Investigation of Spectral Band Requirements for Improving Retrievals of Phytoplankton Functional Types

Abstract

Abstract:Studying phytoplankton functional types (PFTs) from space is possible due to recent advances in remote sensing. Though a variety of products are available, the limited number of wavelengths available compared to the number of model parameters needed to be retrieved is still a major problem in using ocean-color data for PFT retrievals. Here, we investigated which band placement could improve retrievals of three particular PFTs (diatoms, coccolithophores and cyanobacteria). In addition to analyzing dominant spectral features in the absorption spectra of the target PFTs, two previously-developed methods using measured spectra were applied to simulated data. Such a synthetic dataset allowed for significantly increasing the number of scenarios and enabled a full control over parameters causing spectral changes. We evaluated the chosen band placement by applying an adapted ocean reflectance inversion, as utilized in the generalized inherent optical properties (GIOP) retrieval. Results show that the optimal band settings depend on the method applied to determine the bands placement, as well as on the internal variability of the dataset investigated. Therefore, continuous hyperspectral instruments would be most beneficial for discriminating multiple PFTs, though a small improvement in spectral sampling and resolution does not significantly modify the results. Bands, which could be added to future instruments (e.g., Ocean and Land Colour Instrument (OLCI) instrument on the upcoming Sentinel-3B,-3C,-3D, etc., and further satellites) in order to enhance PFT retrieval capabilities, were also determined.

Synergistic Exploitation of Hyper- and Multi-Spectral Precursor Sentinel Measurements to Determine Phytoplankton Functional Types (SynSenPFT)

“…In the study by Organelli et al (2013) it was highlighted that the use of hyperspectral data (radiometric information with a spectral resolution higher than those coming from the current ocean color sensors) would allow to improve the accuracy of spectral-based phytoplankton composition retrievals. This was also supported by Wolanin et al (2016b) who applied PFT retrievals to a large synthetically simulated data set testing different band settings for multispectral data and various resolutions of hyperspectral information. The authors showed that hyperspectral data are the most beneficial for various PFT retrievals.…”

A Consumer's Guide to Satellite Remote Sensing of Multiple Phytoplankton Groups in the Global Ocean

“…Planned capability will expand spectral, spatial, and temporal resolution, in addition to radiometric sensitivity (Mouw et al, 2015). Increased spectral resolution will provide the ability to exploit more spectral signatures of PFTs (Isada et al, 2015;Wolanin et al, 2016). In addition to increased spectral resolution, increased spatial resolution may lend clarity to coastal processes and phytoplankton response to finer scale physical features.…”

Obtaining Phytoplankton Diversity from Ocean Color: A Scientific Roadmap for Future Development

“…to specifically model the variation of composition of PSC or certain (dominant) PT, respectively, and assessed the potential of retrievals in different water types. Werdell et al (2014) optimized the inversion scheme of GIOP to finally retrieve absence or presence of Noctiluca miliaris from MODIS data, while Wolanin et al (2016) used this method to identify optimal band placements for multi-and hyper-spectral satellite data for successful retrievals of certain PT. The results of this study indicate that four additional bands (381, 473, 532, and 594 nm) for the Ocean and Land Colour Instrument (OLCI) would potentially enable absorption-based quantitative retrievals of diatoms, cyanobacteria, and coccolithophores.…”

“…In the few last years, radiative transfer models (RTM) have been used to develop and assess the sensitivity of analytical (spectral) PG retrievals or to find suitable spectral characteristics necessary for ocean color sensors to retrieve PG. Werdell et al (2014) and Wolanin et al (2016) used the GIOP (Generalized Inherent Optical Property) model software (Werdell et al, 2013) to invert reflectance spectra (either water-leaving or top of atmosphere), and Wolanin et al (2015) used the coupled ocean-atmosphere RTM SCIATRAN (Rozanov et al, 2014) to test the sensitivity of a PT retrieval (PhytoDOAS). Evers-King et al (2014) and Xi et al (2015) used the ocean RTM HydroLight (Sequoia Scientific.)…”