Optica Sensing Congress

31 July 2023 – 03 August 2023

Hilton Munich Park
Munich, Germany


Submission Deadline: 28 Mar 2023 12:00
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Hyperspectral/Multispectral Imaging and Sounding of the Environment (HISE)

Seeking presentations of innovations in hyperspectral and multispectral instrumentation, data analysis, algorithm development and technology demonstrations for imaging and sounding of the environment.

Recent years have witnessed a proliferation of hyperspectral and multispectral measurement and detection systems with enhanced imaging and sensing capabilities and innovative measurement platforms, such as unmanned aerial systems, autonomous surface and underwater vehicles, CubeSats, polar orbiting satellite constellations and industrial robots.

The wealth of data from these systems is complemented by a parallel proliferation of open-source software tools and innovative algorithms based on artificial intelligence, machine learning and physical models to process content-rich data and retrieve biophysical parameters of interest. These systems and algorithms provide unprecedented opportunities to understand, monitor and quantitatively characterize physical and biogeochemical processes and phenomena in the Earth’s environment.

This meeting specifically targets studies involving hyperspectral or multispectral sensors with a fine resolution in the spectral, spatial or temporal domains, which provide enhanced feature identification and discrimination capabilities for atmospheric, oceanographic and terrestrial applications as well as industrial applications such as process control, quality assurance and material identification.

With a focus on systems with a high spectral, spatial or temporal resolution, we solicit abstracts dealing with basic research, technology development, data analysis, algorithm development and technology demonstration in atmospheric, oceanographic, terrestrial and industrial applications.

Applications may include routine monitoring as well as rapid response to natural and anthropogenic phenomena such as crashed aircraft, volcanoes, earthquakes, floods, pandemics, oil spills, treaty violations, biomass burning, tropical storms, trace gas emissions and heavy aerosol events.

Studies involving innovative use of physics-based models and statistical approaches such as artificial intelligence and machine learning techniques to exploit content-rich data and extract biophysical information are of particular interest.

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Ka Lok Chan

German Aerospace Center (DLR), Germany

Wesley Moses

Naval Research Laboratory, United States

Shen-En Qian

Canadian Space Agency,

Committee Members

  • Ka Lok Chan, German Aerospace Center (DLR), GermanyChair
  • Wesley Moses, Naval Research Laboratory, United StatesChair
  • Shen-En Qian, Canadian Space AgencyChair
  • Elhadi Adam, University of Witwatersrand
  • Helen Brindley, Imperial College London, United Kingdom
  • Miran Bürmen, University of Ljubljana, Slovenia
  • Daniele Cerra, German Aerospace Center, Germany
  • Leah Crespi, Headwall Photonics, United States
  • Alexandre Fong, Hinalea Imaging, United States
  • Genevieve Gariepy, Canadian Space Agency, Canada
  • Emmett Ientilucci, Rochester Institute of Technology, United States
  • Sanna Kaasalainen, FinnishGeospatial Research Institute, Finland
  • Stefan Livens, VITO, Belgium
  • Nicole Pinnel, German Aerospace Center, Germany
  • Denis Pöhler, Heidelberg University
  • Saurabh Prasad, University of Houston, United States
  • Mariana Soppa, Alfred Wegener Institute, Germany
  • Caroline Turcotte, Defence Research and Development Canada
  • Kevin Turpie, NASA Goddard Space Flight Center