CLASSIFICATION OF MANGROVE ECOSYSTEM AREA IN PANTAI BAHAGIA VILLAGE, MUARA GEMBONG, BEKASI REGENCY, USING SENTINEL IMAGERY WITH NORMALIZED DIFFERENCE VEGETATION INDEX METHOD

Bayu Pamungkas, Rahmat Kurnia, Etty Riani, Taryono

Abstract

Mangrove ecosystems are one type of coastal resources that has benefits in physical, biological, and economic wise. Mangrove ecosystems in Muara Gembong are ecosystems that are included in the category of protected forest. This research aims to estimate the area of mangrove forests and classify its canopy cover. The method used in this study is the Normalized Difference Vegetation Index (NDVI) and using sentinel imagery (with a spatial resolution of 10 m). The canopy cover classification applied in this study refers to the Indonesian Ministry of Forestry standards. Canopy cover data was validated with a densiometer to estimate the percentage of mangrove canopy cover. The results showed that the area of mangrove forests reached 301.83 ha with a high-density level or a tight cover class reaching 59.31% or 179.02 ha. The area of mangroves in Pantai Bahagia Village, Bekasi Regency, has increased from the last few years due to rehabilitation actions taken by several local communities.

References

Ahmad, D.N. 2017. Penyuluhan dan pelatihan upaya pencegahan abrasi pantai pada masyarakat Muara Gembong Bekasi. J. Pengabdian Kepada Masyarakat, 1(2): 90-97. http://doi.org/10.20956/pa.v1i2.2413
Andana, E.K. 2015. Pengembangan data citra satelit landsat-8 untuk pemetaan area tanaman hortikultura dengan berbagai metode algoritma indeks vegetasi (Studi Kasus: Kabupaten Malang dan sekitarnya). Prosiding Seminar Nasional Manajemen Teknologi XXII, Surabaya, Indonesia, 24 Januari 2015. 1501-1510 pp.
Ardiansyah, D.A. & I. Buchori. 2014. Pemanfaatan citra satelit untuk penentuan lahan kritis mangrove di Kecamatan Tugu, Kota Semarang. J. of Geomatics and Planning, 1(1): 1-12. https://doi.org/10.14710/geoplanning.1.1.1-12
Arhatin, R.E. & P.I. Wahyuningrum. 2013. Algoritma indeks vegetasi mangrove menggunakan satelit LANDSAT ETM+ (Vegetation Index Algorithm for Mangrove Derived from Landsat ETM+). Buletin PSP, 21(2): 215-227. http://journal.ipb.ac.id/index.php/bulpsp/article/view/25293
Chuvieco, E. & A. Heute. 2009. Fundamentals of Satellite Remote Sensing. CRC Press. 418 p.
Dafikri, M., Yunasfi, & Z.A. Harahap. 2016. Analisis vegetasi dan pola sebaran salinitas di ekosistem mangrove Percut Sei Tuan Kabupaten Deli Serdang Sumatera Utara. J. Aquacoastmarine, 12(2): 1-14. https://www.scribd.com/document/388847218/13922-33851-1-SM-pdf
Departemen Kehutanan. 2005. Pedoman Inventarisasi dan Identifikasi Lahan Kritis Mangrove. Direktorat Jenderal Rehabilitasi Lahan dan Perhutanan Sosial Departemen Kehutanan. Jakarta. 14 p.
Donato, D.C., J.B. Kauffman, D. Murdiyarso, S. Kurnianto, M. Stidham, & M. Kanninen. 2011. Mangroves among the most carbon-rich forests in the tropics. J. Nature geoscience. 4(5): 293-297. https://doi.org/10.1038/ngeo1123
Frananda, H., H. Hartono, & R.H. Jatmiko. 2015. Komparasi indeks vegetasi untuk estimasi stok karbon hutan mangrove kawasan segoro anak pada kawasan Taman Nasional Alas Purwo Banyuwangi, Jawa Timur. J. Globë, 17(2): 113-123. https://jurnal.big.go.id/index.php/GL/article/download/222/219.pdf
Green, E.P., P.J. Mumby, A.J. Edward, C.D. Clarck, & A.C. Ellis. 1997. Estimating leaf aera index of mangroves from satellite data. J. of Aquatic Botany. 58(9): 11-19. https://doi.org/10.1016/S0304-3770(97)00013-2
Kamal, S., J. Warnken, M. Bakhtiyari, & S.Y. Lee. 2017. Sediment distribution in shallow estuaries at fine scale: in situ evidence of 3D structural complexity effects by mangrove pneumatophores. J. Hydrobiologia, 803: 121-32. https://doi.org/10.1007/s10750-017-3178-3
Kauffman, J.B. & D.C. Donato. 2012. Protocols for the measurement, monitoring and reporting of structure, biomass, and carbon stocks in mangrove forests. CIFOR. Bogor. 50 p.
Kitamura, S., C. Anwar, A. Chaniago, & S. Baba. 1997. Handbook of Mangroves in Indonesia: Bali & Lombok. International Society for Mangrove Ecosystems. ISME. Bali. 119 p.
Kusmana, C. & D.R.P. Ningrum. 2016. Tipologi dan kondisi vegetasi kawasan mangrove Bulaksetra Kabupaten Pangandaran Provinsi Jawa Barat. J. Silvikultur Tropica, 7(2): 137-145. https://jurnal.ipb.ac.id/index.php/jsilvik/article/view/13317.pdf
Landeros, V.L., F. Flores-de-Santiago, J.M. Kovacs, & F. Flores-Verdugo. 2018. An assessment of commonly employed satellite-based remote sensors for mapping mangrove species in Mexico using an NDVI-based classification scheme. J. Environmental monitoring and assessment, 190(1): 23. https://doi.org/10.1007/s10661-017-6399-z
Lee, S.Y. 2016. From blue to black: anthropogenic forcing of carbon and nitrogen influx to mangrove-lined estuaries in the South China Sea. J. Marine pollution bulletin, 109(2): 682-690. https://doi.org/10.1016/j.marpolbul.2016.01.008
Majesty, K.I., M. Karuniasa, & H. Herdiansyah. 2018. The strategy for the community participation development in the management of mangrove forest ecosystem in Muara Gembong District, West Java. Proceedings The 2nd Annual Conference of Engineering and Implementation on Vocational Education, Sumatra Utara, Indionesia, 3 November 2018. 1-8 pp. https://doi.org/10.4108/eai.3-11-2018.2285893
Marsudi, B., O. Satjapradja, & M.L. Salampessy. 2018. Komposisi jenis pohon dan struktur tegakan hutan mangrove di Desa Pantai Bahagia, Kecamatan Muara Gembong, Kabupaten Bekasi, Provinsi Jawa Barat. J. Belantara, 1(2): 115-122. https://doi.org/10.29303/jbl.v1i2.87
Meneses, C.L. 2011. NDVI as indicator of degradation. 238th Edition. Unasylva. 39 p.
Muhsoni, F.F, Sambah A.B., M. Mahmudi, & D.G.R. Wiadnya. Comparison of different vegetation indices for assessing mangrove density using sentinel-2 imagery. J. Geomate, 14(45): 42-51. https://doi.org/10.21660/2018.45.7177
Oktaviani, S., Yonvitner, & Z. Imran. 2019. Daya dukung optimum pola tata guna lahan pesisir di Muara Gembong, Kabupaten Bekasi. J. Ilmu dan Teknologi Kelautan Tropis, 11(1): 75-87. https://doi.org/10.29244/jitkt.v11i1.21600
Pattanaik, C. & S.N. Prasad. 2011. Assessment of aquaculture impact on mangroves of Mahanadi delta (Orissa), East coast of India using remote sensing and GIS. J. Ocean & Coastal Management, 54(11): 789-795. https://doi.org/10.1016/j.ocecoaman.2011.07.013
Philiani, I., L. Saputra, L. Harvianto, & A.A. Muzak. 2016. Pemetaan vegetasi hutan mangrove menggunakan metode Normalized Difference Vegetation Index (NDVI) di Desa Arakan, Minahasa Selatan, Sulawesi Utara. Surya Octagon Interdisciplinary. J. of Technology, 2(1): 211-222. https://doi.org/10.31219/osf.io/c8k6j
Rouse, J.W., R.H. Haas, J.A. Schell, & D.W. Deering. 1973. Monitoring vegetation systems in the Great Plains with ERTS. (in): Rouse JW, Haas RH, Schell JA, Deering DW. Third ERTS Symposium; 10-14 Desember 1973; Washington (US): 309-317 pp.
Sari, S.P. & D. Rosalina. 2016. Mapping and monitoring of mangrove density changes on tin mining area. J. Procedia Environmental Sciences, 33: 436-442. https://doi.org/10.1016/j.proenv.2016.03.094
Suwargana, N. 2008. Analisis perubahan hutan mangrove menggunakan data pengindraan jauh di Pantai Bahagia, Muara Gembong, Bekasi. J. Pengindraan Jauh dan Pengolahan Citra Digital, 5(1): 64-74. https://doi.org/10.15578/segara.v15i2.7461
Tian, J., L. Wang, X. Li, H. Gong, C. Shi, R. Zhong, & X. Liu. 2017. Comparison of UAV and WorldView-2 imagery for mapping leaf area index of mangrove forest. International J. Appl Earth Obs Geoinformation, 61(1): 22-31. https://doi.org/10.1016/j.jag.2017.05.002
Walpole, R.E. 1992. Introduction to Statistics. Third edition. (Translated by) Sumantri B. Gramedia Pustaka Utama. 516 p.
Winarso, G. & A.D. Purwanto. 2014. Pendekatan baru indeks kerusakan mangrove menggunakan data peng-indraan jauh. deteksi parameter geobiofisik dan diseminasi peng-indraan jauh. Di dalam: Budhiman S, Soleh M, Emiyati, Teguh K, Sirin DNS. Prosiding Seminar Nasional Pengindraan Jauh, Bogor, 21 April 2014. 368-379 pp.

Authors

Bayu Pamungkas
Pamungkas315031@gmail.com (Primary Contact)
Rahmat Kurnia
Etty Riani
Taryono
PamungkasB., KurniaR., RianiE., & Taryono. (2020). CLASSIFICATION OF MANGROVE ECOSYSTEM AREA IN PANTAI BAHAGIA VILLAGE, MUARA GEMBONG, BEKASI REGENCY, USING SENTINEL IMAGERY WITH NORMALIZED DIFFERENCE VEGETATION INDEX METHOD. Jurnal Ilmu Dan Teknologi Kelautan Tropis, 12(3), 821-831. https://doi.org/10.29244/jitkt.v12i3.32241

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