loading page

Exploring mission design for imaging spectroscopy retrievals for land and aquatic ecosystems
  • +12
  • Ann Raiho,
  • Kerry Cawse-Nicholson,
  • Adam Chlus,
  • Jeff Dozier,
  • Michelle M. Gierach,
  • Kimberley Miner,
  • Shawn Paul Serbin,
  • David Schimel,
  • Fabian Schneider,
  • Alexey N Shiklomanov,
  • S. McKenzie Skiles,
  • David Ray Thompson,
  • Philip Townsend,
  • Shannon-Kian Zareh,
  • Benjamin Poulter
Ann Raiho
NASA Goddard Space Flight Center

Corresponding Author:[email protected]

Author Profile
Kerry Cawse-Nicholson
Jet Propulsion Laboratory, California Institute of Technology
Author Profile
Adam Chlus
Jet Propulsion Laboratory
Author Profile
Jeff Dozier
University of California, Santa Barbara
Author Profile
Michelle M. Gierach
Jet Propulsion Laboratory, California Institute of Technology
Author Profile
Kimberley Miner
Jet Propulsion Laboratory
Author Profile
Shawn Paul Serbin
Brookhaven National Laboratory (DOE)
Author Profile
David Schimel
Jet Propulsion Laboratory
Author Profile
Fabian Schneider
California Institue of Technology
Author Profile
Alexey N Shiklomanov
NASA Goddard Space Flight Center
Author Profile
S. McKenzie Skiles
University of Utah
Author Profile
David Ray Thompson
Jet Propulsion Laboratory, California Institute of Technology
Author Profile
Philip Townsend
Jet Propulsion Laboratory
Author Profile
Shannon-Kian Zareh
Jet Propulsion Laboratory, California Institute of Technology
Author Profile
Benjamin Poulter
NASA
Author Profile

Abstract

The retrival algorithms used for optical remote sensing satellite data to estimate Earth’s geophysical properties have specific requirements for spatial resolution, temporal revisit, spectral range and resolution, and instrument signal to noise ratio (SNR) performance to meet science objectives. Studies to estimate surface properties from hyperspectral data use a range of algorithms sensitive to various sources of spectroscopic uncertainty, which are in turn influenced by mission architecture choices. Retrieval algorithms vary across scientific fields and may be more or less sensitive to mission architecture choices that affect spectral, spatial, or temporal resolutions and spectrometer SNR. We used representative remote sensing algorithms across terrestrial and aquatic study domains to inform aspects of mission design that are most important for impacting accuracy in each scientific area. We simulated the propagation of uncertainties in the retrieval process including the effects of different instrument configuration choices. We found that retrieval accuracy and information content degrade consistently at >10 nm spectral resolution, >30 m spatial resolution, and >8 day revisit. In these studies, the noise reduction associated with lower spatial resolution improved accuracy vis à vis high spatial resolution measurements. The interplay between spatial resolution, temporal revisit and SNR can be quantitatively assessed for imaging spectroscopy missions and used to identify key components of algorithm performance and mission observing criteria.