Monitoring Deforestasi Mangrove di Kabupaten Belitung Timur Berbasis Citra Penginderaan Jauh Sentinel 2 dan Klasifikasi Random Forest
DOI:
https://doi.org/10.32522/ujht.v9i1.18329Keywords:
Alih fungsi, Deforestasi, Mangrove, Pesisir, Sentinel 2.Abstract
Mangrove merupakan vegetasi yang akarnya menjalar dipermukaan, dan berada di muara sungai, dan pesisir. Hutan mangrove sangat penting keberadaannya karena merupakan sistem di dalam menyeimbangkan ekosistem di pesisir, dan muara sungai. Deforestasi hutan mangrove dari akibat alih fungsi lahan pada vegetasi mangrove menjadi ancaman bagi keberlanjutan kehidupan di wilayah pesisir, dan muara. Keberadaan vegetasi mangrove yang penting bagi Kabupaten Belitung Timur untuk menjaga dari abrasi, dan habitat satwa. Aktivitas manusia menyebabkan alih fungsinya hutan mangrove sehingga menimbulkan deforestasi. Aktivitas manusia menyebabkan alih fungsi berbentuk aktivitas pertambangan, dan budidaya tambak udang. Luasan hutan mangrove yang semakin berkurang dari aktivitas tersebut menyebabkan deforestasi. Hal ini akan menjadi ancaman kepunahan yang akan terjadi di masa depan. Monitoring mangrove sangat penting karena untuk melihat deforestasi luasan hutan mangrove yang berubah dari tahun 2017 ke tahun 2024. Data Sentinel 2 sangat berperan penting untuk data yang diolah untuk melihat keberadaan, dan luasan alih fungsi. Dengan menggunakan rumus Mangrove Vegetation Index (MVI) untuk mengetahui area vegetasi mangrove. Pengolahan data menggunakan cara Random Forest untuk menganalisis tingkat lanjut terhadap perubahan alih fungsi mangrove. Sehingga memudahkan dalam pemetaan terjadinya alih fungsi mangrove. Dilakukan juga survei lapangan (ground check) untuk validasi pada Area of Interest (AOI) yang dikaji.References
Aliviyanti, D., & Isdianto, A. (2020). Komposisi dan Kerapatan Mangrove Kawasan Konservasi Taman Wisata Perairan Gugusan Pulau- Pulau Momparang. Indonesian Journal of Conservation, 9(2), 63–67. https://doi.org/10.15294/ijc.v9i2.26547
Alongi, D. M. (2002). Present state and future of the world’s mangrove forests. Environmental Conservation, 29(3), 331–349. https://doi.org/10.1017/S0376892902000231
Arifanti, V. B., Novita, N., Subarno, & Tosiani, A. (2021). Mangrove deforestation and CO2emissions in Indonesia. IOP Conference Series: Earth and Environmental Science, 874(1), 1–9. https://doi.org/10.1088/1755-1315/874/1/012006
Astikasari, L., Indriyani, S., Muryanto, B. S., Al Madani, A. R., Muhammad, F., Putri, A., Hartanti, A. N., Afifah, R. N., Zuaini, P. A. K., Rezapratama, M. S., Negari, S. I. T., Sunarto, S., Kususmaningrum, L., Kurniawati, I., Budiharta, S., Flores, A. B., & Setyawan, A. D. (2023). Analysis of ecotourism development as a mangrove conservation effort in Pasir Kadilangu and Jembatan Api-Api, Kulon Progo, Yogyakarta, Indonesia. Indo Pacific Journal of Ocean Life, 7(2), 125–132. https://doi.org/10.13057/oceanlife/o070201
Baloloy, A. B., Blanco, A. C., Raymund Rhommel, R. R. C., & Nadaoka, K. (2020). Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 95–117. https://doi.org/10.1016/j.isprsjprs.2020.06.001
Cahyaningsih, A. P., Deanova, A. K., Pristiawati, C. M., Ulumuddin, Y. I., Kusumaningrum, L., & Setyawan, A. D. (2022). Review: Causes and impacts of anthropogenic activities on mangrove deforestation and degradation in Indonesia. International Journal of Bonorowo Wetlands, 12(1), 12–22. https://doi.org/10.13057/bonorowo/w120102
Chatting, M., Al-Maslamani, I., Walton, M., Skov, M. W., Kennedy, H., Husrevoglu, Y. S., & Le Vay, L. (2022). Future Mangrove Carbon Storage Under Climate Change and Deforestation. Frontiers in Marine Science, 9, 1–14. https://doi.org/10.3389/fmars.2022.781876
Cipta, I. M., Sobarman, F. A., Sanjaya, H., & Darminto, M. R. (2021). Analysis of Mangrove Forest Change from Multioral Landsat Imagery Using Google Earth Engine Application : (Case Study: Belitung Archipelago 1990 - 2020). 2021 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology, AGERS 2021 - Proceeding. https://doi.org/10.1109/AGERS53903.2021.9617354
Donato, D. C., Kauffman, J. B., Murdiyarso, D., Kurnianto, S., Stidham, M., & Kanninen, M. (2011). Mangroves among the most carbon-rich forests in the tropics. Nature Geoscience, 4(5), 293–297. https://doi.org/10.1038/ngeo1123
Faizal, A., Mutmainna, N., Amran, M. A., Saru, A., Amri, K., & Nessa, M. N. (2023). Application of NDVI Transformation on Sentinel 2A Imagery for mapping mangrove conditions in Makassar City. Akuatikisle: Jurnal Akuakultur, Pesisir Dan Pulau-Pulau Kecil, 7(1), 59–66. https://doi.org/10.29239/j.akuatikisle.7.1.59-66
FAO. (2007). The World’s Mangrove 1980-2004.
Ghorbanian, A., Ahmadi, S. A., Amani, M., Mohammadzadeh, A., & Jamali, S. (2022). Application of Artificial Neural Networks for Mangrove Mapping Using Multi-Temporal and Multi-Source Remote Sensing Imagery. Water (Switzerland), 14(2), 1–20. https://doi.org/10.3390/w14020244
Henri, Farhaby, A. M., Supratman, O., Adi, W., & Febrianto, S. (2023). Assessment of species diversity, biomass and carbon stock of mangrove forests on belitung island, indonesia. Biodiversitas, 24(12), 6761–6769. https://doi.org/10.13057/biodiv/d250103
Juwita, E., Soewardi, K., & Yonvitner. (2015). Kondisi Habitat dan Ekosistem Mangrove Kecamatan Simpang Pesak, Belitung Timur Untuk Pengembangan Tambak Udang. Manusia Dan Lingkungan, 22(1), 59–65.
Kamal, M., Farda, N. M., Jamaluddin, I., Parela, A., Wikantika, K., Prasetyo, L. B., & Irawan, B. (2020). A preliminary study on machine learning and google earth engine for mangrove mapping. IOP Conference Series: Earth and Environmental Science, 500(1), 1–8. https://doi.org/10.1088/1755-1315/500/1/012038
Kongwongjan, J., Suwanprasit, C., & Thongchumnum, P. (2013). Comparison of vegetation indices for mangrove mapping using THEOS data. Proceedings of the Asia-Pacific Advanced Network, 33(0), 56. https://doi.org/10.7125/apan.33.6
Kuenzer, C., Bluemel, A., Gebhardt, S., Quoc, T. V., & Dech, S. (2011). Remote sensing of mangrove ecosystems: A review. In Remote Sensing (Vol. 3, Issue 5, pp. 878–928). https://doi.org/10.3390/rs3050878
Libriyono, A., Kusratmoko, E., & Kertopermono, A. P. (2018). Spatial modelling of shoreline change to coastal disaster management in Jakarta Bay. AIP Conference Proceedings, 1987, 1–7. https://doi.org/10.1063/1.5047306
Murdiyarso, D., Purbopuspito, J., Kauffman, J. B., Warren, M. W., Sasmito, S. D., Donato, D. C., Manuri, S., Krisnawati, H., Taberima, S., & Kurnianto, S. (2015). The potential of Indonesian mangrove forests for global climate change mitigation. Nature Climate Change, 5(12), 1089–1092. https://doi.org/10.1038/nclimate2734
Nandika, M. R., Ananda, A. A. M., Suardana, P., & Anggraini, N. (2023). Pemetaan Mangrove Menggunakan Algoritma Multivariate Random Forest. Majalah Ilmiah Globè, 25, 21–30.
Oktavia Dina, Pratiwi Dwi Santri, Kamaludin Nuraniya Nadia, Widiawaty Agung Millary, & Dede Moh. (2024). Dynamics of Land use, and Land cover in the Belitung Island, Indonesia. Heliyon, 10, 1–11.
Purnamasayangsukasih, R. P., Norizah, K., Ismail, A. A. M., & Shamsudin, I. (2016). A review of uses of satellite imagery in monitoring mangrove forests. IOP Conference Series: Earth and Environmental Science, 37(1), 1–14. https://doi.org/10.1088/1755-1315/37/1/012034
Randiansyah, R., Henri, H., & Farhaby, A. M. (2023). Analisis Produksi Serasah Mangrove pada Hutan Mangrove Desa Kurau Timur, Kabupaten Bangka Tengah, Bangka Belitung. Jurnal Sains Teknologi & Lingkungan, 9(3), 491–501. https://doi.org/10.29303/jstl.v9i3.439
Rendana, M., Razi Idris, W. M., Abdul Rahim, S., Ghassan Abdo, H., Almohamad, H., Abdullah Al Dughairi, A., & Albanai, J. A. (2023). Effects of the built-up index and land surface temperature on the mangrove area change along the southern Sumatra coast. Forest Science and Technology, 19(3), 179–189. https://doi.org/10.1080/21580103.2023.2220576
Richards, D. R., & Friess, D. A. (2016). Rates and drivers of mangrove deforestation in Southeast Asia, 2000-2012. Proceedings of the National Academy of Sciences of the United States of America, 113(2), 344–349. https://doi.org/10.1073/pnas.1510272113
Rosmasita, Siregar, V. P., Agus, S. B., & Jhonnerie, R. (2019). An object-based classification of mangrove land cover using Support Vector Machine Algorithm. IOP Conference Series: Earth and Environmental Science, 284(1), 1–11. https://doi.org/10.1088/1755-1315/284/1/012024
Schwartz, M. O., Rajah, S. S., Askury ’, A. K., Putthapiban, P., & Djaswadi, S. (1995). The Southeast Asian Tin Belt. Earth-Science Reviews, 38, 95–293.
Sondak, C. F. A., Kaligis, E. Y., & Bara, R. A. (2019). Economic valuation of Lansa Mangrove forest, north Sulawesi, Indonesia. Biodiversitas, 20(4), 978–986. https://doi.org/10.13057/biodiv/d200407
Tsalisa Haiba, A., Deya Safitri, F., Ageng Munawwaroh, G., Donny Sudrajat, M., Novebri Putri, R., Purwadinata, F., Milla, M., Jales, W. W., Ramadhani Said, P., & Eka Mardyansyah Simbolon, M. (2023). Environmental preservation through post-tin mining land reclamation in Sukamandi Village, East Belitung. 8(9), 1467–1472. https://doi.org/10.31603/ce.166
Wang Le, Jia Mingming, Yin Dameng, & Tian Jintan. (2019). A review of remote sensing for mangrove forest: 1956-2018. Remote Sensing of Environment, 231, 1–15. https://doi.org/https://doi.org/10.1016/j.rse.2019.111223


