Data

MODIS derived Coloured Dissolved Organic Matter (CDOM) datasets

Name: MODIS derived Coloured Dissolved Organic Matter (CDOM) datasets
Published: 2013

Geoscience Australia

Huang, Z.

Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]

ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://pid.geoscience.gov.au/dataset/ga/77005&rft.title=MODIS derived Coloured Dissolved Organic Matter (CDOM) datasets&rft.identifier=https://pid.geoscience.gov.au/dataset/ga/77005&rft.publisher=Geoscience Australia&rft.description=The datasets measure the Coloured Dissolved Organic Matter (CDOM) concentrations of ocean surface waters. They are derived products from MODIS (aqua) images using NASA's SeaDAS image processing software. The extent of the datasets covers the entire Australian EEZ and surrounding waters (including the southern ocean). The spatial resolution of the datasets is 0.01 dd. The datasets contain 36 monthly CDOM layers between 2009 and 2011. The unit of the datasets is 1/m.Maintenance and Update Frequency: notPlannedStatement: The CDOM datasets are derived products of MODIS (Aqua) images. SeaDAS (version 6.1) was used to process the MODIS data from raw to L3 products. The algorithm used here was based on a modified QAA (Lee et al., 2002) algorithm (Zhu and Yu, 2012): j1=0.63 j2=0.88 aw_443=0.00696 ap_443=j1 * power(bbp_555,j2) ag_443=a_443 - aw_443 - ap_443 Where a_443 is total absorption coefficient at 443 nm, aw_443 is water absorption coefficient at 443 nm, ap_443 is particles absorption coefficient at 443 nm, bbp_555 is particles backscatter coefficient at 555 nm, and ag_443 is CDOM absorption coefficient at 443 nm. bbp_555 and a_443 from QAA algorithm can be directly derived using SeaDAS. The sequences of processing included: 1. raw - L1A, 2. L1A - L1B, 3. L1B - L2, 4. L2 - L3 (spatial) binning, and 5. L3 binning to L3 time-binning. The first four steps were applied to all individual (daily) raw images to obtain bbp_555 and a_443 products. After completing the above steps for one-month-worth images (around 300 images), in the fifth step, four weekly images were generated: 1. week1: from the 1st to the 7th of the month; 2. week2: from the 8th to the 14th of the month; 3. week3: from the 15th to the 21st of the month; 4. week4: from the 22nd to the last day of the month. The four weekly images were exported as HDF files, then imported into ArcGIS and converted into ArcInfo grids. Next, the weekly products of bbp_555 and a_443 were entered into the above-described algorithm to calculate weekly CDOM products. Finally, the four weekly CDOM grids were mosaiced into a monthly image using the averaging method. The above processes were repeated to generate the final 36 monthly datasets between 2009 and 2011. Lee, Z.P., Carder, K.L., Arnone, R.A., 2002. Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters, Applied Optics, 41, 5755-5772. Zhu, W.; Yu, Q.; , Inversion of Chromophoric Dissolved Organic Matter From EO-1 Hyperion Imagery for Turbid Estuarine and Coastal Waters, Geoscience and Remote Sensing, IEEE Transactions on , vol.PP, no.99, pp.1-13, 0 doi: 10.1109/TGRS.2012.2224117&rft.creator=Huang, Z. &rft.date=2013&rft.coverage=westlimit=100; southlimit=-60.0; eastlimit=170; northlimit=-5.0&rft.coverage=westlimit=100; southlimit=-60.0; eastlimit=170; northlimit=-5.0&rft_rights=&rft_rights=Creative Commons Attribution 4.0 International Licence&rft_rights=CC-BY&rft_rights=4.0&rft_rights=http://creativecommons.org/licenses/&rft_rights=WWW:LINK-1.0-http--link&rft_rights=Australian Government Security ClassificationSystem&rft_rights=https://www.protectivesecurity.gov.au/Pages/default.aspx&rft_rights=WWW:LINK-1.0-http--link&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/by/4.0&rft_subject=oceans&rft_subject=Marine Data&rft_subject=remote sensing&rft_subject=NERP Marine Biodiversity Hub&rft_subject=marine&rft_subject=NERP&rft_subject=Marine Geoscience&rft_subject=EARTH SCIENCES&rft_subject=GEOLOGY&rft_subject=Published_External&rft.type=dataset&rft.language=English Access the data

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Brief description

The datasets measure the Coloured Dissolved Organic Matter (CDOM) concentrations of ocean surface waters. They are derived products from MODIS (aqua) images using NASA's SeaDAS image processing software. The extent of the datasets covers the entire Australian EEZ and surrounding waters (including the southern ocean). The spatial resolution of the datasets is 0.01 dd. The datasets contain 36 monthly CDOM layers between 2009 and 2011. The unit of the datasets is 1/m.

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Maintenance and Update Frequency: notPlanned

Statement: The CDOM datasets are derived products of MODIS (Aqua) images. SeaDAS (version 6.1) was used to process the MODIS data from raw to L3 products. The algorithm used here was based on a modified QAA (Lee et al., 2002) algorithm (Zhu and Yu, 2012):
j1=0.63
j2=0.88
aw_443=0.00696
ap_443=j1 * power(bbp_555,j2)
ag_443=a_443 - aw_443 - ap_443
Where a_443 is total absorption coefficient at 443 nm, aw_443 is water absorption coefficient at 443 nm, ap_443 is particles absorption coefficient at 443 nm, bbp_555 is particles backscatter coefficient at 555 nm, and ag_443 is CDOM absorption coefficient at 443 nm.
bbp_555 and a_443 from QAA algorithm can be directly derived using SeaDAS.
The sequences of processing included:
1. raw - L1A,
2. L1A - L1B,
3. L1B - L2,
4. L2 - L3 (spatial) binning, and
5. L3 binning to L3 time-binning.
The first four steps were applied to all individual (daily) raw images to obtain bbp_555 and a_443 products. After completing the above steps for one-month-worth images (around 300 images), in the fifth step, four weekly images were generated:
1. week1: from the 1st to the 7th of the month;
2. week2: from the 8th to the 14th of the month;
3. week3: from the 15th to the 21st of the month;
4. week4: from the 22nd to the last day of the month.
The four weekly images were exported as HDF files, then imported into ArcGIS and converted into ArcInfo grids. Next, the weekly products of bbp_555 and a_443 were entered into the above-described algorithm to calculate weekly CDOM products. Finally, the four weekly CDOM grids were mosaiced into a monthly image using the averaging method.
The above processes were repeated to generate the final 36 monthly datasets between 2009 and 2011.
Lee, Z.P., Carder, K.L., Arnone, R.A., 2002. Deriving inherent optical properties from water color: a multiband quasi-analytical algorithm for optically deep waters, Applied Optics, 41, 5755-5772.
Zhu, W.; Yu, Q.; , "Inversion of Chromophoric Dissolved Organic Matter From EO-1 Hyperion Imagery for Turbid Estuarine and Coastal Waters," Geoscience and Remote Sensing, IEEE Transactions on , vol.PP, no.99, pp.1-13, 0 doi: 10.1109/TGRS.2012.2224117

Issued: 2013

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text: westlimit=100; southlimit=-60.0; eastlimit=170; northlimit=-5.0

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global : e3dd1af5-7b00-50fd-e044-00144fdd4fa6
URI : pid.geoscience.gov.au/dataset/ga/77005

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MODIS derived Coloured Dissolved Organic Matter (CDOM) datasets

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