1Manajemen Sumber Daya Perairan, Departemen Perikanan, Fakultas Ilmu Kelautan dan Perikanan, Universitas Hasanuddin, Indonesia
21Manajemen Sumber Daya Perairan, Departemen Perikanan, Fakultas Ilmu Kelautan dan Perikanan, Universitas Hasanuddin, Indonesia
3Departemen Ilmu Kelautan, Fakultas Ilmu Kelautan dan Perikanan, Universitas Hasanuddin, Indonesia
BibTex Citation Data :
@article{JKT16496, author = {Muh Rais and Dwi Inaku and Wilma J.C. Moka and Supriadi Mashoreng and Dewi Yanuarita Satari and Nita Rukminasari}, title = {Estimasi Stok Karbon Padang Lamun menggunakan Citra Spot-7 di Perairan Pulau Kodingarenglompo, Sangkarrang, Kota Makassar}, journal = {Jurnal Kelautan Tropis}, volume = {26}, number = {2}, year = {2023}, keywords = {Stok karbon; Kodingarenglompo; lamun}, abstract = { Seagrass is the most effective ecosystem in absorbing carbon. The ability of seagrasses to absorb CO2 from the atmosphere is better than terrestrial ecosystems. Image processing methods and information regarding potential carbon stocks in seagrass beds can then be used as a basis for managing carbon stocks found in coastal areas and small islands. This study aims to estimate the carbon stock of seagrass beds in the waters of Kodingarenglompo Island using remote sensing technology. This research was conducted from March to August 2020. The stages of the field survey were to identify the percentage of seagrass cover in 62 plot points. Seagrass carbon stocks are known based on seagrass cover percentage data using the regression equation. The estimation of seagrass carbon stocks in the study area is divided into two, namely AGC and BGC. The image processing stage is by using the random forest regression algorithm in mapping seagrass carbon stocks. The results of this research survey revealed six species of seagrass, namely Cymodocea rotundata, Enhalus acoroides, Halodule uninervis, Halophila ovalis, Thalassia hemprichii and Syringodium isoetifolium and were dominated by 2 species of seagrass, namely Thalassia hemprichii and Enhalus acoroides. The results showed that remote sensing can be used to map seagrass carbon stocks. Seagrass carbon stocks can be mapped with a maximum accuracy of 67% (SE=1.96 KgC/Pixel), and 85% (SE=7.86 KgC/Pixel) for AGC and BGC. From this model, the total ecosystem carbon stock in seagrasses in the waters of Kodingarenglompo Island is estimated to be around 178.98 tons of organic carbon with an area of seagrass beds of 81.29 hectares. The availability of seagrass carbon stock maps is very important to provide a better understanding of the spatial and temporal distribution of carbon dynamics. Lamun adalah ekosistem yang paling efektif dalam menyerap karbon. Kemampuan lamun untuk menyerap CO2 dari atmosfer lebih baik dari ekosistem darat. Metode pengolahan citra serta informasi mengenai potensi cadangan karbon pada padang lamun selanjutnya dapat dijadikan sebagai dasar pengelolaan stok karbon yang terdapat di pesisir dan pulau-puau kecil. Penelitian ini bertujuan untuk mengestimasi stok karbon padang lamun di perairan Pulau Kodingarenglompo menggunakan teknologi penginderaan jauh. Penelitian ini dilaksanakan dari bulan Maret sampai Agustus 2020. Tahapan survei lapangan yaitu mengidentifikasi persentase tutupan jenis padang lamun sebanyak 62 plot titik. Stok karbon lamun diketahui berdasarkan data persentase tutupan lamun menggunakan persamaan regresi. Estimasi stok karbon padang lamun pada daerah kajian dibedakan menjadi dua yaitu AGC dan BGC. Tahap pengolahan citra yaitu dengan menggunakan algoritma regresi random forest dalam memetakan stok karbon lamun. Hasil survei penelitian ini mendapatkan enam jenis lamun yaitu Cymodocea rotundata, Enhalus acoroides, Halodule uninervis, Halophila ovalis, Thalassia hemprichii dan Syringodium isoetifolium dan didominasi oleh 2 jenis lamun yaitu Thalassia hemprichii dan Enhalus acoroides. Hasil penelitian menunjukkan bahwa penginderaan jauh dapat digunakan untuk memetakan stok karbon lamun. Stok karbon lamun dapat dipetakan dengan akurasi maksimum 67% (SE=1,96 KgC/Piksel), 85% (SE=7,86 KgC/Piksel) untuk AGC dan BGC. Dari model tersebut, total stok karbon ekosistem pada lamun di perairan Pulau Kodingarenglompo diperkirakan sekitar 178,98 ton karbon organik dengan luas padang lamun yaitu 81,29 hektar. Ketersediaan peta stok karbon lamun sangat penting untuk memberikan pemahaman yang lebih baik tentang sebaran dinamika karbon spasial dan temporal. }, issn = {2528-3111}, pages = {387--398} doi = {10.14710/jkt.v26i2.16496}, url = {https://ejournal2.undip.ac.id/index.php/jkt/article/view/16496} }
Refworks Citation Data :
Seagrass is the most effective ecosystem in absorbing carbon. The ability of seagrasses to absorb CO2 from the atmosphere is better than terrestrial ecosystems. Image processing methods and information regarding potential carbon stocks in seagrass beds can then be used as a basis for managing carbon stocks found in coastal areas and small islands. This study aims to estimate the carbon stock of seagrass beds in the waters of Kodingarenglompo Island using remote sensing technology. This research was conducted from March to August 2020. The stages of the field survey were to identify the percentage of seagrass cover in 62 plot points. Seagrass carbon stocks are known based on seagrass cover percentage data using the regression equation. The estimation of seagrass carbon stocks in the study area is divided into two, namely AGC and BGC. The image processing stage is by using the random forest regression algorithm in mapping seagrass carbon stocks. The results of this research survey revealed six species of seagrass, namely Cymodocea rotundata, Enhalus acoroides, Halodule uninervis, Halophila ovalis, Thalassia hemprichii and Syringodium isoetifolium and were dominated by 2 species of seagrass, namely Thalassia hemprichii and Enhalus acoroides. The results showed that remote sensing can be used to map seagrass carbon stocks. Seagrass carbon stocks can be mapped with a maximum accuracy of 67% (SE=1.96 KgC/Pixel), and 85% (SE=7.86 KgC/Pixel) for AGC and BGC. From this model, the total ecosystem carbon stock in seagrasses in the waters of Kodingarenglompo Island is estimated to be around 178.98 tons of organic carbon with an area of seagrass beds of 81.29 hectares. The availability of seagrass carbon stock maps is very important to provide a better understanding of the spatial and temporal distribution of carbon dynamics.
Lamun adalah ekosistem yang paling efektif dalam menyerap karbon. Kemampuan lamun untuk menyerap CO2 dari atmosfer lebih baik dari ekosistem darat. Metode pengolahan citra serta informasi mengenai potensi cadangan karbon pada padang lamun selanjutnya dapat dijadikan sebagai dasar pengelolaan stok karbon yang terdapat di pesisir dan pulau-puau kecil. Penelitian ini bertujuan untuk mengestimasi stok karbon padang lamun di perairan Pulau Kodingarenglompo menggunakan teknologi penginderaan jauh. Penelitian ini dilaksanakan dari bulan Maret sampai Agustus 2020. Tahapan survei lapangan yaitu mengidentifikasi persentase tutupan jenis padang lamun sebanyak 62 plot titik. Stok karbon lamun diketahui berdasarkan data persentase tutupan lamun menggunakan persamaan regresi. Estimasi stok karbon padang lamun pada daerah kajian dibedakan menjadi dua yaitu AGC dan BGC. Tahap pengolahan citra yaitu dengan menggunakan algoritma regresi random forest dalam memetakan stok karbon lamun. Hasil survei penelitian ini mendapatkan enam jenis lamun yaitu Cymodocea rotundata, Enhalus acoroides, Halodule uninervis, Halophila ovalis, Thalassia hemprichii dan Syringodium isoetifolium dan didominasi oleh 2 jenis lamun yaitu Thalassia hemprichii dan Enhalus acoroides. Hasil penelitian menunjukkan bahwa penginderaan jauh dapat digunakan untuk memetakan stok karbon lamun. Stok karbon lamun dapat dipetakan dengan akurasi maksimum 67% (SE=1,96 KgC/Piksel), 85% (SE=7,86 KgC/Piksel) untuk AGC dan BGC. Dari model tersebut, total stok karbon ekosistem pada lamun di perairan Pulau Kodingarenglompo diperkirakan sekitar 178,98 ton karbon organik dengan luas padang lamun yaitu 81,29 hektar. Ketersediaan peta stok karbon lamun sangat penting untuk memberikan pemahaman yang lebih baik tentang sebaran dinamika karbon spasial dan temporal.
Article Metrics:
Last update:
Upon acceptance for publication, authors agree to transfer the copyright of their article to Jurnal Kelautan Tropis, while retaining the right to reuse their work under the terms of the open license applied.
From the date of publication, the copyright for each article is held by Jurnal Kelautan Tropis. This transfer allows the journal to manage, disseminate, and preserve scholarly content in accordance with international standards and open access best practices.
Although copyright is held by the journal, all published articles are made available under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). Under this license, anyone may:
Copy and redistribute the material in any medium or format
Remix, transform, and build upon the material for any purpose, even commercially
provided that:
Appropriate credit is given to the original author(s) and the source
Indications are made of any changes that were made
Derivative works are distributed under the same license (CC BY-SA 4.0)
While copyright is held by the journal, authors retain important reuse rights. Authors may:
Reuse the published version of their article in future works, including books, compilations, and lectures
Deposit the published version in institutional or subject repositories
Share the article freely, including on personal websites or academic networks
as long as the original publication in Jurnal Kelautan Tropis is cited and the CC BY-SA 4.0 license terms are respected.
Authors must ensure that any third-party content included in the article (e.g., figures, images, datasets) is either original, in the public domain, or licensed for reuse under compatible terms. If specific permissions are required, authors must obtain them prior to submission.
For questions regarding copyright or licensing, please contact the editorial office at: j.kelautantropis@gmail.com
View My Stats
Jurnal Kelautan Tropis is published by Departement of Marine Science, Faculty of Fisheries and Marine Science, Universitas Diponegoro under a Creative Commons Attribution-ShareAlike 4.0 International License.
