Mapping Shallow Water Benthic Habitats Using High Resolution Multispectral UAV Data: A Case Study of Panggang Island
Abstract
Full text article
References
Belfiore, S., Cicin-Sain, B., & Ehler, C.N. (2004). Incorporating marine protected areas into integrated coastal and ocean management : principles and guidelines. Gland, Switzerland: IUCN.
Cervantes, J., Garcia-Lamont, F., Rodríguez-Mazahua, L., & Lopez, A. (2020). A comprehensive survey on support vector machine classification: Applications, challenges and trends. Neurocomputing, 408, 189-215. https://doi.org/10.1016/j.neucom.2019.10.118 DOI: https://doi.org/10.1016/j.neucom.2019.10.118
Elma, E., Gaulton, R., Chudley, T.R., Scott, C.L., East, H.K., Westoby, H., & Fitzsimmons, C. (2024). Evaluating UAV-based multispectral imagery for mapping an intertidal seagrass environment. Aquat. Conserv. Mar. Freshw. Ecosyst, 34(8), 1-14. https://doi.org/10.1002/aqc.4230 DOI: https://doi.org/10.1002/aqc.4230
Feng, C., Ye, G., Jiangning, Z., Jian, Z., Jiang, Q., He, L., Zhang, Y., & Xu, Z. (2023). Sustainably developing global blue carbon for climate change mitigation and economic benefits through international cooperation. Nat Commun., 14(1), 1-10. https://doi.org/10.1038/S41467-023-41870-X DOI: https://doi.org/10.1038/s41467-023-41870-x
Gohari, A., Ahmad, A.B., Rabiu, L., Rahim, R.B.A., Supa’At, A.S.M., Elamin, N.I.M., Gismalla, M.S.M., Al-Dharrab, S.I., Rashid, R.A., Nawawi, S.W., et al. (2024). A systematic review of the uav technology usage in ASEAN. IEEE Open J. Veh. Technol, 5(June), 1036-1058. https://doi.org/10.1109/OJVT.2024.3436065 DOI: https://doi.org/10.1109/OJVT.2024.3436065
Gunathilaka, M.D.K.L., & Fernando, S.L.J.. (2022). Accuracy assessment of unsupervised land use and land cover classification using remote sensing and geographical information systems. Int. J. Environ. Eng. Educ., 4(3), 76-82. https://doi.org/10.55151/ijeedu.v4i3.73 DOI: https://doi.org/10.55151/ijeedu.v4i3.73
Hamidah, M., Pasaribu, R.A., & Aditama, F.A. (2021). Benthic habitat mapping using Object-Based Image Analysis (OBIA) on Tidung Island, Kepulauan Seribu, DKI Jakarta. IOP Conf. Ser. Earth Environ. Sci., 944(1). https://doi.org/10.1088/1755-1315/944/1/012035 DOI: https://doi.org/10.1088/1755-1315/944/1/012035
Hamuna, B., Pujiyati, S., Gaol, J.L., & Hestirianoto, T. (2024). Classification and prediction of benthic habitat based on scientific echosounder data: application of machine learning algorithms. Appl. Comput. Sci., 20(4), 100-116. https://doi.org/10.35784/acs-2024-42 DOI: https://doi.org/10.35784/acs-2024-42
Joyce, K.E., Fickas, K.C., & Kalamandeen, M. (2023). The unique value proposition for using drones to map coastal ecosystems. Cambridge Prism. Coast. Futur. 1. https://doi.org/10.35784/acs-2024-42 DOI: https://doi.org/10.1017/cft.2022.7
Kurniawati, E., Siregar, V., & Nurjaya, I.W. (2020). Classification of shallow water habitat based on object using Worldview 2 and Sentinel 2B images in Kepulauan Seribu waters. Ilmu dan Teknol. Kelaut. Trop., 12(2), 421-435. https://doi.org/10.29244/jitkt.v12i2.26089 DOI: https://doi.org/10.29244/jitkt.v12i2.26089
Lillesand, T.M., Kiefer, R.W., & Chipman, J.W. (2015). Remote sensing and image interpretation (7th ed.). Hoboken, New Jersey: John Wiley & Sons. https://books.google.com/books/about/Remote_Sensing_and_Image_Interpretation.html?id=AFHDCAAAQBAJ
Mansor, N.S., Awang, H., Malami, S.T.S., Zolkafli, A., Taiye, M.A., & Maulana, H. (2024). Support Vector Machine for Satellite Images Classification Using Radial Basis Function Kernel Method. Commun. Comput. Inf. Sci., 2001, 301-312. https://doi.org/10.1007/978-981-99-9589-9_23 DOI: https://doi.org/10.1007/978-981-99-9589-9_23
Mohamed, H., Nadaoka, K., & Nakamura, T. (2020). Semiautomated mapping of benthic habitats and seagrass species using a convolutional neural network framework in shallow water environments. Remote Sens., 12(23), 1-18. https://doi.org/10.3390/rs12234002 DOI: https://doi.org/10.3390/rs12234002
Prabowo, N.W., Siregar, V.P., & Agus, S.B. (2018). Classification of benthic habitat based on object with support vector machines and decision tree algorithm using Spot-7 Multispectral Imagery in Harapan and Kelapa Island. J. Ilmu dan Teknol. Kelaut. Trop., 10(1), 123-134. https://doi.org/10.29244/jitkt.v10i1.21670v DOI: https://doi.org/10.29244/jitkt.v10i1.21670
Prentice, R.M., Peciña, M.V., Ward, R.D., Bergamo, T.F., Joyce, C.B., & Sepp, K. (2021). Machine learning classification and accuracy assessment from high-resolution images of coastal wetlands. Remote Sens., 13(18), 1-27. https://doi.org/10.3390/rs13183669 DOI: https://doi.org/10.3390/rs13183669
Roelfsema, C., Kovacs, E., Ortiz, J.C., Wolff, N.H., Callaghan, D., Wettle, M., Ronan, M., Hamylton, S.M., Mumby, P.J., & Phinn, S. (2018). Coral reef habitat mapping: A combination of object-based image analysis and ecological modelling. Remote Sens. Environ., 208, 27-41. https://doi.org/10.1016/j.rse.2018.02.005 DOI: https://doi.org/10.1016/j.rse.2018.02.005
Sugara, A., Suryanita, A., Maulana, A., Anggoro, A., & Siregar, V.P. (2023). Aplikasi teknologi drone sebagai pelengkap data survei lapang untuk pemetaan ekosistem terumbu karang menggunakan citra Worldview-2. J. Mar. Aquat. Sci., 8(2), 202-209. https://doi.org/10.24843/jmas.2022.v08.i02.p05 DOI: https://doi.org/10.24843/jmas.2022.v08.i02.p05
Utama, P.W., Siregar, V., & Nababan, B. (2023). Klasifikasi habitat dasar berbasis objek di perairan dangkal Karang Lebar dan Pulau Lancang. J. Ilmu dan Teknol. Kelaut. Trop., 15(2), 167-184. https://doi.org/10.29244/jitkt.v15i2.36036 DOI: https://doi.org/10.29244/jitkt.v15i2.36036
Ventura, D., Grosso, L., Pensa, D., Casoli, E., Mancini, G., Valente, T., Scardi, M., & Rakaj, A. (2023). Coastal benthic habitat mapping and monitoring by integrating aerial and water surface low-cost drones. Front. Mar. Sci., 9, 1-15. https://doi.org/10.3389/fmars.2022.1096594 DOI: https://doi.org/10.3389/fmars.2022.1096594
Authors
Copyright (c) 2026 Devi Aliyah Sari S.Si, Prof. Dr.Ir. Vincentius P. Siregar, DEA, Dr. Syamsul Bahri Agus, S.Pi, M.Si

This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Jurnal Ilmu dan Teknologi Kelautan Tropis i is an open-access journal, meaning that all content is freely available without charge to the user or their institution. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles in this journal without needing to request prior permission from the publisher or the author.
All articles published by Jurnal Ilmu dan Teknologi Kelautan Tropis are licensed under the Creative Commons Attribution 4.0 International License. This allows for unrestricted use, distribution, and reproduction in any medium, provided proper credit is given to the original authors.
Authors submitting manuscripts should understand and agree that the copyright of published manuscripts is retained by the authors. Copyright encompasses the exclusive rights of authors to reproduce, distribute, and sell any part of the journal articles in all forms and media. Reproduction of any part of this journal, its storage in databases, and its transmission by any form or media is allowed without written permission from Jurnal Ilmu dan Teknologi Kelautan Tropis.
