Abstract:
This dataset includes two MODIS L1B images and the generated sun glint reflectance (LGN) data after atmospheric correction. LGN was also modeled for the two images according to the sun/view geometry, oil and water fresnel reflection. This dataset introduced atmospheric correction and different oil fresnel reflection with water in the calculation of sun glint reflectance from MODIS imagery. By doing this, the calculated sun glint reflectance results are more accurate and the original concept of sun glint critical angle is refined.
Suggested Citation:
Sun, Shaojie. 2017. Sun glint critical angle oil detection. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/N7GQ6VRG
Data Parameters and Units:
This dataset contains normalized sun glint reflectance (LGN) values in units of sr^−1. The following is a brief description about the contents of each folder in the dataset: 1) Original downloaded MODIS L1A image (../glint_critical_angle/MODIS_L1A/, publically available from https://oceancolor.gsfc.nasa.gov/) T2005153165500.L1A_LAC T2013168165000.L1A_LAC 2) Setup data and information The satellite data is processed via software SeaDAS (publically available from https://seadas.gsfc.nasa.gov/) Modeled data is calculated via Cox and Munk (1954) model, with equations in Section 2.1 of Lu, Y., S. Sun, M. Zhang, B. Murch, and C. Hu (2016), Refinement of the critical angle calculation for the contrast reversal of oil slicks under sunglint, J. Geophys. Res. Oceans, 121, 148–161, doi:10.1002/2015JC011001. 3) Output (a)MODIS derived LGN after atmospheric correction (../glint_critical_angle/MODIS_derived_LGN/, in format of ENVI binary) After atmospheric correction for Rayleigh scattering, aerosol scattering, and beam transmittance from the sun to the ocean surface and from the ocean surface to the satellite sensor. The derived products are: MODIS-drived_LGN_(2005153) MODIS-drived_LGN_(2013168) (b) Modelling LGN based on Cox-Munk model(../glint_critical_angle/modelled_LGN/, in format of ENVI binary) For each day, there are modelling results based on different surface roughness. LGN are modeled via Cox and Munk Model (1954). The inputs for the modelling are solar/sensor view geometry (solar zenith angle, sensor zenith angle and relative azimuth angle between solar input and sensor viewing angle), surface roughness (in parenthesis) and different fresnel reflection of oil and water. In the model, the refractive indexes used for Fresnel reflection coefficients calculation: air, seawater, and surface oil are 1.0, 1.34, and 1.38, respectively.