ME23A:
Hyperspectral Sensing of Coastal Aquatic Environments I

Session ID#: 93068

Session Description:
In response to mounting ecological pressures related to climate change and population growth, marine scientists and resource managers have increasingly turned to remote sensing as a means of providing timely and spatially coherent environmental information. Earth imaging sensor technology aboard aircraft and satellites has advanced rapidly from multispectral systems offering a small number of broad, discontiguous bands in the visible and infrared portions of the spectrum to imaging spectrometers with continuous, high-resolution coverage throughout the complete visible and near-infrared spectrum. The subject of hyperspectral remote sensing has rapidly gained momentum with the recent deployment of DESIS on the International Space Station, the launch of PRISMA, and planning for the NASA PACE and SBG sensors in response to the most recent decadal survey. NASA recently completed an airborne mission that mapped coral reefs in the tropical Pacific using PRISM, and applications have expanded to include small, lightweight systems deployable on commonly available drones, effectively placing advanced remote sensing capabilities in the hands of the individual researcher. Most recent investigations include merging the unique aspects of hyperspectral observations with other data to enhance knowledge of marine ecosystem health and biodiversity. The purpose of this session is to present and discuss the state of the art and novel application of hyperspectral remote sensing, from near-surface to space, for coastal aquatic environments. Papers are encouraged that cover all aspects of the topic including sensor development, new algorithmic approaches, emerging modes of deployment, and case studies spanning basic research to societally relevant applications.
Co-Sponsor(s):
  • IS - Ocean Observatories, Instrumentation and Sensing Technologies
Index Terms:

4220 Coral reef systems [OCEANOGRAPHY: BIOLOGICAL]
4815 Ecosystems, structure, dynamics, and modeling [OCEANOGRAPHY: BIOLOGICAL]
4858 Population dynamics and ecology [OCEANOGRAPHY: BIOLOGICAL]
4894 Instruments, sensors, and techniques [OCEANOGRAPHY: BIOLOGICAL]
Primary Chair:  Steven G Ackleson, Naval Research Laboratory, Washington, D.C., DC, United States
Co-chairs:  Heidi M Dierssen, University of Connecticut Avery Point, Groton, CT, United States, Raphael Martin Kudela, University of California Santa Cruz, Santa Cruz, United States and Michelle M Gierach, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
Primary Liaison:  Steven G Ackleson, Naval Research Laboratory, Washington, D.C., DC, United States
Moderators:  Steven G Ackleson, Naval Research Laboratory, Washington, D.C., DC, United States and Heidi M Dierssen, University of Connecticut Avery Point, Groton, CT, United States
Student Paper Review Liaison:  Raphael Martin Kudela, University of California Santa Cruz, Santa Cruz, United States

Abstracts Submitted to this Session:

A Journey Through Hyperspectral Remote Sensing of Earth’s Living Oceans (655704)
Paula S Bontempi, NASA Headquarters, Washington, United States and Michael Behrenfeld, Oregon State University, Corvallis, OR, United States
Hyperspectral Remote Sensing of Coral Reef Condition: COral Reef Airborne Laboratory (651327)
Eric J Hochberg, Bermuda Institute of Ocean Sciences, St.George's, GE, Bermuda and Michelle M Gierach, NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States
Hyperspectral retrievals of phytoplankton abundance and absorption properties in optically complex waters (644013)
Nima Pahlevan1,2 and Brandon Smith1,3, (1)NASA Goddard Space Flight Center, Greenbelt, United States, (2)Science Systems and Applications, Inc., Lanham, MD, United States, (3)Science Systems and Applications, Inc., Lanham, United States
Three-Dimensional Detection of Cyanobacteria Harmful Algal Blooms from a Hyperspectral Aircraft Sensor and Autonomous Underwater Vehicles (658204)
Andrea Joy Vander Woude, Great Lakes Environmental Research Laboratory, Ann Arbor, United States, Steven A Ruberg, NOAA, Great Lakes Environmental Research Laboratory, Ann Arbor, MI, United States, Reagan Errera, National Oceanic and Atmospheric Administration, Great Lakes Environmental Research Laboratory, Ann Arbor, United States and Greg Doucette, NOAA Charleston, Charleston, SC, United States
An open-source Hydrolight-based framework for fast inverse modelling of hyperspectral data (651689)
Tadzio Holtrop and Hans J van der Woerd, Institute for Environmental Studies, Department of Water and Climate Risk, Amsterdam, Netherlands
Estimating Phytoplankton Food Quality Using a Hyperspectral Phytoplankton Functional Type Model for San Francisco Bay, California (651839)
Raphael Martin Kudela, University of California Santa Cruz, Santa Cruz, United States, Sherry L. Palacios, NASA Ames Research Center, Moffett Field, CA, United States, Melissa Peacock, Northwest Indian College, Salish Sea Research Center, Bellingham, WA, United States and Niky Taylor, University of California Santa Cruz, Santa Cruz, CA, United States
Hyperspectral Above-Water Radiometry for Characterization of Phytoplankton Community Composition in Complex Coastal Waters (641860)
Steven E Lohrenz1, Heidi M Sosik2, Sumit Chakraborty3 and E Taylor Crockford2, (1)University of Massachusetts Dartmouth, New Bedford, MA, United States, (2)Woods Hole Oceanographic Institution, Woods Hole, MA, United States, (3)Mote Marine Laboratory, Sarasota, FL, United States