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LiDAR Remote Sensing Multirotor Unmanned Aircraft System

hyperspectral,drone,Airborne Hyperspectral,spectral camera,spectral,hyperspectral scanner,multispectral imaging,swir hyperspectral camera,hyperspectral imager,remote sensing
LiDAR Remote Sensing Multirotor Unmanned Aircraft System
ATHL9010
FOB
1 unit
Made in China
ATHL9010 series is the 3rd generation hyperspectral imager integrated LiDAR system. This new series feature compact and light.
Quantity
Description:
    ATHL9010 hyperspectral scanner series is the 3rd generation hyperspectral imager integrated LiDAR system. This new series feature compact and light.
    It consists of eight main parts of six-rotor UAV, high-stable cloud platform, hyperspectral imager, LiDAR, big memory storage, GPS navigation system, ground receiver station, and ground control system.
    It depends on linear LiDAR to get surface elevation, images ortho-rectification, and 3D object attitude, whose LiDAR data and spectral data are being combined to analysis open up new research way.
    ATHL9010 hyperspectral scanner integrated high-precision hyperspectral imager and high-resolution LiDAR, which generates field true color point cloud, one fly can get as fast as >2 km2 point cloud data.
    From real-time measure spetral data collection to spectral images analysis, and final physicochemical properties calculation. They've widely applied to plants classification and growth assessment.

Features:
  • Range:400~1000nm
  • Spectral Resolution:1.5 nm
  • FOV:23.5°@f=35mm (Lens changeable)
  • IFOV0.9 mrad@f=35mm (Lens changeable)
  • Flight height: 50~1000 m, recommend height 100m
  • Solid state LiDAR with high reliability
  • LiDAR measure range: 1~200m
  • LiDAR measure height error: 20 mm
  • PC Intel Core i7 with max. 2T memory reach up to 100 hours images data
  • 1.5m multi-wing drone with heavy-load or extendable
  • Long flight time about 45 minutes, large cruise area

Application:
  • Monitor Agriculture: plant diseases and insect pest, disaster, categories ID etc.
  • Forestry: Tree categories identification, Phytomass, nutrient elements, forest health etc.
  • Water Environment: Water quality parameters, water waste spatial distribution and migration analysis
  • Soil Pollution: heavy metal waste
  • Minerals: Mineral mapping, ingredients explore, metallogenic prognosis etc.
  • City geological: substances classification and identification