Pemanfaatan Citra Pengindraan Jauh Untuk Memperkirakan Penurunan Tanah Diberbagai Tipe Penggunaan Lahan
DOI:
https://doi.org/10.23887/jstundiksha.v11i2.50314Kata Kunci:
Sentinel 1, Penurunan Tanah, PLAbstrak
Dalam beberapa tahun terakhir, kerugian besar akibat penurunan tanah di daerah perkotaan semakin menarik perhatian. Evaluasi yang tepat dari pola spasial tingkat penurunan tanah di Kota Padang adalah kunci untuk memahami dampak potensialnya terhadap turunnya permukaan tanah dan keberlanjutan jangka panjang wilayah Kota Padang. Dalam studi ini, penurunan tanah yang terjadi selama periode waktu 2018 - 2019 diukur menggunakan Citra Sentinel 1 SAR untuk memahami apakah terjadi subsidensi. Nilai penurunan tanah pada setiap piksel dihasilkan dari pengolahan data Sentinel 1 SAR yang selanjutnya diklasifikasikan menurut kelas penggunaan/penutup lahan di wilayah studi. Peta penggunaan/penutup lahan dihasilkan dari ektraksi citra satelit Landsat 8 OLI/TIRs. Hasilnya perbandingan antara pola penurunan tanah menggunakan Sentinel 1 SAR dan kelas penggunaan lahan yang berbeda di Kota Padang menunjukkan bahwa tidak ada hubungan yang jelas di antara keduanya. Hal ini menunjukkan bahwa fenomena penurunan tanah terjadi pada skala lokal atau terlokalisasi di wilayah ini.
Referensi
Abidin, H. Z., Andreas, H., Gumilar, I., Fukuda, Y., Pohan, Y. E., & Deguchi, T. (2011). Land subsidence of Jakarta (Indonesia) and its relation with urban development. Natural Hazards, 59(3), 1753–1771. https://doi.org//10.1007/s11069-011-9866-9.
Abidin, H. Z., Andreas, H., Gumilar, I., & Wibowo, I. R. R. (2015). On correlation between urban development, land subsidence and flooding phenomena in Jakarta. , 370, 15-20. https://doi: Proceedings of the International Association of Hydrological Sciences, 370, 15–20. https://doi.org/10.5194/piahs-370-15-2015.
Achmad, A. R., & Lee, C. W. (2021). Surface Deformation Measurement of the 2020 M w 6.4 Petrinja, Croatia Earthquake Using Sentinel-1 SAR Data. Korean Journal of Remote Sensing, 37(1), 139–151. https://doi.org/10.7780/kjrs.2021.37.1.11.
Anjasmara, I. M., Yulyta, S. A., & Taufik, M. (2020). Application of time series InSAR (SBAS) method using sentinel-1A data for land subsidence detection in Surabaya city. International Journal on Advanced Science, Engineering and Information Technology, 10(1), 191–197. https://doi.org/10.18517/ijaseit.10.1.6749.
Arslan, İ., Topakcı, M., & Demir, N. (2022). Monitoring Maize Growth and Calculating Plant Heights with Synthetic Aperture Radar (SAR) and Optical Satellite Images. Agriculture, 12(6), 800.
Bagheri-Gavkosh, M., Hosseini, S. M., Ataie-Ashtiani, B., Sohani, Y., Ebrahimian, H., Morovat, F., & Ashrafi, S. (2021). Land subsidence: A global challenge. Science of The Total Environment, 778, 146193. https://doi.org/10.1016/j.scitotenv.2021.146193.
Bott, L. M., Schöne, T., Illigner, J., Haghighi, M. H., Gisevius, K., & Braun, B. (2021). Land subsidence in Jakarta and Semarang Bay–The relationship between physical processes, risk perception, and household adaptation. Ocean & Coastal Management, 211, 105775. https://doi.org/10.1016/j.ocecoaman.2021.105775.
Dang, V. K., Nguyen, T. D., Dao, N. H., Duong, T. L., Dinh, X. V, & Weber, C. (2021). Land subsidence induced by underground coal mining at Quang Ninh, Vietnam: persistent scatterer interferometric synthetic aperture radar observation using Sentinel-1 data. International Journal of Remote Sensing, 49(9), 3563–3582. https://doi.org/10.1080/01431161.2021.1875513.
Devaraj, S., Yarrakula, K., Martha, T. R., Murugesan, G. P., Vaka, D. S., Surampudi, S., & Budamala, V. (2022). Time series SAR interferometry approach for landslide identification in mountainous areas of Western Ghats, India. Journal of Earth System Science, 131(2), 1–17. https://doi.org/10.1007/s12040-022-01876-3.
Du, Z., Ge, L., Ng, A. H. M., Zhu, Q., Yang, X., & Li, L. (2018). Correlating the subsidence pattern and land use in Bandung, Indonesia with both Sentinel-1/2 and ALOS-2 satellite images. International Journal of Applied Earth Observation and Geoinformation, 67, 54–68. https://doi.org/10.1016/j.jag.2018.01.001.
Fajrin, F., Almegi, A., Bakari, A., Ramadhan, R., & Antomi, Y. (2021). Enviromental Monitoring of Land Subsidence in The Coastal Area of Padang City Using Sentinel 1 SAR Dataset. Sumatra Journal of Disaster, Geography and Geography Education, 5(1), 30–34. https://doi.org/10.24036/sjdgge.v5i1.359.
Fárová, K., Jelének, J., Kopačková-Strnadová, V., & Kycl, P. (2019). Comparing DInSAR and PSI techniques employed to Sentinel-1 data to monitor highway stability: a case study of a massive Dobkovičky landslide, Czech Republic. Remote Sensing, 11(22), 2670. https://doi.org/10.3390/rs11222670.
Galloway, D. L., & Burbey, T. J. (2011). Regional land subsidence accompanying groundwater extraction. Hydrogeology Journal, 19(8), 1459–1486. https://doi.org/10.1007/s10040-011-0775-5.
Goldstein, R. M., & Werner, C. L. (1998). Radar interferogram filtering for geophysical applications. Geophysical Research Letters, 25(21), 4035–4038. https://doi.org/10.1029/1998GL900033.
Hakim, W. L., Achmad, A. R., & Lee, C. W. (2020). Land subsidence susceptibility mapping in jakarta using functional and meta-ensemble machine learning algorithm based on time-series InSAR data. Remote Sensing, 12(12), 3627. https://doi.org/10.3390/rs12213627.
Herrera-García, G., Ezquerro, P., Tomás, R., Béjar-Pizarro, M., López-Vinielles, J., Rossi, M., & Ye, S. (2021). Mapping the global threat of land subsidence. Science, 371(6524), 34–36. https://doi.org/10.1126/science.abb8549.
Hussain, M. A., Chen, Z., Shoaib, M., Shah, S. U., Khan, J., & Ying, Z. (2022). Sentinel-1A for monitoring land subsidence of coastal city of Pakistan using Persistent Scatterers In-SAR technique. Scientific Reports, 12(1), 1–18. https://doi.org/10.1038/s41598-022-09359-7.
Ishwar, S. G., & Kumar, D. (2017). Application of DInSAR in mine surface subsidence monitoring and prediction. Current Science, 46–51. https://doi.org/10.18520/cs/v112/i01/46-51.
Islam, L. J. F., Prasetyo, Y., & Sudarsono, B. (2017). Analisis Penurunan Muka Tanah (Land Subsidence) Kota Semarang Menggunakan Citra Sentinel-1 Berdasarkan Metode DInSAR pada Perangkat Lunak SNAP. Jurnal Geodesi Undip, 6(2), 29–36.
Lo, W., Purnomo, S. N., Dewanto, B. G., & Sarah, D. (2022). Integration of numerical models and InSAR techniques to assess land subsidence due to excessive groundwater abstraction in the coastal and lowland regions of semarang city. Water (Switzerland), 14(2), 201. https://doi.org/10.3390/w14020201.
Minderhoud, P. S. J., Coumou, L., Erban, L. E., Middelkoop, H., Stouthamer, E., & Addink, E. A. (2018). The relation between land use and subsidence in the Vietnamese Mekong delta. Science of The Total Environment, 634, 715–726. https://doi.org/10.1016/j.scitotenv.2018.03.372.
Novelli, A., Aguilar, M. A., Nemmaoui, A., Aguilar, F. J., & Tarantino, E. (2016). Performance evaluation of object based greenhouse detection from Sentinel-2 MSI and Landsat 8 OLI data: A case study from Almería (Spain). International Journal of Applied Earth Observation and Geoinformation, 52, 403–411. https://doi.org/10.1016/j.jag.2016.07.011.
Rahmati, O., Golkarian, A., Biggs, T., Keesstra, S., Mohammadi, F., & Daliakopoulos, I. N. (2019). Land subsidence hazard modeling: Machine learning to identify predictors and the role of human activities. Journal of Environmental Management, 236, 466–480. https://doi.org/10.1016/j.jenvman.2019.02.020.
Raspini, F., Bianchini, S., Moretti, S., Loupasakis, C., Rozos, D., Duro, J., & Garcia, M. (2016). Advanced interpretation of interferometric SAR data to detect, monitor and model ground subsidence: outcomes from the ESA-GMES Terrafirma project. Natural Hazards, 83(1), 155–181. https://doi.org/10.1007/s11069-016-2341-x.
Sanabria, M. P., Guardiola-Albert, C., Tomás, R., Herrera, G., Prieto, A., Sánchez, H., & Tessitore, S. (2014). Subsidence activity maps derived from DInSAR data: Orihuela case study. Natural Hazards and Earth System Sciences, 14(5), 1341–1360. https://doi.org/10.5194/nhess-14-1341-2014.
Shirzaei, M., Freymueller, J., Törnqvist, T. E., Galloway, D. L., Dura, T., & Minderhoud, P. S. (2021). Measuring, modelling and projecting coastal land subsidence. Nature Reviews Earth & Environment, 2(1), 40–58. https://doi.org/10.1038/s43017-020-00134-8.
Simmons, B. S., & Wempen, J. M. (2021). Quantifying relationships between subsidence and longwall face advance using DInSAR. International Journal of Mining Science and Technology, 31(1), 91–94. https://doi.org/10.1016/j.ijmst.2020.12.021.
Takagi, H., Esteban, M., Mikami, T., Pratama, M. B., Valenzuela, V. P. B., & Avelino, J. E. (2021). People’s perception of land subsidence, floods, and their connection: A note based on recent surveys in a sinking coastal community in Jakarta. Ocean & Coastal Management, 211, 105753. https://doi.org/10.1016/j.ocecoaman.2021.105753.
Umarhadi, D. A., Widyatmanti, W., Kumar, P., Yunus, A. P., Khedher, K. M., Kharrazi, A., & Avtar, R. (2022). Tropical peat subsidence rates are related to decadal LULC changes: Insights from InSAR analysis. Science of The Total Environment, 816, 151561. https://doi.org/10.1016/j.scitotenv.2021.151561.
Widodo, J., Naryanto, H. S., Hidayat, N., Putra, A. P., Izumi, Y., Perissin, D., & Sumantyo, J. S. (2021). Land Subsidence Assessment of Bandung City, Indonesia in Geological Perspective, Based on Interferometric SAR Using C-band Data. In 2021 Photonics & Electromagnetics Research Symposium (PIERS), 2377–2381. https://doi.org/10.1109/PIERS53385.2021.9694892.
Zaenudin, A., Darmawan, I. G. B., Minardi, S., & Haerudin, N. (2018). Land subsidence analysis in Bandar Lampung City based on InSAR. In Journal of Physics: Conference Series, 1080(1), 012043. https://doi.org/10.1088/1742-6596/1080/1/012043.
Zhang, Y., Liu, Y., Jin, M., Jing, Y., Liu, Y., Liu, Y., & Chen, Y. (2019). Monitoring land subsidence in Wuhan city (China) using the SBAS-InSAR method with radarsat-2 imagery data. Sensors, 19(3), 743. https://doi.org/10.3390/s19030743.
Zoysa, S., Schöne, T., Herbeck, J., Illigner, J., Haghighi, M., Simarmata, H., & Hornidge, A. K. (2021). The ‘wickedness’ of governing land subsidence: Policy perspectives from urban Southeast Asia. LPoS One, 16(6), e0250208. https://doi.org/10.1371/journal.pone.0250208.
Unduhan
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2022 Fajrin Fajrin, Yudi Antomi
Artikel ini berlisensiCreative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with the Jurnal Sains dan Teknologi (JST) agree to the following terms:
- Authors retain copyright and grant the journal the right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work. (See The Effect of Open Access)