UAV hyperspectral imaging system

NegotiableUpdate on 01/09

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Nature of the Manufacturer: Producers

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Overview

The unmanned aerial vehicle hyperspectral imaging system has the characteristics of multiple bands, narrow bands, large information content, high accuracy, and integrated spectra, which make this technology applicable to various fields, including precision agriculture, environmental monitoring, disaster assessment, geological exploration, etc.

Product Details

UAV hyperspectral imaging systemIt is a new type of information data technology that combines the flexibility of drones with the high-precision analysis capability of hyperspectral imaging technology. This system uses a hyperspectral camera mounted on a drone to continuously image the target area in the spectral range of ultraviolet to near-infrared (200-2500nm), thereby obtaining spectral information of the object.

Hyperspectral imaging technology has the characteristics of multiple bands, narrow bands, large information content, high accuracy, and integrated spectra, making it applicable in various fields, including precision agriculture, environmental monitoring, disaster assessment, geological exploration, etc.

In the field of precision agriculture,UAV hyperspectral imaging systemIt can help farmers monitor crop health by analyzing the spectral reflectance of crops to quickly detect issues such as nutrient deficiency, pests, and diseases, thereby achieving precise fertilization and disease prevention.

In terms of environmental monitoring, drones can assess water quality, monitor changes in vegetation cover, and even track the migration of wildlife without disturbing the natural environment. For example, the unmanned airborne hyperspectral imaging system technology developed by Chinese President of Science Chun Guangji can complete real-time high-precision water quality monitoring of 50 meters wide and 5 kilometers long rivers in 20 minutes.

In addition,UAV hyperspectral imaging systemIt also has the advantages of large coverage area, long flight time, and wide flight range. Through high-performance CMOS image sensors, the spot diameter is less than 0.5 pixels, and the spectral range can be changed from 400 to 2500 nanometers. The objective lens can be replaced according to detection needs. These characteristics make the imaging system have a very broad application prospect in the future.

UAV hyperspectral imaging systemIt is a new type of information data technology that uses drones equipped with hyperspectral cameras to capture spectral bands and image target areas. This technology has many significant features:

1. Expanded measurement space and range: Drone flight measurement can cover a wider area, greatly exceeding the scope of traditional measurement methods.

2. High flight altitude and long flight time: Drones can fly at an altitude of up to 7000m and have a flight time of up to 45 minutes, which means they can conduct longer remote sensing measurements in larger areas.

3. Fast and accurate data acquisition: Drones fly at high speeds, and by measuring remote sensing images of the ground, they can quickly, accurately, and extensively obtain hyperspectral information of target objects.

4. High precision positioning: The drone is equipped with a global positioning system consisting of GPS, GLONASS, BeiDou, and Galileo. The flight positioning can be accurate to 0.1m, ensuring the stability and clarity of the captured images.

5. Wide spectral range and high resolution: The imaging system can support changing the spectral range to 400 to 2500 nanometers, with high spectral resolution, better than 1.3nm, and can provide rich spectral information.

6. Large capacity data storage: The unmanned aerial vehicle has an onboard computer that supports up to 2T of storage and can store up to 100 hours of imaging data.

7. Wide application areas: Due to the characteristics of multi band, narrow band, large information content, high accuracy, and integrated spectra of hyperspectral imaging, this technology has a wide range of applications in water quality detection, soil salinization degree detection, soil nutrient composition detection, and other fields.