Ngurawan, M Ghifary Royyan (2021) Analisis Sebaran Spasial Genangan Banjir Dengan Data Sentinel-1 Menggunakan Googlw Earth Engine (Studi Kasus: Kalimantan Selatan). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Hujan dengan intensitas sedang hingga tinggi menyebabkan banjir pada pertengahan bulan Januari 2021 di Provinsi Kalimantan Selatan. Banjir di Provinsi Kalimantan Selatan pada Januari 2021 membawa dampak korban jiwa maupun materi. Dalam rangka mengurangi kerugian materi yang lebih besar, perlu dilakukan identifikasi wilayah yang mengalami banjir. Dalam penelitian ini daerah sebaran genangan banjir diidentifikasi menggunakan metode change detection dan threshold atau ambang batas. Data diperoleh dari hasil pengolahan menggunakan Google Earth Engine (GEE) berupa peta genangan banjir yang dievaluasi dengan peta hasil pelaporan Badan Nasional Penanggulangan Bencana Daerah Provinsi Kalimantan Selatan. Metode change detection dilakukan pada citra dengan cara membagi nilai piksel citra saat banjir dibagi dengan sebelum banjir. Ekstraksi area genangan kemudian dilakukan dengan nilai threshold sebesar 1,05; 1,1; dan 1,25. Pengolahan dilakukan secara komputasi cloud menggunakan Google Earth Engine (GEE). Luas genangan banjir yang dihasilkan pada tanggal 20 Januari 2021 adalah seluas 226.905 hektar. Hasil tersebut dievaluasi terhadap data laporan banjir secara partisipatif oleh masyarakat dengan nilai overall accuracy sebesar 81,79%. Sedangkan hasil evaluasi terhadap data genangan banjir oleh Badan Perencanaan Pembangunan Daerah (BPPD) memiliki overall accuracy sebesar 97%. Dengan melihat nilai akurasi yang dihasilkan maka nilai threshold yang tepat digunakan pada kejadian banjir pada 20 Januari 2021 adalah dengan nilai threshold sebesar 1,10.
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Rain with moderate to high intensity caused flooding in mid-January 2021 in South Kalimantan Province. Floods in South Kalimantan Province in January 2021 brought both human and material casualties. In order to reduce the greater material losses, it is necessary to do it in areas that experience flooding. In this study, the distribution area of flood identification was identified using change detection and threshold methods. The data obtained from processing using Google Earth Engine (GEE) is in the form of an initial evaluation map with a report map from the National Disaster Management Agency of South Kalimantan Province. The change detection method is carried out on the image by dividing the pixel value of the image during the flood divided by before the flood. The area extraction is then carried out with a threshold value of 1.05; 1.1; and 1.25. Processing is done in cloud computing using Google Earth Engine (GEE). The resulting flood area on January 20, 2021, is 226,905 hectares. These results are against the flood report data in a participatory manner by the community with an overall accuracy value of 81.79%. While the results of the evaluation of flood evaluation data by the Regional Development Planning Agency (BPPD) have an overall accuracy of 97%. By looking at the resulting accuracy value, the appropriate threshold value used in the flood event on January 20, 2021, is with a threshold value of 1.10.
Item Type: | Thesis (Undergraduate) |
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Subjects: | G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing |
Divisions: | Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis |
Depositing User: | M Ghifary Royyan Ngurawan |
Date Deposited: | 18 Aug 2021 01:48 |
Last Modified: | 18 Aug 2021 01:48 |
URI: | http://repository.its.ac.id/id/eprint/87584 |
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