Painpoints
It’s difficult to accurately locate the crop areas that need attention without geotagged data.
Manual samplings are lengthy and labor consuming, thus reducing the possible sampling frequency.
Traditional crop evaluation methods rely on observation with limited data analysis.
Limited visibility of the crop field overall health.
Advantages
Evaluate health and prevent diseases of each individual crop with georeferenced data collection.
Increase data sampling frequency with fast aerial data collection.
Access a variety of data including RGB images, multispectral, thermal, and LiDAR data.
Cover larger areas in a single flight.
Drone Platform
Matrice 350 RTK
Weight: Approx. 6.47 kg (with single downward gimbal and two TB65 batteries)
Max Flight Time: 55 minutes
Sensing System: Six-directional sensing and positioning
Environment Adaptability: IP55; max service ceiling above sea level 7,000 m (with 1676 propellers, without other payload); max wind resistance 12 m/s
Payload and Software
Zenmuse L2
Integrates frame LiDAR, a self-developed high-accuracy IMU system, and a 4/3 CMOS RGB mapping camera.
Coverage: 2.5 km² per flight
Detection Range: 250 m @ 10 % reflectivity, 100 klx
Effective Point Cloud Rate: 240 000 pts/s
Returns: Supports 5 Returns
Solution: Turnkey Solution
DJI Terra
Modeling and flight mission plan
DJI Pilot 2
Ground control.
Workflow
1 Data Collection:
– Using the DJI Pilot 2 app and the 3D Mapping Flight Mission feature, capture the data to generate a 3D model of the forest.
2 Data Processing:
– Import the data into DJI Terra, then reconstruct a high-resolution 3D model.
3 Data Analysis:
– Perform point cloud classification to analyze forest status and make accurate decisions. Import the resulting point cloud into third-party software for further forest management and analysis.
Contact Us
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