Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra Landsat
Remote sensing-based research in Indonesia using satellite imagery frequently faces the challenge of cloud coverage due to the tropical country. One spatial data that can be extracted from satellite imagery is bathymetry. However, cloud-covered water bathymetric extraction still needs to be examined...
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| Format: | Article |
| Language: | English |
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Department of Earth Science and Technology, Universitas Negeri Gorontalo
2022-07-01
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| Series: | Jambura Geoscience Review |
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| Online Access: | https://ejurnal.ung.ac.id/index.php/jgeosrev/article/view/13886 |
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| author | Gerardus David Ady Purnama Bayuaji Seftiawan Samsu Rijal Kuncoro Teguh Setiawan Kholifatul Aziz |
| author_facet | Gerardus David Ady Purnama Bayuaji Seftiawan Samsu Rijal Kuncoro Teguh Setiawan Kholifatul Aziz |
| author_sort | Gerardus David Ady Purnama Bayuaji |
| collection | DOAJ |
| description | Remote sensing-based research in Indonesia using satellite imagery frequently faces the challenge of cloud coverage due to the tropical country. One spatial data that can be extracted from satellite imagery is bathymetry. However, cloud-covered water bathymetric extraction still needs to be examined. This study aims to understand the ability of Landsat 7 ETM+ acquired on 29 July 2013, and Landsat 8, acquired on 24 July 2020, as the representative of non-cloudy image compared to Landsat 8, acquired on 9 August 2020, as the cloudy image. Stumpf algorithm was applied, including a statistical approach of linear regression analysis with in-situ data measurement from Single Beam Echo-Sounder (SBES) to derive the absolute bathymetric map with several classes of depth ranging from 0 – 2 m up to 10 m. To assess the accuracy, RMSE and confusion matrix was used. The result shows that Landsat 7 ETM+ yields the highest R2 with 0,52, while the lowest total RMSE (8,167 m) and highest overall accuracy of about 69% from the confusion matrix was achieved by the cloudy image of Landsat 8. Nevertheless, the highest absolute depth value yield by Landsat 8 non-cloudy image with 16,1 m. This research confirms that the highest R2 value does not always produce the best model, but it is still promised to be used. Furthermore, the quality of the imagery based on its percentage of cloud coverage is affecting the resulted model. |
| first_indexed | 2024-04-12T07:02:49Z |
| format | Article |
| id | doaj.art-965e98eda3634d4eb58515aae17a6096 |
| institution | Directory Open Access Journal |
| issn | 2623-0682 2656-0380 |
| language | English |
| last_indexed | 2024-04-12T07:02:49Z |
| publishDate | 2022-07-01 |
| publisher | Department of Earth Science and Technology, Universitas Negeri Gorontalo |
| record_format | Article |
| series | Jambura Geoscience Review |
| spelling | doaj.art-965e98eda3634d4eb58515aae17a60962022-12-22T03:42:58ZengDepartment of Earth Science and Technology, Universitas Negeri GorontaloJambura Geoscience Review2623-06822656-03802022-07-014210210910.34312/jgeosrev.v4i2.138864254Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra LandsatGerardus David Ady Purnama Bayuaji0Seftiawan Samsu Rijal1Kuncoro Teguh Setiawan2Kholifatul Aziz3Program Studi Ilmu Kelautan, Fakultas Perikanan dan Ilmu Kelautan, Universitas BrawijayaProgram Studi Ilmu Kelautan, Fakultas Perikanan dan Ilmu Kelautan, Universitas BrawijayaPusat Pemanfaatan Penginderaan Jauh, Lembaga Penerbangan dan Antariksa Nasional, BRINPusat Pemanfaatan Penginderaan Jauh, Lembaga Penerbangan dan Antariksa Nasional, BRINRemote sensing-based research in Indonesia using satellite imagery frequently faces the challenge of cloud coverage due to the tropical country. One spatial data that can be extracted from satellite imagery is bathymetry. However, cloud-covered water bathymetric extraction still needs to be examined. This study aims to understand the ability of Landsat 7 ETM+ acquired on 29 July 2013, and Landsat 8, acquired on 24 July 2020, as the representative of non-cloudy image compared to Landsat 8, acquired on 9 August 2020, as the cloudy image. Stumpf algorithm was applied, including a statistical approach of linear regression analysis with in-situ data measurement from Single Beam Echo-Sounder (SBES) to derive the absolute bathymetric map with several classes of depth ranging from 0 – 2 m up to 10 m. To assess the accuracy, RMSE and confusion matrix was used. The result shows that Landsat 7 ETM+ yields the highest R2 with 0,52, while the lowest total RMSE (8,167 m) and highest overall accuracy of about 69% from the confusion matrix was achieved by the cloudy image of Landsat 8. Nevertheless, the highest absolute depth value yield by Landsat 8 non-cloudy image with 16,1 m. This research confirms that the highest R2 value does not always produce the best model, but it is still promised to be used. Furthermore, the quality of the imagery based on its percentage of cloud coverage is affecting the resulted model.https://ejurnal.ung.ac.id/index.php/jgeosrev/article/view/13886bathymetrylandsatmenjanganstumpf algorithm |
| spellingShingle | Gerardus David Ady Purnama Bayuaji Seftiawan Samsu Rijal Kuncoro Teguh Setiawan Kholifatul Aziz Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra Landsat Jambura Geoscience Review bathymetry landsat menjangan stumpf algorithm |
| title | Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra Landsat |
| title_full | Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra Landsat |
| title_fullStr | Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra Landsat |
| title_full_unstemmed | Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra Landsat |
| title_short | Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra Landsat |
| title_sort | deteksi batimetri perairan dangkal di pulau menjangan provinsi bali menggunakan citra landsat |
| topic | bathymetry landsat menjangan stumpf algorithm |
| url | https://ejurnal.ung.ac.id/index.php/jgeosrev/article/view/13886 |
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