Adapt to DJI M400 Intelligent Machine Nest Unmanned Aerial Vehicle Hyperspectral System

Adapt to DJI M400 Intelligent Machine Nest Unmanned Aerial Vehicle Hyperspectral SystemIt has the function of synchronously collecting multidimensional data, and can obtain hyperspectral spectrum data and high-definition visible light photos of 300 bands in one flight. At the same time, it can calculate various commonly used indices such as NDVI and NDWI through supporting software, and has a built-in multi parameter water quality inversion algorithm, which can accurately invert various water quality parameter indicators such as total nitrogen, total phosphorus, ammonia nitrogen, permanganate index, chlorophyll, suspended solids, etc., generating clear and intuitive concentration distribution maps for precise traceability.

Adapt to DJI M400 Intelligent Machine Nest Unmanned Aerial Vehicle Hyperspectral SystemIt mainly consists of a hyperspectral mounting system, onboard high-definition cameras, unmanned aerial vehicles, and unmanned aerial vehicle automatic hangars, with automatic takeoff and landing and charging functions for unmanned aerial vehicles. In addition, the airport is also equipped with data servers and networks. After returning, the drone can automatically download data and calculate it, and finally upload it to the user's server. Real time data is transmitted directly to the aircraft remote control through the drone signal link and forwarded to the user data platform.

Unmanned operation

Through the lightweight design of a hyperspectral payload system, combined with industry drones and automated machine nests, the entire remote sensing monitoring system will achieve automated task planning and execution. Drones have the ability to fly autonomously, support intelligent path planning and dynamic obstacle avoidance, greatly improving flexibility and safety in practical operations.

Remote monitoring and management

The system can provide real-time data feedback at the ground station, enabling remote viewing of equipment's operational status, task progress, and real-time data streams. During the homework process, the work status can be monitored at any time or manually controlled to ensure the smooth progress of the task.

Built in intelligent algorithm

The system is equipped with various deep learning algorithms, and users can import different algorithm models according to their own application needs, self train and upgrade, continuously expand application scenarios, and improve monitoring accuracy.

Real time inversion capability

By obtaining real-time data through hyperspectral sensors, the system can complete preliminary data processing and inversion, and upload the inversion results to the cloud platform in real time, providing immediate support for decision-making.

Adapt to multiple scenarios

The system is equipped with various algorithms such as water quality monitoring and vegetation index, which can support different application scenarios such as agriculture, forestry, water quality, and urban areas, and meet the needs of low altitude comprehensive remote sensing monitoring.

Support third-party data calibration

The system supports the automatic calibration of airborne remote sensing analysis results using high-precision data from third-party laboratories or online monitoring stations, correcting system errors and improving data accuracy.