Polarized observations for advanced atmosphere-ocean algorithms using airborne multi-spectral hyper-angular polarimetric imager
Journal of Quantitative Spectroscopy and Radiative Transfer, ISSN: 0022-4073, Vol: 262, Page: 107515
2021
- 14Citations
- 18Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Airborne measurements of the linear polarization state of light were carried out over coastal and open ocean conditions to study aerosol and water column properties and investigate the possibility of using a multi-spectral, hyper-angular imaging polarimeter for retrieving aerosol and hydrosol optical properties. The instrument, the Versatile Imager for the Coastal Ocean (VICO), is used to support the analysis of ocean color polarized observations and their implication for future space-borne polarimetry such as the polarimeters planned to be deployed with the NASA Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) mission. Several sets of images at different viewing angles from the visible to the near-infrared spectrum were collected and compared with simulations using a vector radiative transfer (VRT) code. The simulations were obtained based on measured seawater inherent optical properties from shipborne instruments and measured atmospheric parameters from the Aerosol Robotic Network (AERONET) and a shipborne sunphotometer at different locations. An uncertainty method has been derived by propagating uncertainties from the measured polarized radiances. The method demonstrates practicable uncertainty formulations that can be used to construct a measurement uncertainty budget for the polarized data products. Results from VICO and the VRT simulation are consistent for both radiance and polarization spectrum at all the measured viewing angles. The total and polarized water-leaving reflectances are retrieved at four bands and varied geometries. It is also shown that the polarized remote sensing reflectance measured at various angles could be used to distinguish between the aerosols’ and hydrosols’ optical signatures by exploiting the fact that the polarized reflectance is fairly insensitive to hydrosols for given acquisition geometries. This study thus provides an opportunity to investigate various relationships between the microphysical properties of the oceanic and atmospheric particulates such as refractive index and particle size properties. It also contributes to the development of polarization-based inverse ocean color algorithms. Finally, the provided analysis gives insights for the validation of the ocean color parameters that will be retrieved from the forthcoming polarimetric satellite missions.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S002240732100008X; http://dx.doi.org/10.1016/j.jqsrt.2021.107515; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85099698471&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S002240732100008X; https://api.elsevier.com/content/article/PII:S002240732100008X?httpAccept=text/xml; https://api.elsevier.com/content/article/PII:S002240732100008X?httpAccept=text/plain; https://dul.usage.elsevier.com/doi/; https://dx.doi.org/10.1016/j.jqsrt.2021.107515
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know