Exploring Mission Design for Imaging Spectroscopy Retrievals for Land and Aquatic Ecosystems

Author:

Raiho A. M.12ORCID,Cawse‐Nicholson K.3ORCID,Chlus A.3,Dozier J.4ORCID,Gierach M.3ORCID,Miner K.3,Schneider F.3ORCID,Schimel D.3,Serbin S.5ORCID,Shiklomanov A. N.1ORCID,Thompson D. R.3ORCID,Townsend P. A.36ORCID,Zareh S.3,Skiles M.7ORCID,Poulter B.1ORCID

Affiliation:

1. NASA Goddard Space Flight Center Biospheric Sciences Lab Greenbelt MD USA

2. Earth System Science Interdisciplinary Center University of Maryland College Park MD USA

3. Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

4. Bren School of Environmental Science & Management University of California Santa Barbara CA USA

5. Brookhaven National Laboratory Upton NY USA

6. University of Wisconsin—Department of Forest and Wildlife Ecology Madison WI USA

7. Department of Geography University of Utah Salt Lake City UT USA

Abstract

AbstractThe retrieval 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 biogeoscience 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.

Publisher

American Geophysical Union (AGU)

Subject

Paleontology,Atmospheric Science,Soil Science,Water Science and Technology,Ecology,Aquatic Science,Forestry

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