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We will attend the The EARSeL SIG-IS´s 20th birthday

You are therefore cordially invited to participate and visit the ASD Panalytical booth along with Bonsai Advanced Technologies in the 10th EARSeL SIG Imaging Spectroscopy Workshop
19 – 21 April 2017 and organized by The European Association of Remote Sensing Laboratories and University of Zurich, Switzerland

EARSeL’s Special Interest Group on Imaging Spectroscopy aims at encouraging interdisciplinary discussions among specialists working with innovative Earth Observation methods and technologies.

Visit our booth and learn more about our Remote Sensing Instruments.

We are leader in the spectroscopy industry for more than 25 years. You will have the opportunity to get further information about our instruments and applications.
We will be delighted to receive all the researchers interested in high performance analytical instrumentation solutions for a variety of applications such as:
  • Geology/Mining
  • Image Classification/Analysis
  • Optics and Photonics
  • Materials Analysis
  • Agriculture and Environmental

EARSeL is a scientific network of European remote sensing laboratories, coming from both academia and the commercial/industrial sector, which covers all fields of geoinformation and earth observation through remote sensing. All scientists, professionals and researchers involved or interested in the field of the symposium are strongly encouraged to present papers according to the following topics:

Advanced methods for spectroscopy calibration, data processing, and archiving

  • Sensor calibration and product validation
  • Software systems for imaging spectroscopy
  • Big data and data mining
  • Inversion schemes and data assimilation
  • In-situ, field and laboratory spectroscopy
  • Atmospheric compensation techniques
  • Spectral databases and information systems
  • Very high resolution spectroscopy
  • Statistical and computational methods for data analysis

Integrated approaches in Earth System Science using spectroscopy

  • Combined use of Earth Observation technologies (LiDAR, SAR, etc. and spectroscopy)
  • Forward and inverse modeling of spheres
  • Sphere specific analysis methods (atmosphere, biosphere, hydrosphere, lithosphere, geosphere, anthroposphere)
  • Ecosystem processes and functions in vegetated ecosystems, soils, snow & ice, atmosphere, coastal and inland waters, urban areas
  • Scaling, interactions and feedback mechanisms between and across spheres
  • Transdisciplinary applications using Soil- and Ecosystem Services (ESS)
  • Spectroscopy in the context of societal challenges (water scarcity, food security, biodiversity loss, etc.)

Next generation platforms and sensors

  • Spectroscopy from ground, drone, air- and spaceborne platforms
  • Visible, near-, mid- and thermal infrared spectral and multi-angular spectral measurements
  • Emerging concepts, technologies and missions

Topical Keynote Sessions

Blending physical modelling and machine learning: new frontiers in spectroscopy data processing


  • Jochem Verrelst (Universitat de Valencia)
  • Gustau Camps-Valls (Universitat de Valencia)
  • Jose Gomez Dans (University College London)

Physically-based radiative transfer models (RTMs) help understand the interactions of radiation with vegetation and atmosphere. However, advanced RTMs can be computationally burdensome and too rigid for daily use. Alternatively, recent machine learning models can cope with large datasets with high accuracy but deploy too flexible models that may not respect the underlying physics. This special session will discuss the emerging field of synergistic use of physical models with machine learning techniques for efficient spectroscopy data processing. Advances in emulation approaches will be presented, as well new machine learning methods that encode RTM differential equations and learn the latent forces from empirical data, as well practical applications in the fields of sensitivity analysis, efficient inversion (or retrieval) and synthetic scene generation approaches. The session will close with a discussion on how advanced physical models and machine learning can live together and contribute to the analysis and processing of forthcoming imaging spectroscopy data streams.

Keywords: emulation, radiative transfer models, metamodels, machine learning

Imaging spectroscopy from unmanned aerial systems (UAS): Recent advances in technology and applications


  • Pablo J. Zarco-Tejada (European Commission, Joint Research Centre, Ispra, Italy)
  • Helge Aasen (ETH Zurich, Switzerland)
  • Lammert Kooistra (Wageningen University, The Netherlands)
  • Arko Lucieer (University of Tasmania, Australia)

The acquisition of spatially high resolution imaging spectroscopy data from unmanned aerial systems (UAS) has become a reality and enables addressing several challenging scientific questions related to environmental change, food security, or the assessment of hazardous events. Nevertheless, critical technical advances are still required before such data can be operationally acquired. Particularly limitations and restrictions imposed by unmanned aircraft vehicles (UAV) require future attention, e.g. optimizing the size and weight of sensors, or the miniaturization of auxiliary devices needed during flight. This session will discuss current technology available to facilitate imaging spectroscopy from UAS and will outline emerging applications in which the use of UAS based imaging spectroscopy is important. Current technological limitations that complicate the application of miniature-based imaging spectrometers will be discussed, e.g. issues related to the radiometric and spectral calibration of sensors, or the atmospheric correction of acquired images. Further, critical next steps to eventually facilitate a successful application of imaging spectroscopy for quantitative remote sensing will be defined.