Monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements
A new framework that enables evaluation of the in situ ocean color radiometry measurement uncertainty is presented. The study was conducted on the multispectral data from a permanent mooring deployed in clear open ocean water. The uncertainty is evaluated for each component of the measurement equati...
| Main Authors: | , , , , , , |
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| Format: | Journal Article |
| Language: | English |
| Published: |
AMER METEOROLOGICAL SOC
2020
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/79146 |
| _version_ | 1848764008959574016 |
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| author | Białek, A. Vellucci, V. Gentil, B. Antoine, David Gorroño, J. Fox, N. Underwood, C. |
| author_facet | Białek, A. Vellucci, V. Gentil, B. Antoine, David Gorroño, J. Fox, N. Underwood, C. |
| author_sort | Białek, A. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | A new framework that enables evaluation of the in situ ocean color radiometry measurement uncertainty is presented. The study was conducted on the multispectral data from a permanent mooring deployed in clear open ocean water. The uncertainty is evaluated for each component of the measurement equation and data processing step that leads to deriving the remote sensing reflectance. The Monte Carlo method was selected to handle the data complexity such as correlation and nonlinearity in an efficient manner. The results are presented for a prescreened dataset that is suitable for system vicarious calibration applications. The framework provides uncertainty value per measurement taking into consideration environmental conditions present during acquisition. A summary value is calculated from the statistics of the individual uncertainties per each spectral channel. This summary value is below 4% (k 5 1) for the blue and green spectral range. For the red spectral channels, the summary uncertainty value increases to approximately 5%. The presented method helps to understand the significance of various uncertainty components and to provide a way of identifying major contributors. This can be used for efficient system performance improvement in the future. |
| first_indexed | 2025-11-14T11:12:32Z |
| format | Journal Article |
| id | curtin-20.500.11937-79146 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T11:12:32Z |
| publishDate | 2020 |
| publisher | AMER METEOROLOGICAL SOC |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-791462021-02-11T00:31:19Z Monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements Białek, A. Vellucci, V. Gentil, B. Antoine, David Gorroño, J. Fox, N. Underwood, C. Science & Technology Technology Physical Sciences Engineering, Ocean Meteorology & Atmospheric Sciences Engineering Ocean In situ oceanic observations Quality assurance control Error analysis ATMOSPHERIC CORRECTION CHLOROPHYLL-A RADIANCE INSTRUMENT FACILITY MODIS BUOY A new framework that enables evaluation of the in situ ocean color radiometry measurement uncertainty is presented. The study was conducted on the multispectral data from a permanent mooring deployed in clear open ocean water. The uncertainty is evaluated for each component of the measurement equation and data processing step that leads to deriving the remote sensing reflectance. The Monte Carlo method was selected to handle the data complexity such as correlation and nonlinearity in an efficient manner. The results are presented for a prescreened dataset that is suitable for system vicarious calibration applications. The framework provides uncertainty value per measurement taking into consideration environmental conditions present during acquisition. A summary value is calculated from the statistics of the individual uncertainties per each spectral channel. This summary value is below 4% (k 5 1) for the blue and green spectral range. For the red spectral channels, the summary uncertainty value increases to approximately 5%. The presented method helps to understand the significance of various uncertainty components and to provide a way of identifying major contributors. This can be used for efficient system performance improvement in the future. 2020 Journal Article http://hdl.handle.net/20.500.11937/79146 10.1175/JTECH-D-19-0049.1 English AMER METEOROLOGICAL SOC fulltext |
| spellingShingle | Science & Technology Technology Physical Sciences Engineering, Ocean Meteorology & Atmospheric Sciences Engineering Ocean In situ oceanic observations Quality assurance control Error analysis ATMOSPHERIC CORRECTION CHLOROPHYLL-A RADIANCE INSTRUMENT FACILITY MODIS BUOY Białek, A. Vellucci, V. Gentil, B. Antoine, David Gorroño, J. Fox, N. Underwood, C. Monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements |
| title | Monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements |
| title_full | Monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements |
| title_fullStr | Monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements |
| title_full_unstemmed | Monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements |
| title_short | Monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements |
| title_sort | monte carlo–based quantification of uncertainties in determining ocean remote sensing reflectance from underwater fixed-depth radiometry measurements |
| topic | Science & Technology Technology Physical Sciences Engineering, Ocean Meteorology & Atmospheric Sciences Engineering Ocean In situ oceanic observations Quality assurance control Error analysis ATMOSPHERIC CORRECTION CHLOROPHYLL-A RADIANCE INSTRUMENT FACILITY MODIS BUOY |
| url | http://hdl.handle.net/20.500.11937/79146 |