Deteksi Batimetri Perairan Dangkal di Pulau Menjangan, Provinsi Bali Menggunakan Citra Landsat

Gerardus David Ady Purnama Bayuaji, Seftiawan Samsu Rijal, Kuncoro Teguh Setiawan, Kholifatul Aziz

Abstract


Remote sensing-based research in Indonesia using satellite imagery frequently faces the challenge of cloud coverage due to the tropical country. One spatial data that can be extracted from satellite imagery is bathymetry. However, cloud-covered water bathymetric extraction still needs to be examined. This study aims to understand the ability of Landsat 7 ETM+ acquired on 29 July 2013, and Landsat 8, acquired on 24 July 2020, as the representative of non-cloudy image compared to Landsat 8, acquired on 9 August 2020, as the cloudy image. Stumpf algorithm was applied, including a statistical approach of linear regression analysis with in-situ data measurement from Single Beam Echo-Sounder (SBES) to derive the absolute bathymetric map with several classes of depth ranging from 0 – 2 m up to > 10 m. To assess the accuracy, RMSE and confusion matrix was used. The result shows that Landsat 7 ETM+ yields the highest Rwith 0,52, while the lowest total RMSE (8,167 m) and highest overall accuracy of about 69% from the confusion matrix was achieved by the cloudy image of Landsat 8. Nevertheless, the highest absolute depth value yield by Landsat 8 non-cloudy image with 16,1 m. This research confirms that the highest R2 value does not always produce the best model, but it is still promised to be used. Furthermore, the quality of the imagery based on its percentage of cloud coverage is affecting the resulted model.

Keywords


Bathymetry; Landsat; Menjangan; Stumpf Algorithm

Full Text:

PDF

References


Aji, S., Sukmono, A., & Amarrohman, F. (2021). Analisis Pemanfaatan Satellite Derived Bathymetry Citra Sentinel-2a Dengan Menggunakan Algoritma Lyzenga Dan Stumpf (Studi Kasus : Perairan Pelabuhan Malahayati, Provinsi Aceh). Jurnal Geodesi Undip, 8(1), 170–179.

Hartuti, M., & Winarso, G. (2017). Extraction of satellite derived bathymetry information from Landsat 8 in Jakarta Bay. Proceeding Joint Convention HAGI - IAGI - IAFMI - IATMI.

Mahyudin, M., Suprayogi, I., & Trimaijon, T. (2014). Model Prediksi Liku Kalibrasi Menggunakan Pendekatan Jaringan Saraf Tiruan (ZST) (Studi Kasus : Sub DAS Siak Hulu). Jurnal Online Mahasiswa Fakultas Teknik Universitas Riau, 1(1), 1–18.

Manessa, M. D. M., Haidar, M., Hartuti, M., & Kresnawati, D. K. (2018). Determination of the Best Methodology for Bathymetry Mapping Using Spot 6 Imagery: a Study of 12 Empirical Algorithms. International Journal of Remote Sensing and Earth Sciences (IJReSES), 14(2), 127. https://doi.org/10.30536/j.ijreses.2017.v14.a2827

Nurkhayati, R. (2013). Pemteaan Batimetri Perairan Dangkal Menggunakan Citra Quickbird di Perairan Taman Nasional Karimun Jawa, Kabupaten Jepara, Jawa Tengah. Jurnal Bumi Indonesia, 2(2), 140–148.

Prayogo, L. M., & Basith, A. (2020). Uji Performa Citra Worldview 3 dan Sentinel 2A untuk Pemetaan Kedalaman Laut Dangkal (Studi Kasus di Kepulauan Karimunjawa, Jawa Tengah). JGISE: Journal of Geospatial Information Science and Engineering, 3(2), 161. https://doi.org/10.22146/jgise.59572

Purnamasari, E., Kamal, M., & Wicaksono, P. (2021). Comparison of vegetation indices for estimating above-ground mangrove carbon stocks using PlanetScope image. Regional Studies in Marine Science, 44, 101730. https://doi.org/10.1016/j.rsma.2021.101730

Pushparaj, J., & Hegde, A. V. (2017). Estimation of bathymetry along the coast of Mangaluru using Landsat-8 imagery. The International Journal of Ocean and Climate Systems, 8(2), 71–83. https://doi.org/10.1177/1759313116679672

Rijal, S. S., & Bayuaji, G. D. P. (2021). Penentuan Kesesuaian Lokasi Marikultur Ikan Kerapu Di Sumatera Utara, Indonesia Menggunakan Google Earth Engine. JFMR-Journal of Fisheries and Marine Research, 5(2). https://doi.org/10.21776/ub.jfmr.2021.005.02.21

Sesama, A. S., Setiawan, K. T., & Julzarika, A. (2020). Bathymetric Extraction Using Planetscope Imagery ( Case Study : Kemujan Island , Central Java ). 17(2), 209–216.

Setiawan, K. T., Adawiah, S. W., Marini, Y., & Winarso, G. (2017). Bathymetry Data Extraction Analysis Using Landsat 8 Data. International Journal of Remote Sensing and Earth Sciences (IJReSES), 13(2), 79. https://doi.org/10.30536/j.ijreses.2016.v13.a2448

Setiawan, K. T., Osawa, T., & Nuarsa, I. W. (2014). Aplikasi Algoritma Van Hengel dan Spitzer untuk Ekstraksi Informasi Batimetri Menggunakan Data. Seminar Nasional Penginderaan Jauh 2014, 222–230.

Stumpf, R. P., Holderied, K., & Sinclair, M. (2003). Determination of water depth with high-resolution satellite imagery over variable bottom types. Limnology and Oceanography, 48(1 II), 547–556. https://doi.org/10.4319/lo.2003.48.1_part_2.0547

Tarigan, V. A., Sasmito, B., & Hani’ah, H. (2019). Kajian Akurasi Penentuan Garis Pantai Menggunakan Citra Landsat 8 (Studi Kasus Kabupaten Lampung Timur) Victor. 8(1), 278–287.

USGS. (2013). Landsat Missions Timeline (p. 40).

Zulkarnain, M., Purwanti, P., & Indrayani, E. (2013). Analysis of Aquaculture Production Value Effect To Gross Domestic Product of Fisheries Sector in. Jurnal ECSOFiM, 1(1), 52–68.




DOI: https://doi.org/10.34312/jgeosrev.v4i2.13886



Copyright (c) 2022 Author

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

slot gacor slot gacor hari ini slot gacor 2025 demo slot pg slot gacor slot gacor