Pemantauan Sebaran Spasial Genangan Banjir Menggunakan Citra Satelit Sentinel-1 Dan Google Earth Engine (Studi Kasus: Banjir Sulawesi Selatan Tahun 2021).

Putriyani, Novia Nurfadila (2022) Pemantauan Sebaran Spasial Genangan Banjir Menggunakan Citra Satelit Sentinel-1 Dan Google Earth Engine (Studi Kasus: Banjir Sulawesi Selatan Tahun 2021). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Setiap tahun, banjir melanda sebagian besar Provinsi Sulawesi Selatan. Pada tahun 2021, Provinsi Sulawesi Selatan mengalami hujan lebat. Sulawesi Selatan dilanda banjir pada Agustus dan Desember 2021 yang berdampak pada 19.769 jiwa. Bencana alam yang paling merusak antara lain banjir. Banjir memberikan dampak negatif bagi daerah yang tergenang. Oleh karena itu, diperlukan suatu rencana mitigasi bencana untuk mengurangi dampak tersebut. Dalam penelitian ini, wilayah genangan diekstraksi menggunakan nilai ambang batas 1,1 dan 1,25 yang ditemukan dari studi sebelumnya, setelah membuat perbandingan visual antara citra satelit SAR Sentinel-1 yang diperoleh dengan polarisasi VV dan VH yang diperoleh dari arah lintasan ascending dan descending. Hasil luas genangan banjir antara data genangan banjir hasil ekstrasi Citra SAR Sentinel-1 dievalusi dengan daftar data daerah terdampak banjir dari Badan Nasional Penanggulangan Bencana (BNPB). Pemrosesan dilakukan menggunakan Google Earth Engine di cloud (GEE). Dengan membagi nilai piksel gambar sebelum banjir dengan nilai pikselnya selama banjir, metode lapisan Perbedaan diterapkan pada gambar. Parameter yang paling baik dalam uji akurasi adalah polarisasi VV dengan arah lintasan descending, yang memiliki nilai kappa 0,5968 dan nilai akurasi keseluruhan 86%, termasuk dalam kelompok cukup. Luas genangan banjir adalah 172.835.375 hektar yaitu 3,6994% dari luas keselurahan Provinsi Sulawesi Selatan.
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Every year, floods hit most of South Sulawesi Province. In 2021, South Sulawesi Province will experience heavy rains. South Sulawesi was hit by floods in August and December 2021 which affected 19,769 people. The most destructive natural disasters are floods. Floods have a negative impact on inundated areas. Therefore, a disaster mitigation plan is needed to reduce these impacts. In this study, inundation areas were extracted using threshold values of 1.1 and 1.25 found from previous studies, after making a visual comparison between the SAR Sentinel-1 satellite imagery obtained with VV and VH polarizations obtained from pass direction ascending and descending. The results of the flood inundation area between the flood inundation data extracted from the Sentinel-1 SAR image were evaluated with a list of flood-affected area data from the National Disaster Management Agency (BNPB). Processing is done using Google Earth Engine in the cloud (GEE). By dividing the pixel value of the image before flooding by its pixel value during the flood, the Difference layer method is applied to the image. The best parameter in the accuracy test is the VV polarization with a descending trajectory, which has a kappa value of 0.5968 and an overall accuracy value of 86 percent, which is included in the sufficient group. The flood inundation area is 172,835,375 hectares, which is 3.6994% of the total area of South Sulawesi Province.

Item Type:	Thesis (Other)
Additional Information:	RSG 551.577 Put p-1 2022
Uncontrolled Keywords:	Difference layer, Genangan Banjir, Google Earth Engine, Penginderaan Jauh, Sentinel-1. Difference layer, Google Earth Engine, Inundation, Remote Sensing, Sentinel-1.
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	18 May 2026 06:17
Last Modified:	18 May 2026 06:17
URI:	http://repository.its.ac.id/id/eprint/133220

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