The ability to detect oil spills remotely is important in marine environmental monitoring. The optical polarization remote sensing has the unique advantage of inversion of refractive index of spilled oils which is the key parameter for calculation of sunglint reflectance. Compared to nonpolarization optical image, the degree of linear polarization (DOLP) of spilled oil's sunglint depends on the refractive index and viewing angles but not on the surface roughness. Accurate correction of sunglint reflectance can promote optical estimation of spilled oils. In this article, a polarized optical model was used to calculate equivalent refractive index of Deepwater Horizon (DWH) spilled oils using space-borne Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) images covering Gulf of Mexico (GOM) in 2010. When the angle (θm) between the direction of the flat surface specular reflection and that of observation is less than 20°, the PARASOL-derived and modeled DOLPs agree well, and the atmospheric polarization effects can be neglected. The equivalent refractive index of the spilled oil area, which implies the relative proportions of seawater and spilled oil in each pixel, could be estimated using polarized remote sensing under sunglint. Furthermore, if the relationship between the equivalent refractive index and remote sensing reflectance (Rrs) of spilled oils in the remote sensing images can be given, it might be used to correct the sunglint effect on various spilled oils, thereby leading to an improvement for optical quantifying spilled oil volume.

It has been presented in this study, the evaluation of remote sensing reflectance (R _rs ) derived from the atmospheric correction of Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua satellite. A switching algorithm was developed for the atmospheric correction. The evaluation shows that MODIS measured R _rs at visible bands compare reasonably well with in situ R _rs , with the mean ratios ranging from 0.955 to 1.374. The spatiotemporal variation of R _rs in Bohai sea is characterized using MODIS data from July 2002 to June 2014. It is noted from the time series of monthly mean R _rs and wind speed a time lag for the response of Rrs to wind. Significant linear relationship is found between the monthly mean R _rs and wind speed, with the correlation coefficients much higher than those between the annual mean R _rs and total river discharge, indicating that wind plays a more important role than river discharge in determining the variation of R _rs in Bohai sea. Strong seasonal variation is observed in the monthly mean R _rs , which is the lowest during July and August and increases to the maximum in January-February and then decreases. Using the entire archive of MODIS/Aqua data over Bohai sea, this study documents the apparent optical properties which serve as an indicator of sediment transport, providing a low-cost and efficient way for monitoring the marine environmental change and for demonstrating the effect from sediment transport on coastal morphology and ecosystem.

A comparison between efforts to detect methane anomalies by a simple band ratio approach from the Airborne Visual Infrared Imaging Spectrometer-Classic (AVIRIS-C) data for the Kern Front oil field, Central California, and the Coal Oil Point marine hydrocarbon seep field, offshore southern California, was conducted. The detection succeeded for the marine source and failed for the terrestrial source, despite these sources being of comparable strength. Scene differences were investigated in higher spectral and spatial resolution collected by the AVIRIS-C successor instrument, AVIRIS Next Generation (AVIRIS-NG), by a sensitivity study. Sensitivity to factors including water vapor, aerosol, planetary boundary layer (PBL) structure, illumination and viewing angle, and surface albedo clutter were explored. The study used the residual radiance method, with sensitivity derived from MODTRAN (MODerate resolution atmospheric correction TRANsmission) simulations of column methane (XCH₄). Simulations used the spectral specifications and geometries of AVIRIS-NG and were based on a uniform or an in situ vertical CH₄ profile, which was measured concurrent with the AVIRIS-NG data. Small but significant sensitivity was found for PBL structure and water vapor; however, highly non-linear, extremely strong sensitivity was found for surface albedo error. For example, a 10% decrease in the surface albedo corresponded to a 300% XCH₄ increase over background XCH₄ to compensate for the total signal, less so for stronger plumes. This strong non-linear sensitivity resulted from the high percentage of surface-reflected radiance in the airborne at-sensor total radiance. Coarse spectral resolution and feedback from interferents like water vapor underlay this sensitivity. Imaging spectrometry like AVIRIS and the Hyperspectral InfraRed Imager (HyspIRI) candidate satellite mission, have the advantages of contextual spatial information and greater at-sensor total radiance. However, they also face challenges due to their relatively broad spectral resolution compared to trace gas specific orbital sensors, e.g., the Greenhouse gases Observing SATellite (GOSAT), which is especially applicable to trace gas retrievals over scenes with high spectral albedo variability. Results of the sensitivity analysis are applicable for the residual radiance method and CH₄ profiles used in the analysis, but they illustrate potential significant challenges in CH₄ retrievals using other approaches.

An atmospheric correction algorithm has been developed for the Airborne Imaging Spectrometer for Applications (AISA) imagery over optically shallow waters in Sugarloaf Key of the Florida Keys. The AISA data were collected repeatedly during several days in May 2012, October 2012, and May 2013. Non-zero near-infrared (NIR) remote-sensing reflectance (R_rs) was accounted for through iterations, based on the relationship of field-measured R_rs between the NIR and red wavelengths. Validation showed mean ratios of 0.94–1.002 between AISA-retrieved and in situ R_rs in the blue to red wavelengths, with uncertainties generally <0.003 sr^–1. Such an approach led to observations of short-term changes in AISA-retrieved R_rs from repeated measurements over waters with bottom types of seagrass meadow, sand, and patch reef. Some of these changes are larger than twofold the R_rs uncertainties from AISA retrievals, therefore representing statistically significant changes that can be well observed from airborne measurements. Through radiative transfer modelling, we demonstrated that short-term R_rs changes within 1 hour resulted primarily from sediment resuspension, while tides played a relatively minor role due to the small variation in tidal heights. A sensitivity analysis indicated that although R_rs generally increases with decreasing tide height but increasing suspended sediments, more changes were observed over sandy bottom than over seagrass. The case study suggests that repeated airborne measurements may be used to study short-term changes in shallow-water environments, and such a capacity may be enhanced with future geostationary satellite missions specifically designed to observe coastal ecosystems.