APLIKASI GOOGLE EARTH ENGINE UNTUK KLASIFIKASI HABITAT BENTIK PESISIR NONGSA BATAM MENGGUNAKAN ALGORITMA RANDOM FOREST
Abstract
This study aims to map benthic habitats in the coastal area of Nongsa, Batam, using Sentinel-2A satellite imagery processed using the Random Forest (RF) algorithm on the Google Earth Engine (GEE) platform. The study area includes Teluk Mata Ikan, Tanjung Bemban, and Batu Besar, Nongsa District, Batam City, Kepulauan Riau Province. Field data were obtained through snorkeling surveys and underwater photo documentation in 16-18 August 2024. The four main habitat classes that were successfully identified include coral, sand, seagrass, and rubble (dead coral fragments). The classification results show the dominance of non-living substrates in the form of sand and rubble in most of the study area, while seagrass and coral are distributed in a limited area. Validation of the classification results produced an Overall Accuracy value of 89.90%, indicating a very good level of classification accuracy and suitability. The combination of Sentinel-2A imagery, RF algorithm, and GEE has proven to be effective, efficient, and replicable for mapping tropical benthic habitats spatially and periodically as a basis for sustainable coastal area management.
Keywords
References
Belgiu, M., & Drăguţ, L. 2016. Random forest in remote sensing: A review of applications and future directions. ISPRS Journal of Photogrammetry and Remote Sensing, 114, 24–31.
Breiman, L. 2001. Random forests. Machine Learning, 45(1), 5–32.
Congalton, R. G., & Green, K. 2008. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. CRC Press.
Foody, G. M. 2002. Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80(1), 185–201.
Hossain, M.D., D. Chen. 2019. Segmentation for object-based image analysis (OBIA): a review of algorithms and challenges from remote sensing perspective. ISPRS Journal of Photogrammetry and Remote Sensing, 150, 115-134. Doi: https://doi.org/10.1016/j.isprsjprs.2019.02.009.
Kutser, T., Dekker, A. G., & Skirving, W. 2006. Modelling spectral discrimination of Great Barrier Reef benthic communities by remote sensing instruments. Limnology and Oceanography, 51(1), 168–171.
Laffoley, D., & Grimsditch, G. 2009. The Management of Natural Coastal Carbon Sinks. IUCN.
Lyons, M. B., Roelfsema, C. M., & Phinn, S. R. 2020. Towards understanding temporal and spatial patterns of seagrass change across Australia using Sentinel-2. Remote Sensing of Environment, 238, 111644.
Mastu, L. K., Nababan, B., & Panjaitan, J. P. 2018. Pemetaan habitat bentik berbasis objek menggunakan citra Sentinel-2. Jurnal Ilmu dan Teknologi Kelautan Tropis, 10(2), 381–396.
Mumby, P. J., Green, E. P., Edwards, A. J., & Clark, C. D. 2004. Remote sensing handbook for tropical coastal management. UNESCO Publishing.
Prabowo, N.W., V.P. Siregar, & S.B. Agus. 2018. Klasifikasi habitat bentik berbasis objek dengan algoritma support vector machine dan decision tree menggunakan citra multispectral SPOT-7 di Pulau Harapan dan Pulau Kelapa. Jurnal Ilmu dan Teknologi Kelautan Tropis, 10(1), 123-134.
Roelfsema, C., Kovacs, E., Phinn, S. 2018. Coral reef habitat mapping: A combination of object-based image analysis and ecological modeling. Remote Sensing of Environment, 208, 27–41.
Setiawan, R., Maulana, A., & Wahyudi, A. 2021. Monitoring habitat bentik pesisir berbasis data satelit. Jurnal Kelautan Tropis, 26(1), 55–63.
Siregar, V.P., S.B. Agus, A. Sunuddin, T. Subarno, & N.N. Azizah. 2020. Analisis perubahan habitat dasar perairan dangkal menggunakan citra satelit resolusi tinggi di Karang Lebar, Kepulauan Seribu. Jurnal Ilmu dan Teknologi Kelautan Tropis, 12(1), 37-51.
Tomascik, T., Mah, A. J., Nontji, A., & Moosa, M. K. 1997. The Ecology of the Indonesian Seas. Periplus Editions.
Traganos, D., & Reinartz, P. 2017. Mapping Mediterranean seagrass with Sentinel-2 imagery. Marine Pollution Bulletin, 134, 197–209.
Utama, P.W., V.P. Siregar, & B. Nababan. 2023. Klasifikasi habitat dasar berbasis objek di perairan dangkal karang lebar dan pulang lancing. Jurnal Ilmu dan Teknologi Kelautan Tropis, 15(2): 167-184. Doi: https://doi.org/10.29244/jitkt.v15i2.36036
Wahidin, N., V.P. Siregar, B. Nababan, I. Jaya, & S. Wouthuyzen. 2015. Object-based image analysis for coral reef benthic habitat mapping with several classification algorithms. Procedia Environmental Sciences, 24: 222-227.
DOI: http://dx.doi.org/10.33512/jpk.v15i1.33372
Refbacks
- There are currently no refbacks.