Carbomap Perform Laser Scan on Long Duration UAV Flight with RIEGL
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Carbomap Perform Laser Scan on Long Duration UAV Flight with RIEGL

Carbomap in collaboration with high RIEGL, UAVE and The University of Edinburgh has announced the first successful demonstration flight of a RIEGL VUX-1LR survey-grade waveform laser scanner on a fixed wing, long range UAV.

This is likely the first time that such a high-performance scanner has ever flown on a fixed wing UAV with such an advanced specification for long duration (8 hrs) and long range (1,000 km). With centimetre-scale 3-dimensional accuracy, this development will greatly increase the worldwide accessibility to high quality laser scanning (known as LiDAR).

Obtaining high quality 3D data can be very expensive using conventional airborne surveys. It is difficult to process without specialised software, and as a consequence, it is rarely available in most developing nations. By bringing such instruments together into a single UAV system (Forest-Lux (F-Lux)), together with its own solution-focused software, it is now possible to get a system that can be a local asset, under local stakeholder control, and be operated at an affordable price in any country in the world.

Technical Details for the F-Lux:

  • F-Lux processes data in near-real time to produce high quality metrics.
  • Has a 1,000 km range and can cover up to 800 km2 in a single day.
  • Uses the RIEGL VUX-1LR LiDAR sensor
  • Can operate up to 650m in altitude and collects full waveform LiDAR data
  • Uses instant-Omega software so users have the data already in the Cloud when they return to base

 

The goal for F-Lux is for it to be a local or national asset; this means the cost of mobilising the system is had to be low, which significantly reducing the overall cost of collecting data. F-Lux can be applied to a range of other applications, such as mapping power lines, roads, and other infrastructure, as well as agriculture. The ability to rapidly deploy the drone means it can also be used in post-disaster situations, collecting and processing high quality and vital data on demand.

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