EVALUASI TINGKAT AKURASI PEMETAAN HABITAT BENTIK PERAIRAN DANGKAL PADA PERBEDAAN JUMLAH KELAS MENGUNAKAN CITRA SATELIT RESOLUSI TINGGI

Ayub Sugara, Vincentius Paulus Siregar, Syamsul Bahri Agus

Abstract


Pulau Sebaru Besar merupakan salah satu pulau yang terdapat di bagian utara Kepulauan Seribu yang memliki keanekaragaman habitat perairan laut dangkal dengan ketersedian data spasial yang masih sedikit. Penginderaan jauh dengan menggunakan citra resolusi tinggi diitegrasikan dengan data observasi lapang dapat menjadi alternatif sumber informasi terkait habitat bentik perairan dangkal. Penelitian ini bertujuan untuk melakukan klasifikasi habitat bentik perairan dangkal di Pulau Sebaru Besar Kepulauan Seribu menggunakan Citra Worldview-2 dengan penerapan 9 dan 7 kelas serta melakukan uji akurasi hasil klasifikasi. Data Citra Worldview-2 yang digunakan merupakan salah satu citra resolusi tinggi dengan resolusi spasial 1.84 x 1.84 meter2  yang diakuisisi pada 27 Mei 2018. Survei lapang habitat bentik perairan dangkal dilakukan pada tanggal 10 – 12 Mei 2018 dan 09 – 10 Desember 2018 dengan teknik foto kuadrat yang menghasilkan sample sebanyak 159 titik. Persentase tutupan habitat setiap foto kuadrat dianalisis dengan perangkat lunak Coral Point Count with Excel extensions (CPCe). Berdasarkan hasil penelitian akurasi klasifikasi pemetaan habitat bentik perairan dangkal untuk 9 dan 7 kelas dihasilkan akurasi sebesar 63.2% dan 67.5% dengan algoritma Maximum Likelihood Classification (MLC). Habitat bentik perairan laut dangkal dapat dipetakan dengan baik sehingga bisa menjadi masukan basis data informasi untuk pengelola Taman Nasional Kepulauan Seribu (TNKpS) kaitannya dalam usaha monitoring habitat bentik terkhusus terumbu karang dan upaya konservasi habitat perairan laut  dangkal

Keywords


Citra Worldview-2; Habitat Bentik; Pulau Sebaru Besar

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References


Andréfouët, S., Kramer, P., Torres-Pulliza, D., Joyce, K. E., Hochberg, E. J., Garza-Pérez, R., … Muller-Karger, F. E. (2003). Multi-site evaluation of IKONOS data for classification of tropical coral reef environments. Remote Sensing of Environment, 88(1–2), 128–143. https://doi.org/10.1016/j.rse.2003.04.005

Chollett, I., & Mumby, P. J. (2012). Predicting the distribution of Montastraea reefs using wave exposure. Coral Reefs, 31(2), 493–503. https://doi.org/10.1007/s00338-011-0867-7

Collin, A., & Hench, J. L. (2012). Towards deeper measurements of tropical reefscape structure using the WorldVsiew-2 spaceborne sensor. Remote Sensing, 4(5), 1425–1447. https://doi.org/10.3390/rs4051425

Congalton G. Russell and Green Kass. (2009). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. In The Photogrammetric Record (Vol. 25). https://doi.org/10.1111/j.1477-9730.2010.00574_2.x

Digitalglobe. 2009. White Paper – The Benefits of the 8 Spectral Bands of Worlview2.].http://www.digitalglobe.com/downloads/WorldView-2_8 Band_Applications_Whitepaper.pdf

Edmund P. Green, P. J. M., & Clark, A. J. E. and C. D. (2000). Remote Sensing Handbook for Tropical Coastal Management. United Nations Educational, Scientific and Cultural Organization 7, place de Fontenoy, 75352 Paris 07 SP.

English, S., Wilkinson, C., & Baker, V. (1997). Survey manual for tropical marine resources. Second edition. Survey Manual for Tropical Marine Resources. Second Edition.

Eugenio, F., Marcello, J., Martin, J., & Rodríguez-Esparragón, D. (2017). Benthic habitat mapping using multispectral high-resolution imagery: Evaluation of shallow water atmospheric correction techniques. Sensors (Switzerland), 17(11). https://doi.org/10.3390/s17112639

Knudby, A., Roelfsema, C., Lyons, M., Phinn, S., & Jupiter, S. (2011). Mapping fish community variables by Integrating field and satellite data, object-based image analysis and modeling in a traditional Fijian fisheries management area. Remote Sensing, 3(3), 460–483. https://doi.org/10.3390/rs3030460

Kohler, K. E., & Gill, S. M. (2006). Coral Point Count with Excel extensions (CPCe): A Visual Basic program for the determination of coral and substrate coverage using random point count methodology. Computers and Geosciences, 32(9), 1259–1269. https://doi.org/10.1016/j.cageo.2005.11.009

Lyons, M., Phinn, S., & Roelfsema, C. (2011). Integrating Quickbird multi-spectral satellite and field data: Mapping bathymetry, seagrass cover, seagrass species and change in Moreton Bay, Australia in 2004 and 2007. Remote Sensing, 3(1), 42–64. https://doi.org/10.3390/rs3010042

Lyzenga, D. R. (1981). Remote sensing of bottom reflectance and water attenuation parameters in shallow water using aircraft and landsat data. International Journal of Remote Sensing, 2(1), 71–82. https://doi.org/10.1080/01431168108948342

Mahiny, A. S., & Turner, B. J. (2007). 03-114. 73(4), 361–368.

Mastu, L. O. K., Nababan, B., & Panjaitan, J. P. (2018). Pemetaan Habitat Bentik Berbasis Objek Menggunakan Citra Sentinel-2 Di Perairan Pulau Wangi-Wangi Kabupaten Wakatobi. Jurnal Ilmu Dan Teknologi Kelautan Tropis, 10(2), 381. https://doi.org/10.29244/jitkt.v10i2.21039

Peraturan Badan Informasi Geospasial

Nomor 7 Tahun 2017 Tentang Kompetensi Kerja di Bidang Informasi Geospasial

Phinn, S. R., Roelfsema, C. M., & Mumby, P. J. (2012). Analysis for mapping geomorphic and ecological zones on coral reefs. International Journal of Remote Sensing, (July 2012), 37–41.

Purkis, S. J., Graham, N. A. J., & Riegl, B. M. (2008). Predictability of reef fish diversity and abundance using remote sensing data in Diego Garcia (Chagos Archipelago). Coral Reefs, 27(1), 167–178. https://doi.org/10.1007/s00338-007-0306-y

Richards, J. A. (2006). Remote Sensing Digital Image Analysis. In Remote Sensing Digital Image Analysis. https://doi.org/10.1007/978-3-662-02462-1

Richards, J. A., & Jia, X. (2013). [John_A._Richards,_Xiuping_Jia]_Remote_Sensing_Dig(BookFi). https://doi.org/10.1007/3-540-29711-1

Roelfsema, C., Kovacs, E., Ortiz, J. C., Wolff, N. H., Callaghan, D., Wettle, M., … Phinn, S. (2018). Coral reef habitat mapping: A combination of object-based image analysis and ecological modelling. Remote Sensing of Environment, 208(May 2017), 27–41. https://doi.org/10.1016/j.rse.2018.02.005

Roelfsema, C., & Phinn, S. (2008). Evaluating eight field and remote sensing approaches for mapping the benthos of three different coral reef environments in Fiji. Remote Sensing of Inland, Coastal, and Oceanic Waters, 7150, 71500F. https://doi.org/10.1117/12.804806

Roelfsema, C., Phinn, S., Jupiter, S., Comley, J., & Albert, S. (2013). Mapping coral reefs at reef to reef-system scales, 10s-1000s km2, using object-based image analysis. International Journal of Remote Sensing, 34(18), 6367–6388. https://doi.org/10.1080/01431161.2013.800660

Selamat, M. B., Jaya, I., Siregar, V. P., & Hestirianoto, T. (2012). APLIKASI CITRA QUICKBIRD UNTUK PEMETAAN 3D SUBSTRAT DASAR DI GUSUNG KARANG The Application of Quickbird Imagery for 3D Mapping of Bottom Substrate at Patch Reef. Jurnal Geomatika, 18(2), 95–106. Retrieved from http://jurnal.big.go.id/index.php/GM/article/view/183

Siregar, V. (2010). Pemetaan substrat dasar perairan dangkal karang congkak dan lebar kepulauan seribu menggunakan citra satelit quick bird. 2(1), 19–30.

Wahidin, N., Siregar, V. P., Nababan, B., Jaya, I., & Wouthuyzen, S. (2014). Deteksi Perubahan Habitat Terumbu Karang Menggunakan Citra Landsat di Pulau Morotai Provinsi Maluku Utara. Jurnal Ilmu Dan Teknologi Kelautan Tropis, 6, No.2(February 2016), 507–524.




DOI: http://dx.doi.org/10.24895/MIG.2020.22-2.1137

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