Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments)
Abstract
Seawater intrusion can increase soil salinity, which occurs due to flooding, evaporation, and land cover changes in coastal areas. This research aims to map and observe the characteristics of seawater intrusion in Way Urang, Kalianda, South Lampung, using Dual-polarization of Sentinel-1 SAR imagery with VV, VH, VV+VH, and (VV+VH)/2 polarization. There were 28 samples used in this research which were divided into two types, GCP (ground control point) and ICP (independent check point). GCP samples are used to create a seawater intrusion estimation model using the regression method, while ICP samples are used to test the validation model using the RMSE method. The seawater intrusion estimation model created in this study had a good RMSE accuracy of 0.01 – 0.08. However, these results were not followed by a strong relationship between backscatter and estimated salinity value. This can be caused by high levels of soil moisture in the research area. Based on the salinity value estimation model, it shows that there is no seawater intrusion in the research area.
Seawater intrusion can increase soil salinity, which occurs due to flooding, evaporation, and land cover changes in coastal areas. This research aims to map and observe the characteristics of seawater intrusion in Way Urang, Kalianda, South Lampung, using Dual-polarization of Sentinel-1 SAR imagery with VV, VH, VV+VH, and (VV+VH)/2 polarization. There were 28 samples used in this research which were divided into two types, GCP (ground control point) and ICP (independent check point). GCP samples are used to create a seawater intrusion estimation model using the regression method, while ICP samples are used to test the validation model using the RMSE method. The seawater intrusion estimation model created in this study had a good RMSE accuracy of 0.01 – 0.08. However, these results were not followed by a strong relationship between backscatter and salinity value. This can be caused by high levels of soil moisture in the research area. Based on the salinity value estimation model, it shows that there is no seawater intrusion in the research area.
Bahasa Abstract
Intrusi air laut dapat meningkatkan salinitas pada permukaan tanah yang terjadi akibat adanya banjir, evaporasi, dan perubahan tutupan lahan di daerah pesisir. Penelitian ini bertujuan untuk memetakan dan mengamati karakteristik intrusi air laut di daerah pesisir Kalianda, Lampung Selatan, menggunakan citra SAR Sentinel-1 polarisasi VV, VH, VV+VH, dan (VV+VH)/2. Terdapat 28 sampel yang digunakan pada penelitian ini yang dibagi menjadi dua jenis yaitu GCP (ground control point) dan ICP (independent check point). Sampel GCP untuk membuat model estimasi intrusi air laut dengan metode regressi, sedangkan sampel ICP digunakan untuk menguji hasil validasi model tersebut menggunakan metode RMSE. Model estimasi intrusi air laut yang dibuat pada penelitian ini memiliki ketelitian RMSE yang baik yaitu sebesar 0.01 – 0.08, tetapi hasil tersebut tidak diikuti oleh kuatnya hubungan antara backscatter dengan estimasi nilai salinitas. Hal tersebut dapat disebabkan oleh tingginya tingkat kelembaban tanah pada area penelitian. Berdasarkan model estimasi nilai salinitas yang dibuat menunjukkan bahwa tidak adanya intrusi air laut pada area peneltian.
References
Abdikan, S., Sanli, F.B., Ustuner, M., Calò, F. (2016). Land cover mapping using Sentinel-1 SAR data. The International Archives of the Photogrammetry, XLI(Remote Sensing and Spatial Information Sciences,\), 757–761. https://doi.org/https://doi.org/10.5194/isprsarchives-XLI-B7-757-2016
Arief, M., Anggraini, N., Adawiah, S. W., Hartuti, M., & Suwargana, N. (2017). Aplikasi Data Satelit Radar Sentinel-1A Guna Deteksi Hutan Mangrove Studi Kasus : Segara Anakan , Kabupaten Cilacap. Seminar Nasional Penginderaan Jauh ke-4 Tahun 2017, 1982, 277–289.
Aslam, K., Rashid, S., Saleem, R., & Aslam, R. M. S. (2015). Use of Geospatial Technology for Assessment of Waterlogging & Salinity Conditions in the Nara Canal Command Area in Sindh, Pakistan. Journal of Geographic Information System, 07(04), 438–447. https://doi.org/10.4236/jgis.2015.74035
Ataie-Ashtiani, B., Werner, A. D., Simmons, C. T., Morgan, L. K., & Lu, C. (2013). Quelle est l’importance de l’impact de l’inondation des terres sur l’intrusion marine causée par l’élévation du niveau de la mer? Hydrogeology Journal, 21(7), 1673–1677. https://doi.org/10.1007/s10040-013-1021-0
Chaturvedi, S. K. (2019). Study of synthetic aperture radar and automatic identification system for ship target detection. Journal of Ocean Engineering and Science, 4(2), 173–182. https://doi.org/10.1016/j.joes.2019.04.002
Ghazali, M. F., & Wikantika, K. (2021). Pre-assessment of the Potential Dual Polarization Sentinel-1 Data for Mapping the Mangrove Tree Species Distribution in South Bali, Indonesia. In IEE (Ed.), 7th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR) (hal. 1–6). IEEE (Institute of Electrical and Electronics Engineers). https://doi.org/10.1109/APSAR52370.2021
Hoa, P. V., Giang, N. V., Binh, N. A., Hai, L. V. H., Pham, T. D., Hasanlou, M., & Bui, D. T. (2019). Soil salinity mapping using SAR Sentinel-1 data and advanced machine learning algorithms: A case study at Ben Tre Province of the Mekong River Delta (Vietnam). Remote Sensing, 11(2), 1–21. https://doi.org/10.3390/rs11020128
Jumarang, M. I., Nurjaya, I. W., Atmadipoera, A. S., & Bengen, D. G. (2020). Sebaran Salinitas Perairan Laut Kabupaten Bengkayang pada Musim Kemarau. Positron, 10(1), 64. https://doi.org/10.26418/positron.v10i1.40113
Lasne, Y., Paillou, P., Freeman, A., Farr, T., McDonald, K. C., Ruffié, G., Malézieux, J. M., Chapman, B., & Demontoux, F. (2008). Effect of salinity on the dielectric properties of geological materials: Implication for soil moisture detection by means of radar remote sensing. IEEE Transactions on Geoscience and Remote Sensing, 46(6), 1674–1688. https://doi.org/10.1109/TGRS.2008.916220
Lestari, A. I., & Kushardono, D. (2018). Potensi data satelit radar x- band dan c- band untuk pemantauan lahan sawah dan fase pertumbuhan padi. Inderaja, IX(March).
Li, Y. Y., Zhao, K., Ding, Y. L., & Ren, J. H. (2013). An empirical method for soil salinity and moisture inversion in West of Jilin. International Conference on Remote Sensing, Environment and Transportation Engineering, RSETE 2013, 41201335, 19–21. https://doi.org/10.2991/rsete.2013.5
Li, Y. Y., Zhao, K., Ren, J. H., Ding, Y. L., & Wu, L. L. (2014). Analysis of the dielectric constant of saline-alkali soils and the effect on radar backscattering coefficient: A case study of soda alkaline saline soils in western Jilin province using RADARSAT-2 data. Scientific World Journal, 2014. https://doi.org/10.1155/2014/563015
Nguyen, K. A., Liou, Y. A., Tran, H. P., Hoang, P. P., & Nguyen, T. H. (2020). Soil salinity assessment by using near-infrared channel and Vegetation Soil Salinity Index derived from Landsat 8 OLI data: a case study in the Tra Vinh Province, Mekong Delta, Vietnam. Progress in Earth and Planetary Science, 7(1), 1–16. https://doi.org/10.1186/s40645-019-0311-0
Pangesti, S. (2016). SATS4312: Modul 1 Regresi Linear Sederhana (hal. 52).
Simon I, P., Rikardo, H., & Ferdimon, K. (2020). Variasi musiman suhu, salinitas dan kekeruhan air laut di perairan selat lembeh, Sulawesi Utara. Jurnal Ilmiah PLATAX, 8(1), 111–117. http://ejournal.unsrat.ac.id/index.php/platax
Suprayogi, I., Trimaijon, & Mahyudin. (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.
Taghadosi, M. M., Hasanlou, M., & Eftekhari, K. (2019). Soil salinity mapping using dual-polarized SAR Sentinel-1 imagery. International Journal of Remote Sensing, 40(1), 237–252. https://doi.org/10.1080/01431161.2018.1512767
Thiam, S., Villamor, G. B., Faye, L. C., Sène, J. H. B., Diwediga, B., & Kyei-Baffour, N. (2021). Monitoring land use and soil salinity changes in coastal landscape: a case study from Senegal. Environmental Monitoring and Assessment, 193(5). https://doi.org/10.1007/s10661-021-08958-7
Wu, W., Muhaimeed, A. S., Al-Shafie, W. M., & Al-Quraishi, A. M. F. (2019). Using l-band radar data for soil salinity mapping—a case study in central iraq. Environmental Research Communications, 1(8). https://doi.org/10.1088/2515-7620/ab37f0
Yu, X., Xin, P., & Hong, L. (2021). Effect of evaporation on soil salinization caused by ocean surge inundation. Journal of Hydrology, 597(November 2020), 126200. https://doi.org/10.1016/j.jhydrol.2021.126200
Zulfikar, M. E. (2021). Perbandingan Metode Klasifikasi Maximum Likelihood Dan Minimum Distance Pada Pemetaan Tutupan Lahan Di Kabupaten Bandung Barat, Jawa Barat. Seminar Nasional dan Diseminasi Tugas Akhir, Mlc, 531–541.
Recommended Citation
Salsabila, Choirunnisa; Ghazali, Mochamad Firman; Dermawan, Ananda; Zahra, Lauditta; Melliana, Ni Made Mega; and Aulia, Mila
(2024)
"Characteristic of Dual Polarization Sentinel-1 for Estimation of Seawater Intrusion on Kalianda Coast, South Lampung: A Preliminary Study,"
Jurnal Geografi Lingkungan Tropik (Journal of Geography of Tropical Environments): Vol. 7:
No.
1, Article 7.
Available at:
https://scholarhub.ui.ac.id/jglitrop/vol7/iss1/7
Included in
Geographic Information Sciences Commons, Physical and Environmental Geography Commons, Remote Sensing Commons, Spatial Science Commons