Hyperspectral/Multispectral Imaging and Sounding of the Environment (HISE)
Events
Hyperspectral/Multispectral Imaging and Sounding of the Environment (HISE)
HISE seeks 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 vehicles, 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 physical and biogeochemical processes 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, including rapid response to natural and anthropogenic disasters.
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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Hyperspectral/Multispectral Imaging and Sounding of the Environment (HISE)
Topics
Hyperspectral/Multispectral Imaging and Sounding of the Environment (HISE)
Topics of Interest
- Atmospheric Sensing and Sounding
- Atmospheric measurements and their applications
- Modeling and compensation for atmospheric effects
- Air pollution and air quality monitoring
- Weather prediction and climate modeling
- Aquatic Remote Sensing
- Water quality monitoring in inland and coastal waters
- Phytoplankton functional group and species discrimination
- Harmful algal bloom monitoring
- Determination of concentrations of physical and biological constituents in water
- Bottom type and bottom depth determination in shallow water environments
- Terrestrial Remote Sensing
- Precision agriculture
- Species discrimination and mapping of vegetation in forests and wetlands
- Soil studies, including soil classification, soil moisture content and trafficability
- High-resolution imaging for urban planning and development
- Radiative Transfer Modeling
- New approaches for computationally efficient and fast radiative transfer modeling
- Vector radiative transfer modeling using hyperspectral and polarimetric data
- Fast radiative transfer through dimensionality reduction and machine learning approaches
- Image Processing, Algorithm Development and Machine Learning
- Innovative signal and digital image processing techniques including image segmentation, pattern recognition and neural networks
- High-resolution data analysis using artificial intelligence and machine learning techniques
- Dimensionality reduction and information content analysis
- Fusion with active or passive sensors and visualization algorithms
- Spectral inversion techniques such as unmixing, deconvolution, derivatives, optimal estimation and spectral fingerprinting
- Industrial Applications
- Imaging and sensing applications in the mining, oil and gas industries
- High-resolution imaging for industrial quality analysis, process control and material identification
- Imaging and sensing technologies for food adulteration monitoring
- Incident Response and Monitoring Applications
- Environmental changes due to pandemics, hurricanes and other natural disasters
- Thermal sensing of wildfires and volcanoes
- Deployment of imaging technologies for rapid response to natural disasters/events
- Sensor Development
- New hyperspectral/multispectral imager design, development and sensor characterization
- Planned and recently launched operational imaging and/or sounding systems
- Observing system simulation experiments
- Active hyperspectral imaging and LiDAR
Sanna Kaasalainen
Finnish Geospatial Research Institute, Finland,
Co-Chair
Wesley Moses
Naval Research Laboratory, United States,
Co-Chair
Shen-En Qian
Canadian Space Agency, Canada,
Co-Chair
Committee
- Sanna Kaasalainen, Finnish Geospatial Research Institute, Finland, Co-Chair
- Wesley Moses, Naval Research Laboratory, United States, Co-Chair
- Shen-En Qian, Canadian Space Agency, Canada, Co-Chair
- Elhadi Adam, University of Witwatersrand, South Africa
- Keith Beckett, EarthDaily Analytics, Canada
- Miran Bürmen, Univerza v Ljubljani, Slovenia
- Ka Lok Chan, University of Stirling, United Kingdom
- Regina Eckert, Jet Propulsion Laboratory, United States
- Genevieve Gariepy, Canadian Space Agency, Canada
- Emmett Lentilucci, Rochester Institute of Technology, United States
- Stefan Livens, VITO, Belgium
- Morgaine McKibben, NASA Goddard Space Flight Center, United States
- Nicole Pinnel, Deutsches Zent f.Luft-u.Raumfahrt eV (W), Germany
- Dario Polli, Politecnico di Milano, Italy
- Caroline Turcotte, Defence Research and Development Canada, Canada
- Andrea Vander Woude, NOAA Great Lakes Environmental Res Lab, United States
