing the filtering parameters to enhance data quality while preserving valuable information. Data registration involves merging multiple LiDAR scans into a single, cohesive dataset and integrating GNSS and IMU data to accurately georeference the LiDAR point cloud.

The final step is analyzing the LiDAR drone survey data to extract valuable insights. Point cloud analysis includes feature extraction using automated classification algorithms to identify and categorize objects such as buildings, vegetation, and roads. Feature-specific point clouds are generated for detailed analysis and modeling. Distance measurements are calculated using point-to-point measurement tools and validated against ground truth or existing datasets. Elevation analysis involves generating Digital Elevation Models (DEMs) and contour maps from the LiDAR point cloud data, analyzing elevation variations to identify slopes, ridges, valleys, and other terrain features.

Data interpretation and visualization involve detecting anomalies through statistical analysis and change detection to identify issues such as elevation changes, vegetation density variations, or structural deformations. Potential risks or areas of interest are flagged for further investigation. Data fusion integrates LiDAR data with orthophotos, aerial imagery, or other geospatial datasets for comprehensive visualization and analysis, creating multi-layered geospatial maps that combine LiDAR-derived features with other relevant data sources.

Choosing the best LiDAR payload and drone combo for drone survey operations depends on your specific requirements and the project's demands. The DJI M350 RTK + DJI Zenmuse L2 offers a comprehensive and affordable solution with its high-precision aerial LiDAR system, integrated RGB mapping camera, and advanced IMU system. With its high vertical and horizontal accuracy of 4 cm and 5 cm, respectively, it covers a substantial 2.5 km² area in a single flight. The Zenmuse L2's penetration capabilities, smaller laser spots, and support for up to 5 returns make it suitable for various applications, including land surveying and forestry. For more information on how to choose the right LiDAR system please refer to our blog post:  Choosing the Right Drone Based LiDAR System

On the other hand, the YellowScan Voyager offers flexibility with its multi-platform support and high accuracy of 1 cm. It excels in vegetation penetration, making it ideal for forestry and environmental applications. With its ability to detect up to 15 target echoes per laser pulse and a scanning rate of 1.5 million points per second, it offers impressive data collection capabilities. The choice between these two depends on your specific needs: the Zenmuse L2 may be more suitable for general surveying with its broader range of features and compatibility with the DJI M350 RTK, while the YellowScan Voyager might be preferable for specialized applications requiring high accuracy and vegetation penetration. Both options are reliable choices, but selecting the right one will ultimately depend on the project's scope, budget, and specific requirements. In summary, here is what you will need for a LiDAR Drone Survey:

Choose a drone model with extended flight endurance (>30 minutes), stability features (e.g., gimbal stabilization), and sufficient payload capacity to carry the LiDAR sensor. 

Select a sensor with appropriate range (>100 meters), high accuracy (sub-centimeter), and point density (>1000 points/m²) based on survey requirements.

Use a high-precision GNSS receiver with RTK (Real-Time Kinematic) capabilities for accurate geolocation, such as the Emlid Reach RS3 or Stonex S900+

Employ an IMU with high update rates (>100 Hz) for precise orientation and motion tracking.

Specialized software is required to process and analyze LiDAR data effectively. There are various software packages available that provide tools for filtering, classifying, and visualizing point cloud data.

Some popular LiDAR processing software include YellowScan CloudStation, Greenvalley LiDAR 360, Correlator3D and DJI Terra. These software packages offer a wide range of features and functionalities, enabling surveyors to extract valuable information from LiDAR point clouds efficiently and accurately.