title: Spectral interdependence of remote-sensing reflectance and its implications on the design of ocean color satellite sensors.
abstract: Using 901 remote-sensing reflectance spectra (R(rs)(λ), sr⁻¹, λ from 400 to 700 nm with a 5 nm resolution), we evaluated the correlations of R(rs)(λ) between neighboring spectral bands in order to characterize (1) the spectral interdependence of R(rs)(λ) at different bands and (2) to what extent hyperspectral R(rs)(λ) can be reconstructed from multiband measurements. The 901 R(rs) spectra were measured over a wide variety of aquatic environments in which water color varied from oceanic blue to coastal green or brown, with chlorophyll-a concentrations ranging from ~0.02 to >100  mg  m⁻³, bottom depths from ~1  m to >1000  m, and bottom substrates including sand, coral reef, and seagrass. The correlation coefficient of R(rs)(λ) between neighboring bands at center wavelengths λ(k) and λ(l), r(Δλ)(λ(k), λ(l)), was evaluated systematically, with the spectral gap (Δλ=λ(l)-λ(k)) changing between 5, 10, 15, 20, 25, and 30 nm, respectively. It was found that r(Δλ) decreased with increasing Δλ, but remained >0.97 for Δλ≤20  nm for all spectral bands. Further, using 15 spectral bands between 400 and 710 nm, we reconstructed, via multivariant linear regression, hyperspectral R(rs)(λ) (from 400 to 700 nm with a 5 nm resolution). The percentage difference between measured and reconstructed R(rs) for each band in the 400-700 nm range was generally less than 1%, with a correlation coefficient close to 1.0. The mean absolute error between measured and reconstructed R(rs) was about 0.00002  sr⁻¹ for each band, which is significantly smaller than the R(rs) uncertainties from all past and current ocean color satellite radiometric products. These results echo findings of earlier studies that R(rs) measurements at ~15 spectral bands in the visible domain can provide nearly identical spectral information as with hyperspectral (contiguous bands at 5 nm spectral resolution) measurements. Such results provide insights for data storage and handling of large volume hyperspectral data as well as for the design of future ocean color satellite sensors.
authors.forename: Zhongping
authors.initials: Z
authors.lastname: Lee
authors.forename: Shaoling
authors.initials: S
authors.lastname: Shang
authors.forename: Chuanmin
authors.initials: C
authors.lastname: Hu
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Zibordi
mesh_terms: D003116:Color; D003124:Colorimetry / Q000295:instrumentation*; D004784:Environmental Monitoring / Q000295:instrumentation*; D004867:Equipment Design; D019544:Equipment Failure Analysis; D009792:Oceans and Seas; D058998:Remote Sensing Technology / Q000295:instrumentation*; D012623:Seawater / Q000032:analysis* / Q000737:chemistry; D018531:Spacecraft / Q000295:instrumentation*; D013057:Spectrum Analysis / Q000295:instrumentation*; D014159:Transducers