Mangrove Density Mapping from Landsat 8/9 OLI Imagery in Dompak Island, Indonesia: A Study from 2017 to 2022

Open Access

Issue		BIO Web Conf. Volume 70, 2023 Maritime Continent Fulcrum International Conference (MaCiFIC 2023)


Article Number		01010
Number of page(s)		12
Section		Maritime Science and Technology
DOI		https://doi.org/10.1051/bioconf/20237001010
Published online		06 November 2023

C. M. Duarte, I. J. Losada, I. E. Hendriks, I. Mazarrasa, and N. Marbà, “The role of coastal plant communities for climate change mitigation and adaptation,” Nature Climate Change, 3(11), pp. 961–968 (2013). [CrossRef] [Google Scholar]
F. Sahami, “Penilaian Kondisi Mangrove Berdasarkan Tingkat Kerapatan Jenis,” Jurnal Ilmiah Perikanan dan Kelautan. Volume 6 (2), pp. 33–40 (2018). [Google Scholar]
R. M. Brinkman, “Wave attenuation in mangrove forests: an investigation through field and theoretical studies”: James Cook University (2006). [Google Scholar]
C. Tan et al., “Remotely Assessing Fraction of Photosynthetically Active Radiation (FPAR) for Wheat Canopies Based on Hyperspectral Vegetation Indexes,” Front. Plant Sci., 9, pp. 776 (2018). [Google Scholar]
C. J. Tucker, “Red and Photographic Infrared l,lnear Combinations for Monitoring Vegetation,” pp. 24. [Google Scholar]
https://reverb.echo.nasa.gov. [Google Scholar]
A. Hardianto, P. U. Dewi, T. Feriansyah, N. F. S. Sari, and N.S. Rifiana, “Pemanfaatan Citra Landsat 8 Dalam Mengidentifikasi Nilai Indeks Kerapatan Vegetasi (NDVI) Tahun 2013 dan 2019 (Area Studi: Kota Bandar Lampung),” Jurnal Geosains dan Remote Sensing (JGRS), Vol 2 (1), pp. 8–15 (2021). [CrossRef] [Google Scholar]
P. Coppin, I. Jonckheere, K. Nackaerts, B. Muys, & E. Lambin, “Digital change detection methods in ecosystem monitoring : A review,” International Journal of Remote Sensing, 25(9), pp. 1565–1596 (2004). [CrossRef] [Google Scholar]
N. Pettorelli, J. O. Vik, A. Mysterud, J. M. Gaillard, C. J. Tucker, and N. C. Stenseth, “Satellite remote sensing for applied ecologists: Opportunities and challenges,” Journal of Applied Ecology, 51(4), pp. 839–848 (2014). [CrossRef] [Google Scholar]
F. Lestari, “Komposisi Jenis dan Sebaran Ekosistem Mangrove di Kawasan Pesisir Kota Tanjungpinang, Kepulauan Riau,”, 4(1), pp. 68–75 (2014). [Google Scholar]
Z. Husin, K. Ismail and Susiana, “Kajian Kesesuaian Jurnal Dinamika Maritim Wisata Mangrove Kawasan Pesisir Dompak Tanjungpinang Kepulauan Riau” Jurnal Elektronik, 1(1), pp. 67–82 (2017). [Google Scholar]
I. Addini, S. N. Azizah, and H. Irawan, “Carbon Stock Analysis in Mangrove Vegetation on Dompak Island, Riau Islands,” Carbon Stock Analysis in Mangrove Vegetation on Dompak Island, Riau Islands. In MaCiFIC 2022: Proceedings of the 2nd Maritime Continent Fulcrum International Conference, MaCiFIC 2022, September 28-October 1, 2022, Tanjungpinang, Indonesia, pp. 188–196 (2023). European Alliance for Innovation https://doi.org/10.4108/eai.28-9-2022.2328376 [Google Scholar]
R. Saputra, J. L. Gaol, and S. B. Agus, “Studi perubahan tutupan lahan berbasis objek (Obia) menggunakan citra satelit di kawasan mangrove, Pulau Dompak, Provinsi Kepulauan Riau,” Jurnal Ilmu dan Teknologi Kelautan Tropis. vol. 13, pp. 39–55 (2021). [Google Scholar]
BPS-Statistics of Tanjungpinang Municipality, “Kota Tanjung Pinang Dalam Angka 2017”: CV. Rizky Mandiri. Tanjungpinang - Kepulauan Riau (2017). [Google Scholar]
BPS-Statistics of Tanjungpinang Municipality, “Kota Tanjung Pinang Dalam Angka 2022”: CV. Rizky Mandiri. Tanjungpinang - Kepulauan Riau (2022). [Google Scholar]
A. Imanuel, N. Efriyeldi, and S. Nasution, “Condition Of Mangrove Forests In Dompak Urban Village Bukit Bestari Sub-District Riau Island Province,” Asian Journal of Aquatic Sciences, Vol 3 (3), pp. 286–296. (2020). [CrossRef] [Google Scholar]
P. K. Dialam, “Tingkat Kerusakan Ekosistem Mangrove Di Pulau Dompak Kepulaua Riau.” (Thesis, UMRAH). (2022). http://repositori.umrah.ac.id/3876/. [Google Scholar]
J. Xue, and B. Su, “Significant Remote Sensing Vegetation Indices : A Review of Developments and Applications,” Journal of Sensors, 2017, pp. 1–17 (2017). [CrossRef] [Google Scholar]
C. Tan et al., “Remotely Assessing Fraction of Photosynthetically Active Radiation (FPAR) for Wheat Canopies Based on Hyperspectral Vegetation Indexes,” Front. Plant Sci., 9, pp. 776 (2018). [Google Scholar]
Y. Ke, et al., “Characteristics of Landsat 8 OLI-derived NDVI by comparison with multiple satellite sensors and in-situ observations,” Remote Sensing of Environment, 1–16 (2015). [Google Scholar]
J. Mallick et al., “Evaluating the NDVI-Rainfall Relationship in Bisha Watershed, Saudi Arabia Using Non-Stationary Modeling Technique,” Atmosphere, 12(5), pp. 593, (2021). DOI: 10.3390/atmos12050593. [CrossRef] [Google Scholar]
N. Simarmata, K. Wikantika, S. Darmawan, T. T. Agnestasia, M. Aldyansyah, R. K. Tohir, Y. Purnama, and C. N. Yewanda, “Evaluation of Multi-temporal Imagery and Vegetation Indices for Mangrove Mapping (Case Study of The East Coast of Lampung),” IOP Conf. Ser.: Earth Environ. Sci. 1083 (012067), pp. 1–11 (2022). [Google Scholar]
J. Lou, G. Xu, Z. Wang, Z. Yang, and S. Ni, “Multi-Year NDVI Values as Indicator of the Relationship between Spatiotemporal Vegetation Dynamics and Environmental Factors in the Qaidam Basin, China,” Remote Sensing, 13 (7), 1240, (2021). [CrossRef] [Google Scholar]
G. M. Gandhi, S. Parthiban, N. Thummalu, and A. Christy, “NDVI: Vegetation Change Detection Using Remote Sensing and Gis - A Case Study of Vellore District,” Procedia Computer Science, 57, pp. 1199–1210 (2015). [CrossRef] [Google Scholar]
Karimah. (2017). Peran Ekosistem Hutan Mangrove Sebagai Habitat Untuk Organisme Laut. Jurnal Biologi Tropis, 2. [Google Scholar]
Suyadi, Naroli, I., & Sitepu, A. B. (2021). KARAKTERISTIK VEGETASI MANGROVE DAN PEMANFAATANNYA: STUDI KASUS. Jurnal Kelautan dan Perikanan Terapan, 37–45. [CrossRef] [Google Scholar]
O. Silitonga, D. Purnama, and E. Nofridiansyah, “Pemetaan Kerapatan Vegetasi Mangrove Di Sisi Tenggara Pulau Enggano Menggunakan Data Citra Satelit,” Jurnal Enggano Vol. 3 (1), pp. 98–111. (2018).: E-ISSN: 2527-5186. P-ISSN:2615-5958. [CrossRef] [Google Scholar]

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