Prof. Heidi Dierssen
Department of Marine Sciences,
University of Connecticut,
Groton, CT, USA 06340

Established: June 2020


Benthic reflectance is a property describing the colour of the bottom boundary in aquatic ecosystems. It is an essential parameter for mapping habitats in optically shallow water using remote sensing techniques and has applications in ecology, ecosystem health and function, global change, marine geology and archeology. Benthic reflectance is quantified as the upwelled irradiance reflected from the bottom boundary normalized to the incident downwelling irradiance. Many techniques are available to measure this property and the aim of this working group is to produce a report that covers an overview of instrumentation and methods, examples of benthic reflectance across different scales and habitats, environmental influences on the measurements, applications and emerging technologies.

There are many different instruments and techniques for making benthic reflectance measurements but no recommendations for the best practices for each method or potential uncertainties inherent to the measurement. Various instruments are used e.g., closed path with internal lighting, open path using natural sunlight, laboratory methods in air etc.

Recent modeling work shows that the three-dimensionality influences the benthic reflectance from shadowing in a manner that is related to the rugosity of the benthic structure (Hedley et al. 2018). Assessing the structure of the coral and solar conditions during fieldwork may provide important information in assessing the variability in benthic reflectance across a habitat and the uncertainty in remote sensing methods to estimate benthic reflectance.

Membership of the working group is international. If you have experience with making benthic reflectance measurements and are interested in contributing your expertise to an IOCCG report on this topic, please contact Heidi Dierssen (


The intent of this working group is to:

  • document how these different methods work
  • characterize the uncertainties inherent to the measurements
  • provide recommendations as to best practices for each method in order to minimize the uncertainty.
  • provide recommendations for relevant metadata to be included for each dataset
  • possibly recommend practices in field validation for benthic remote sensing.


  • Ackleson, Steve, Naval Research Lab, USA
  • Barnes, Brian, USF, USA
  • Chirayath, Ved, U. Miami, USA
  • Dekker, Arnold, CSIRO, Australia
  • Fournier, George, Canada
  • Gege, Peter, DLR, Germany
  • Goodman, Jamie, HySpeed Computing LLC., USA
  • Hedley, John, Env. Computer Science Ltd., UK
  • Hestir, Erin, US Merced, USA
  • Hochberg, Eric, Bermuda Institute of Ocean Sciences, Bermuda
  • Johnsen, Geir, NTNU, Norway
  • Joyce, Karen, James Cook U., Australia
  • Kutser, Tiit, University of Tartu, Estonia
  • Laliberte, Julien, Dept of Fisheries & Oceans, Canada
  • Oppelt, Natascha, Kiel University, Germany
  • Palacios, Sherry, California State U., USA
  • Pascual, Gema Casal, Maynooth University, Ireland
  • Phinn, Stuart, U. of Queensland, Australia
  • Pitarch Portero, Jaime, CNR-ISMAR, Italy
  • Roelfsema, Chris, U. of Queensland, Australia
  • Russell, Brandon, Labsphere, Inc., USA
  • Scrivner, Charles, U. of Connecticut, USA
  • Wonkook Kim, Pusan National U., Korea
  • Zimmerman, Richard, Old Dominion U., USA

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