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All Journal Jurnal Geofisika Makara Journal of Science
Irnaka, Theodosius Marwan
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Earth & Planetary Sciences Energy Physics

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Pemetaan Endapan Awan Panas Gunung Api Semeru Periode Juni 2021 – Desember 2021 menggunakan Citra Radar Sentinel 1 dan Optik Sentinel 2 Darmawan, Herlan; Budiarti, Dyah Retno; Irnaka, Theodosius Marwan
Jurnal Geofisika Vol 21 No 2 (2023): Jurnal Geofisika
Publisher : Himpunan Ahli Geofisika Indonesia (HAGI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36435/jgf.v21i2.565

Abstract

Gunung Semeru merupakan gunung api aktif di Kabupaten Lumajang dan Kabupaten Malang, Jawa Timur yang memiliki potensi bencana erupsi. Erupsi Gunung Api Semeru tanggal 4 Desember 2021 mengakibatkan awan panas dengan jarak luncur melebihi batas Kawasan Rawan Bencana (KRB) III tahun 1996. Pasca kejadian erupsi, satelit non-komersil (Sentinel-1) melintas dan mengambil gambar sebaran awan panas Gunung Semeru. Penelitian ini menggunakan dataset Sentinel-1 untuk memonitor perubahan morfologi dan memetakan zona endapan awan panas Semeru dari bulan Juni hingga Desember 2021. Data satelit Sentinel-1 yang digunakan untuk penelitian memanfaatkan informasi intensitas hamburan balik dari satelit radar Sentinel-1. Kemudian perbandingan dua data dengan waktu yang berbeda dilakukan untuk melihat perubahan morfologi Gunung Semeru. Hasil perbandingan kemudian didelineasi dan divalidasi dengan citra Sentinel-2 sehingga didapatkan peta zona bahaya awan panas Gunung Semeru. Hasil peta zona bahaya awan panas menggambarkan awan panas guguran sekitar 15,2 km dari puncak, dengan luas area terdampak mencapai 5,5 km2. Area tersebut digunakan sebagai dasar koreksi peta zona KRB III tahun 1996 dan sudah sesuai dengan peta zona KRB III tahun 2021 yang ditetapkan oleh Badan Geologi Kementerian Energi dan Sumber Daya Mineral.
Fast Dispersion-Curve Inversion using Automatic Differentiation Gradient-Based Calculation Irnaka, Theodosius Marwan; Hartantyo, Eddy
Makara Journal of Science Vol. 29, No. 4
Publisher : UI Scholars Hub

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Abstract

Surface wave inversion is a crucial technique in geophysics for subsurface imaging. However, traditional methods can be computationally intensive, especially for complex models. This study introduces automatic differentiation (AD) as an efficient alternative to finite difference (FD) methods for gradient calculation in surface wave inversion. We compare AD and FD methods using three synthetic examples of varying complexity. Our results demonstrate that AD is significantly faster, with speed improvements of 3 to 12 times over FD, depending on model complexity. Moreover, AD requires up to 3 times less memory than FD. In terms of accuracy, AD provides gradient calculations that are exact up to machine precision, while FD is subject to truncation errors. This improved accuracy translates to more reliable inversion results, particularly for complex models. The efficiency and accuracy gains of AD are especially beneficial for gradient-based inversion methods in geophysics, where computational resources often limit the scale and complexity of problems that can be addressed. Our findings suggest that integrating AD into gradient-based inversion methods could significantly enhance subsurface imaging techniques across various geophysical applications.
Co-Authors Budiarti, Dyah Retno Darmawan, Herlan Eddy Hartantyo