Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate Island
Turbidity is a parameter of the marine environment that greatly affects the condition of seagrass whose habitat is an intertidal zone in shallow sea waters. Seagrass is an important type of ecosystem that can be found in several coastal areas of Ternate Island. This study aims to analyze the turbidi...
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| Format: | Article |
| Language: | English |
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Universitas Syiah Kuala
2025-07-01
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| Series: | Depik Jurnal |
| Online Access: | https://jurnal.usk.ac.id/depik/article/view/46989 |
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| author | Rustam Effendi Paembonan Dietriech Geoffrey Bengen I Wayan Nurjaya Syamsul Bahri Agus Nyoman Metta N Natih Beginer Subhan Joko Santoso |
| author_facet | Rustam Effendi Paembonan Dietriech Geoffrey Bengen I Wayan Nurjaya Syamsul Bahri Agus Nyoman Metta N Natih Beginer Subhan Joko Santoso |
| author_sort | Rustam Effendi Paembonan |
| collection | DOAJ |
| description | Turbidity is a parameter of the marine environment that greatly affects the condition of seagrass whose habitat is an intertidal zone in shallow sea waters. Seagrass is an important type of ecosystem that can be found in several coastal areas of Ternate Island. This study aims to analyze the turbidity conditions of seagrass habitat waters and apply a remote sensing algorithm using Sentinel 2B images. The turbidity research method was carried out by field measurements. The turbidity algorithm model used refers to references with mathematical equations (Rrs665-0.014)/0.013, and the development of a new algorithm as a comparison algorithm. Both algorithms were validated with field data to determine the level of accuracy using the Normalized Mean Absolute Error (NMAE) and determination coefficient (R2). The results were obtained from turbidity data with values ranging from 0.3 NTU to 1.5 NTU with an average value of 0.87 ± 0.45 NTU. The Sentinel 2B image in this study was restored with geometric corrections, atmosphere, radiometric digital values, land masking, and sun glint. The turbidity algorithm model used obtained good accuracy in mapping and monitoring the turbidity of seagrass habitat waters on Ternate Island. The application of the turbidity algorithm used as a reference in this study has an NMAE value of 50.44 and R2 of 0.8822, while the newly discovered turbidity algorithm has an NMAE value of 29.38 and R2 of 0.8827.
Keywords:
remote sensing
ecosystems
coastal
sedimentation
North Maluku |
| format | Article |
| id | doaj-art-73f23e1b978f45d08c59196d5ba12d45 |
| institution | Kabale University |
| issn | 2089-7790 2502-6194 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Universitas Syiah Kuala |
| record_format | Article |
| series | Depik Jurnal |
| spelling | doaj-art-73f23e1b978f45d08c59196d5ba12d452025-08-20T03:39:41ZengUniversitas Syiah KualaDepik Jurnal2089-77902502-61942025-07-010010.13170/depik.0.0.4698921159Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate IslandRustam Effendi Paembonan0Dietriech Geoffrey Bengen1I Wayan Nurjaya2Syamsul Bahri Agus3Nyoman Metta N Natih4Beginer Subhan5Joko Santoso6Khairun UniversityIPB UniversityIPB UniversityIPB UniversityIPB UniversityIPB UniversityIPB UniversityTurbidity is a parameter of the marine environment that greatly affects the condition of seagrass whose habitat is an intertidal zone in shallow sea waters. Seagrass is an important type of ecosystem that can be found in several coastal areas of Ternate Island. This study aims to analyze the turbidity conditions of seagrass habitat waters and apply a remote sensing algorithm using Sentinel 2B images. The turbidity research method was carried out by field measurements. The turbidity algorithm model used refers to references with mathematical equations (Rrs665-0.014)/0.013, and the development of a new algorithm as a comparison algorithm. Both algorithms were validated with field data to determine the level of accuracy using the Normalized Mean Absolute Error (NMAE) and determination coefficient (R2). The results were obtained from turbidity data with values ranging from 0.3 NTU to 1.5 NTU with an average value of 0.87 ± 0.45 NTU. The Sentinel 2B image in this study was restored with geometric corrections, atmosphere, radiometric digital values, land masking, and sun glint. The turbidity algorithm model used obtained good accuracy in mapping and monitoring the turbidity of seagrass habitat waters on Ternate Island. The application of the turbidity algorithm used as a reference in this study has an NMAE value of 50.44 and R2 of 0.8822, while the newly discovered turbidity algorithm has an NMAE value of 29.38 and R2 of 0.8827. Keywords: remote sensing ecosystems coastal sedimentation North Malukuhttps://jurnal.usk.ac.id/depik/article/view/46989 |
| spellingShingle | Rustam Effendi Paembonan Dietriech Geoffrey Bengen I Wayan Nurjaya Syamsul Bahri Agus Nyoman Metta N Natih Beginer Subhan Joko Santoso Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate Island Depik Jurnal |
| title | Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate Island |
| title_full | Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate Island |
| title_fullStr | Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate Island |
| title_full_unstemmed | Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate Island |
| title_short | Mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel-2B imagery in Ternate Island |
| title_sort | mapping and validation of spatial algorithm for monitoring turbidity of seagrass habitat using sentinel 2b imagery in ternate island |
| url | https://jurnal.usk.ac.id/depik/article/view/46989 |
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