Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates
This study, focusing on the Antarctic polynyas, performed the imputation of chlorophyll-a concentration (Chl-a) dataset, which is one of the ocean color products mainly used for estimating primary productivity, using the Data Interpolating Empirical Orthogonal Function method and constructed accurat...
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Online Access: | https://doi.org/10.22761/GD.2023.0002 https://doaj.org/article/708c671394674fe495d3fd8d507ea182 |
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ftdoajarticles:oai:doaj.org/article:708c671394674fe495d3fd8d507ea182 2023-10-09T21:46:58+02:00 Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates Jinku Park Sungjae Lee Jeong-Hoon Kim Hyun-Cheol Kim 2023-03-01T00:00:00Z https://doi.org/10.22761/GD.2023.0002 https://doaj.org/article/708c671394674fe495d3fd8d507ea182 EN KO eng kor GeoAI Data Society http://geodata.kr/upload/pdf/GD-2023-0002.pdf https://doaj.org/toc/2713-5004 2713-5004 doi:10.22761/GD.2023.0002 https://doaj.org/article/708c671394674fe495d3fd8d507ea182 Geo Data, Vol 5, Iss 1, Pp 8-14 (2023) antarctic polynyas ocean color chlorophyll-a concentration imputation data interpolating empirical orthogonal function Environmental sciences GE1-350 Geology QE1-996.5 article 2023 ftdoajarticles https://doi.org/10.22761/GD.2023.0002 2023-09-10T00:35:21Z This study, focusing on the Antarctic polynyas, performed the imputation of chlorophyll-a concentration (Chl-a) dataset, which is one of the ocean color products mainly used for estimating primary productivity, using the Data Interpolating Empirical Orthogonal Function method and constructed accurate time-series data that excludes as much uncertainty as possible in long-term variability studies due to missing data. The polynya regions were classified into a total of 23 zones through quantitative criterions, and the statistical accuracy of imputation performance was 0.89 for R2 and 0.42, 0.24, and 0.15 for root mean square error, mean squared error, mean absolute error, respectively, on average, showing the ability to perform generally accurate reconstruction. Finally, the reconstructed Chl-a data showed a relatively stable fluctuation compared with standard satellite Chl-a data, and tended to be underestimated due to the expansion of the observable regions. We expect that securing these relatively stable and accurate estimates will be significantly different from the time-series data composed of standard Chl-a estimates, enabling more accurate variability and trend analysis. Article in Journal/Newspaper Antarc* Antarctic Antarctica Directory of Open Access Journals: DOAJ Articles Antarctic The Antarctic GEO DATA 5 1 8 14 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English Korean |
topic |
antarctic polynyas ocean color chlorophyll-a concentration imputation data interpolating empirical orthogonal function Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
antarctic polynyas ocean color chlorophyll-a concentration imputation data interpolating empirical orthogonal function Environmental sciences GE1-350 Geology QE1-996.5 Jinku Park Sungjae Lee Jeong-Hoon Kim Hyun-Cheol Kim Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates |
topic_facet |
antarctic polynyas ocean color chlorophyll-a concentration imputation data interpolating empirical orthogonal function Environmental sciences GE1-350 Geology QE1-996.5 |
description |
This study, focusing on the Antarctic polynyas, performed the imputation of chlorophyll-a concentration (Chl-a) dataset, which is one of the ocean color products mainly used for estimating primary productivity, using the Data Interpolating Empirical Orthogonal Function method and constructed accurate time-series data that excludes as much uncertainty as possible in long-term variability studies due to missing data. The polynya regions were classified into a total of 23 zones through quantitative criterions, and the statistical accuracy of imputation performance was 0.89 for R2 and 0.42, 0.24, and 0.15 for root mean square error, mean squared error, mean absolute error, respectively, on average, showing the ability to perform generally accurate reconstruction. Finally, the reconstructed Chl-a data showed a relatively stable fluctuation compared with standard satellite Chl-a data, and tended to be underestimated due to the expansion of the observable regions. We expect that securing these relatively stable and accurate estimates will be significantly different from the time-series data composed of standard Chl-a estimates, enabling more accurate variability and trend analysis. |
format |
Article in Journal/Newspaper |
author |
Jinku Park Sungjae Lee Jeong-Hoon Kim Hyun-Cheol Kim |
author_facet |
Jinku Park Sungjae Lee Jeong-Hoon Kim Hyun-Cheol Kim |
author_sort |
Jinku Park |
title |
Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates |
title_short |
Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates |
title_full |
Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates |
title_fullStr |
Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates |
title_full_unstemmed |
Imputation of Ocean-color Product in Polynya Region of Antarctica for Primary Productivity Estimates |
title_sort |
imputation of ocean-color product in polynya region of antarctica for primary productivity estimates |
publisher |
GeoAI Data Society |
publishDate |
2023 |
url |
https://doi.org/10.22761/GD.2023.0002 https://doaj.org/article/708c671394674fe495d3fd8d507ea182 |
geographic |
Antarctic The Antarctic |
geographic_facet |
Antarctic The Antarctic |
genre |
Antarc* Antarctic Antarctica |
genre_facet |
Antarc* Antarctic Antarctica |
op_source |
Geo Data, Vol 5, Iss 1, Pp 8-14 (2023) |
op_relation |
http://geodata.kr/upload/pdf/GD-2023-0002.pdf https://doaj.org/toc/2713-5004 2713-5004 doi:10.22761/GD.2023.0002 https://doaj.org/article/708c671394674fe495d3fd8d507ea182 |
op_doi |
https://doi.org/10.22761/GD.2023.0002 |
container_title |
GEO DATA |
container_volume |
5 |
container_issue |
1 |
container_start_page |
8 |
op_container_end_page |
14 |
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1779309602122235904 |