Abstract:

Remote sensing reflectance, Rrs(λ), is used for validation of airborne and satellite ocean color measurements. Inverse models also employ Rrs measurements to estimate the bio-optical properties of near-surface waters or shallow benthic environments. It has been used to detect algal blooms, floating vegetation. The presence of oil also alters the water’s specular reflectance properties, and thus the measured Rrs. Rrs(λ) is measured from the ship using a handheld spectroradiometer. Multiple measurements of the light reflected from the water’s surface, a portion of the sky, and a calibrated, diffuse reflectance reference plaque are made using a spectroradiometer with a limited field of view. The Rrs measurement is most reliable during moderate solar elevations, using observational angles consistent with remote sensing protocols. Multiple radiance measurements are combined in the computation of Rrs(λ). Measurements were collected in the northern Gulf of Mexico from May 2-12, 2017.

Suggested Citation:

Chuanmin Hu, David English. 2018. Spectral remote sensing reflectance of the water surface collected at multiple stations, cruise DP05, May 2017. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7ZK5F24

Publications:

Barnes, B. B., Cannizzaro, J. P., English, D. C., & Hu, C. (2019). Validation of VIIRS and MODIS reflectance data in coastal and oceanic waters: An assessment of methods. Remote Sensing of Environment, 220, 110–123. doi:10.1016/j.rse.2018.10.034

Purpose:

Remote sensing reflectance was measured to help relate the optical properties and material within the surface waters to values derived from above water or ocean color satellite measurements.

Data Parameters and Units:

Investigators, Affiliations (University of South Florida), Contact, Experiment, Cruise, Station, Data filename, Date (YYYYMMDD), Time (HH:MM:SS), Water depth (m), Cloud percent (%), Wind speed, Wave height, Comments, Wavelength (nm), Remote sensing reflectance(Rrs, sr^-1), Time (DD-MMM-YY HH:MM), Latitude (latt, decimal degrees), Longitude (long, decimal degrees), Approximate station Missing data = -999

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