Airborne mapping of benthic reflectance spectra with Bayesian linear mixtures

David R. Thompson, Eric J. Hochberg, Gregory P. Asner, Robert O. Green, David E. Knapp, Bo Cai Gao, Rodrigo Garcia, Michelle Gierach, Zhongping Lee, Stephane Maritorena, Ronald Fick

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Remote imaging spectroscopy from 400 to 800 nm can use benthic reflectance signatures to map the composition and condition of shallow water ecosystems. We present a novel probabilistic approach to jointly estimate the seafloor reflectance and water properties while flexibly incorporating varied domain knowledge and in situ measurements. The inversion transforms remote radiance data with an atmospheric correction followed by a water column correction. Benthic reflectance and water optical properties are both represented by linear mixtures of endmember spectra. We combine remote measurements, prior knowledge and field data using a flexible Bayesian optimal estimation, solving for the Maximum A Posteriori (MAP) combination of water column properties, seafloor reflectance, and depth. We then demonstrate performance in controlled simulations and in overflights of a coral reef in Hawaii with coincident in situ measurements. The measurement approach helps lay a foundation for wide-area airborne mapping of the condition of threatened coastal ecosystems such as coral reefs.

Original languageEnglish (US)
Pages (from-to)18-30
Number of pages13
JournalRemote Sensing of Environment
Volume200
DOIs
StatePublished - Oct 2017
Externally publishedYes

Fingerprint

reflectance
Reefs
in situ measurement
coral reef
Water
seafloor
water
water column
Ecosystems
coral reefs
atmospheric correction
radiance
optical property
ecosystems
optical properties
shallow water
transform
Hawaii
spectroscopy
Optical properties

Keywords

  • Atmospheric correction
  • Coral reefs
  • Imaging spectroscopy
  • Remote sensing

ASJC Scopus subject areas

  • Soil Science
  • Geology
  • Computers in Earth Sciences

Cite this

Thompson, D. R., Hochberg, E. J., Asner, G. P., Green, R. O., Knapp, D. E., Gao, B. C., ... Fick, R. (2017). Airborne mapping of benthic reflectance spectra with Bayesian linear mixtures. Remote Sensing of Environment, 200, 18-30. https://doi.org/10.1016/j.rse.2017.07.030

Airborne mapping of benthic reflectance spectra with Bayesian linear mixtures. / Thompson, David R.; Hochberg, Eric J.; Asner, Gregory P.; Green, Robert O.; Knapp, David E.; Gao, Bo Cai; Garcia, Rodrigo; Gierach, Michelle; Lee, Zhongping; Maritorena, Stephane; Fick, Ronald.

In: Remote Sensing of Environment, Vol. 200, 10.2017, p. 18-30.

Research output: Contribution to journalArticle

Thompson, DR, Hochberg, EJ, Asner, GP, Green, RO, Knapp, DE, Gao, BC, Garcia, R, Gierach, M, Lee, Z, Maritorena, S & Fick, R 2017, 'Airborne mapping of benthic reflectance spectra with Bayesian linear mixtures', Remote Sensing of Environment, vol. 200, pp. 18-30. https://doi.org/10.1016/j.rse.2017.07.030
Thompson, David R. ; Hochberg, Eric J. ; Asner, Gregory P. ; Green, Robert O. ; Knapp, David E. ; Gao, Bo Cai ; Garcia, Rodrigo ; Gierach, Michelle ; Lee, Zhongping ; Maritorena, Stephane ; Fick, Ronald. / Airborne mapping of benthic reflectance spectra with Bayesian linear mixtures. In: Remote Sensing of Environment. 2017 ; Vol. 200. pp. 18-30.
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