Pemantauan Backscatter Permukaan Dan Deformasi Terkait Bencana Banjir Kalimantan Selatan 2021 Menggunakan Data SAR Sentinel-1

Febriansyah, Muhammad Nahdi (2024) Pemantauan Backscatter Permukaan Dan Deformasi Terkait Bencana Banjir Kalimantan Selatan 2021 Menggunakan Data SAR Sentinel-1. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Banjir merupakan salah satu penyumbang angka kejadian bencana terbesar di Indonesia. Banjir didefinisikan sebagai peristiwa atau keadaan dimana terendamnya suatu daerah atau daratan karena volume air yang meningkat. Pada awal tahun 2021, bencana banjir melanda Provinsi Kalimantan Selatan. Bencana ini diketahui disebabkan oleh intesitas curah hujan yang tinggi sehingga memicu luapan air sungai pada 9 Januari 2021. Badan Nasional Penanggulangan Bencana (BNPB) mencatat 112.709 warga mengungsi dan 27.111 rumah terendam akibat banjir ini. Kalimantan Selatan merupakan salah satu Provinsi di Pulau Kalimantan. Pulau Kalimantan merupakan wilayah dimana proses tektonik relatif kecil dibandingkan dengan daerah lain di Indonesia. Distribusi kegempaan dan sejarah gempa bumi membuktikan bahwa Kalimantan kurang berpotensi untuk gempa besar. Maka apabila terdapat deformasi pada wilayah ini, kemungkinan erat kaitannya dengan periode hidrologi musiman termasuk hujan dan banjir. Teknik penginderaan jauh dengan memanfaatkan pekembangan teknologi SAR (Synthetic Aperture Radar) memberikan solusi dalam pemantauan tersebut. Saat ini, citra satelit SAR banyak digunakan untuk pemantauan genangan banjir dan deformasi karena citra tersebut dapat diakses secara bebas serta memiliki resolusi spasial dan temporal yang tinggi. Citra satelit SAR juga cocok digunakan untuk pemantauan genangan banjir dan deformasi karena keunggulannya yang bisa digunakan tanpa terkendala kondisi cuaca, waktu siang dan malam, dan tutupan awan dan kabut. Oleh karena itu dengan memanfaatkan citra SAR Sentinel-1 dilakukan pengolahan data amplitudo backscatter untuk identifikasi sebaran spasial genangan banjir, serta dari data fase interferogram akan didapatkan informasi deformasi pada saat kejadian banjir. Pengolahan koefisien backscatter dalam bentuk sigma nought menggunakan citra Sentinel-1 GRD polarisasi VH dengan metode change detection mendapatkan sebaran genangan banjir dengan luas sebesar 2022,558 km2, dengan Overall Accuraccy 90,833%. Dari pengolahan DInSAR multitemporal menggunakan citra Sentinel-1 SLC dan dilakukan cropping area dengan sebaran genangan banjir. Didapatkan 7 pengamatan, kemudian dilakukan kumulatif sehingga diperoleh uplift maksimal sebesar 0,168 meter dan subsidence maksimal sebesar 0,159 meter. Sedangkan hubungan antara nilai deformasi dengan backscatter dilihat dari hasil koefisien korelasi dimana hasil DInSAR dengan backscatter polarisasi VV sebesar 0,211 dan untuk hasil DInSAR dengan backscatter polarisasi VH sebesar 0,327. Pada area sebaran genangan banjir luasan subsidence lebih besar besar dibanding uplift. Selain itu hasil yang telah didapatkan menunjukan hubungan keterkaitan namun tidak secara signifikan antara bencana banjir yang merupakan permukaan air temporal dengan deformasi.
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Floods are one of the largest contributors to the number of disasters in Indonesia. Flooding is defined as an event or situation where an area or land is submerged due to an increased volume of water. At the beginning of 2021, a flood disaster hit South Kalimantan Province. This disaster is known to have been caused by the high intensity of rainfall, which triggered the overflow of river water on January 9 2021. The National Disaster Management Agency (BNPB) recorded that 112.709 residents were displaced and 27.111 houses were submerged due to this flood. South Kalimantan is one of the provinces on the island of Kalimantan. Kalimantan Island is an area where tectonic processes are relatively small compared to other areas in Indonesia. The distribution of seismicity and the history of earthquakes prove that Kalimantan has little potential for large earthquakes. So if there is deformation in this area, it is likely closely related to seasonal hydrological periods including rain and floods. Remote sensing techniques utilizing developments in SAR (Synthetic Aperture Radar) technology provide a solution for this monitoring. Currently, SAR satellite images are widely used for monitoring flood inundation and deformation because these images can be accessed freely and have high spatial and temporal resolution. SAR satellite imagery is also suitable for monitoring flood inundation and deformation because of its advantage that it can be used without being constrained by weather conditions, time of day and night, and cloud and fog cover. Therefore, by utilizing Sentinel-1 SAR images, backscatter amplitude data processing is carried out to identify the spatial distribution of flood inundation, and from the interferogram phase data, information on deformation during a flood event will be obtained. Processing the backscatter coefficient in the form of sigma nought using Sentinel-1 GRD VH polarization images with the change detection method obtained a distribution of flood inundation with an area of 2022,558 km2, with an Overall Accuracy of 90,833%. From multi-temporal DInSAR processing using Sentinel-1 SLC imagery and cropping the area with the distribution of flood inundation. Seven observations were obtained, then cumulative to obtain a maximum uplift of 0,168 meters and a maximum subsidence of 0,159 meters. Meanwhile, the relationship between deformation values and backscatter can be seen from the correlation coefficient results where the DInSAR results with VV polarization backscatter are 0,211 and for DInSAR results with VH polarization backscatter it is 0,327. In the flood inundation distribution area, the subsidence area is greater than the uplift. Apart from that, the results obtained show a correlation, but not a significant one, between flood disasters, which are temporal water levels, and deformation.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Banjir, Backscatter, Deformasi, Sentinel-1, Flood, Backscatter, Deformation, Sentinel-1
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography > GA102.4.R44 Cartography--Remote sensing G Geography. Anthropology. Recreation > GB Physical geography > GB1399.9 Floods G Geography. Anthropology. Recreation > GB Physical geography > GB651 Subsidences (Earth movements)
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29101-(S2) Master Thesis
Depositing User:	Muhammad Nahdi Febriansyah
Date Deposited:	29 Jul 2024 13:16
Last Modified:	29 Jul 2024 13:16
URI:	http://repository.its.ac.id/id/eprint/109918

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