REMOTE SENSING OF AEROSOLS AND OCEAN COLOR WITH MULTI-ANGLE POLARIMETERS AND SPECTRO-RADIOMETERS

Abstract

The atmospheric correction (AC) is an essential step in ocean color remote sensing. The heritage AC processes applied to MODIS-like spectrometers degrade over optically complex scenes involving absorbing aerosols and/or coastal waters. The rich information content of MAPs has made MAPs a powerful instrument to characterize aerosols and perform AC over optically complex scenes. The MAPs in synergy with the spectrometers such as in NASAÕs PACE and ESAÕs MetOp-SG future satellite missions are examples of the synergistic use of MAPs to improve the AC of the multi- or hyper-spectral radiometers. The first part of this dissertation presents an AC scheme, Polynomial-based Atmospheric Correction (POLYAC), for hyperspectral radiometers based on aerosol and surface information retrieved from collocated MAPs. POLYAC is expected to provide a robust and computationally efficient AC scheme for future satellite missions. One-step AC algorithms are implemented for MAP measurements. These al- gorithms include a forward RT model, with sub-models to represent the optics of the atmosphere, water surface, and water body. The retrieval performances of joint retrieval algorithms partially depend on the balance between model fidelity and the number of forward model parameters. More intricate models can closely resem- ble an observed scene while it becomes computationally demanding and unstable for retrieval algorithms. The ocean color bio-optical models that characterize the water-leaving signal are important. Bio-optical models with more than a single pa- rameter are required to represent the optical properties of coastal waters. Up to date, the number of parameters that are used in these bio-optical models is arbi- trary. The second part of this dissertation evaluates the information content of the water-leaving signal and the water bio-optical models. This work is expected to provide constraints on ocean bio-optical models. The third part of this disserta- tion evaluates the impact of the bio-optical models on MAP retrievals based on the MAPOL algorithm with airborne MAP measurements. The study evaluates three bio-optical models representing open and coastal waters. This work is expected to contribute to the development of MAP retrieval algorithms for aerosols and ocean color retrievals. The bio-optical models can also be easily applied to other retrieval algorithms as well.