A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans
The classification of natural waters is a way to generalize and systematize ocean color science. However, there is no consensus on an optimal water classification template in many contexts. In this study, we conducted an unsupervised classification of the PACE (Plankton, Aerosols, Cloud, and Ocean E...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/19/4018 |
| _version_ | 1797515806488133632 |
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| author | Tianxia Jia Yonglin Zhang Rencai Dong |
| author_facet | Tianxia Jia Yonglin Zhang Rencai Dong |
| author_sort | Tianxia Jia |
| collection | DOAJ |
| description | The classification of natural waters is a way to generalize and systematize ocean color science. However, there is no consensus on an optimal water classification template in many contexts. In this study, we conducted an unsupervised classification of the PACE (Plankton, Aerosols, Cloud, and Ocean Ecosystem) synthetic hyperspectral data set, divided the global ocean waters into 15 classes, then obtained a set of fuzzy logic optical water type schemes (abbreviated as the U-OWT in this study) that were tailored for several multispectral satellite sensors, including SeaWiFS, MERIS, MODIS, OLI, VIIRS, MSI, and OLCI. The consistency analysis showed that the performance of U-OWT on different satellite sensors was comparable, and the sensitivity analysis demonstrated the U-OWT could resist a certain degree of input disturbance on remote sensing reflectance. Compared to existing ocean-aimed optical water type schemes, the U-OWT can distinguish more mesotrophic and eutrophic water classes. Furthermore, the U-OWT was highly compatible with other water classification taxonomies, including the trophic state index, the multivariate absorption combinations, and the Forel-Ule Scale, which indirectly demonstrated the potential for global applicability of the U-OWT. This finding was also helpful for the further conversion and unification of different water type taxonomies. As the fundamental basis, the U-OWT can be applied to many oceanic fields that need to be explored in the future. To promote the reproducibility of this study, an IDL<sup>®</sup>-based standalone U-OWT calculation tool is freely distributed. |
| first_indexed | 2024-03-10T06:52:28Z |
| format | Article |
| id | doaj.art-c6b72fc1a2bf4e70ace1d7d001105fbe |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T06:52:28Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-c6b72fc1a2bf4e70ace1d7d001105fbe2023-11-22T16:44:17ZengMDPI AGRemote Sensing2072-42922021-10-011319401810.3390/rs13194018A Universal Fuzzy Logic Optical Water Type Scheme for the Global OceansTianxia Jia0Yonglin Zhang1Rencai Dong2State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, ChinaState Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, ChinaState Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, ChinaThe classification of natural waters is a way to generalize and systematize ocean color science. However, there is no consensus on an optimal water classification template in many contexts. In this study, we conducted an unsupervised classification of the PACE (Plankton, Aerosols, Cloud, and Ocean Ecosystem) synthetic hyperspectral data set, divided the global ocean waters into 15 classes, then obtained a set of fuzzy logic optical water type schemes (abbreviated as the U-OWT in this study) that were tailored for several multispectral satellite sensors, including SeaWiFS, MERIS, MODIS, OLI, VIIRS, MSI, and OLCI. The consistency analysis showed that the performance of U-OWT on different satellite sensors was comparable, and the sensitivity analysis demonstrated the U-OWT could resist a certain degree of input disturbance on remote sensing reflectance. Compared to existing ocean-aimed optical water type schemes, the U-OWT can distinguish more mesotrophic and eutrophic water classes. Furthermore, the U-OWT was highly compatible with other water classification taxonomies, including the trophic state index, the multivariate absorption combinations, and the Forel-Ule Scale, which indirectly demonstrated the potential for global applicability of the U-OWT. This finding was also helpful for the further conversion and unification of different water type taxonomies. As the fundamental basis, the U-OWT can be applied to many oceanic fields that need to be explored in the future. To promote the reproducibility of this study, an IDL<sup>®</sup>-based standalone U-OWT calculation tool is freely distributed.https://www.mdpi.com/2072-4292/13/19/4018ocean colorwater type taxonomiestrophic stateinherent optical propertiesForel-Ule Scale |
| spellingShingle | Tianxia Jia Yonglin Zhang Rencai Dong A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans Remote Sensing ocean color water type taxonomies trophic state inherent optical properties Forel-Ule Scale |
| title | A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans |
| title_full | A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans |
| title_fullStr | A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans |
| title_full_unstemmed | A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans |
| title_short | A Universal Fuzzy Logic Optical Water Type Scheme for the Global Oceans |
| title_sort | universal fuzzy logic optical water type scheme for the global oceans |
| topic | ocean color water type taxonomies trophic state inherent optical properties Forel-Ule Scale |
| url | https://www.mdpi.com/2072-4292/13/19/4018 |
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