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A Customisable Data Acquisition System for Open-Source Hyperspectral Imaging.

Yiwei Mao1,2, Christopher H Betters1,2, Samuel Garske2

  • 1School of Physics, The University of Sydney, Sydney, NSW 2006, Australia.

Sensors (Basel, Switzerland)
|October 28, 2023
PubMed
Summary
This summary is machine-generated.

Researchers developed an open-source data acquisition system for hyperspectral imagers, enabling concurrent collection of hyperspectral and navigation data for direct georeferencing on drones.

Keywords:
data acquisitionhyperspectral imagingopen-sourceremote sensing

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Area of Science:

  • Remote Sensing
  • Environmental Monitoring
  • Geospatial Technology

Background:

  • Hyperspectral imagers are crucial for environmental studies across various disciplines.
  • A gap exists in the market for self-contained, off-the-shelf data acquisition systems for compact hyperspectral imagers.
  • Deploying hyperspectral sensors on platforms like drones requires integrated navigation capabilities.

Purpose of the Study:

  • To develop and demonstrate a low-cost, lightweight, and deployable open-source data acquisition system for hyperspectral imagers.
  • To enable concurrent collection of hyperspectral, navigation, and orientation data for direct georeferencing.
  • To provide a cost-effective and accessible solution for remote sensing applications.

Main Methods:

  • Utilized commercial-off-the-shelf hardware and open-source software.
  • Designed a compact data acquisition device with a microcontroller, custom PCB, and Raspberry Pi/NVIDIA Jetson.
  • Integrated ancillary navigation sensors for timestamped data collection.
  • Demonstrated the system on a Matrice M600 drone, collecting parallel data streams.

Main Results:

  • Successfully deployed an entirely open-source system for concurrent hyperspectral and navigation data collection.
  • Achieved direct georeferencing of hyperspectral data using collected navigation and orientation information.
  • The complete system, including the imager and housing, weighed only 735 g.
  • The system proved easy to assemble, modify, and deploy.

Conclusions:

  • The developed system offers a cost-effective and customizable solution for hyperspectral data acquisition.
  • This open-source approach democratizes access to advanced remote sensing capabilities.
  • The system facilitates direct georeferencing, enhancing the utility of hyperspectral data in environmental studies.