Pemanfaatan Data Alos PALSAR Untuk Etimasi Pergerakan Tanah Kota Padang Upaya Mitigasi Bencana Longsor
DOI:
https://doi.org/10.25077/jfu.9.1.93-99.2020Abstract
Telah dilakukan penelitian untuk mendeteksi besar pergerakan tanah sebagai faktor pendorong penyebab terjadinya bencana longsor di Kota Padang. Penelitian ini menggunakan data penginderaan jauh yakni data citra ALOS PalSAR tahun 2008 sampai 2009. Metode yang digunakan dalam pengolahan adalah Differential Interferometry Synthetic Radar (DInSAR). Metode ini dapat mengamati pergerakan tanah terutama pada daerah perbukitan dengan ketelitian sentimeter. Hasil penelitian menunjukkan besar pergerakan tanah untuk wilayah di Kota Padang berkisar antara 0,33- 3,04 cm/tahun. Dari 11 kecamatan di Kota Padang, lima diantaranya yakni Kecamatan Pauh, Padang Selatan, Bungus Teluk Begalung, Koto Tangah dan Kuranji mengalami pergerakan atau pergeseran tanah yang cukup besar dari kecamatan lainnya yakni berkisar antara 0,825- 2,31 cm/tahun. Besarnya pergerakan tanah tersebut menyebabkan lima kecamatan di atas sering mengalami bencana tanah longsor dengan kategori cukup rawan.
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Research has been conducted to detect the magnitude of land movement as a driving factor for the occurrence of landslides in the city of Padang. This study uses remote sensing data namely ALOS PalSAR image data from 2008 to 2009. The method used in processing is Differential Interferometry Synthetic Radar (DInSAR). This method can observe the movement of the soil, especially in hilly areas with sub-centimeter accuracy. The results showed the amount of land movement for the area in Padang City ranged from 0,33 to 3,04 cm /year. Of the 11 districts in the city of Padang five of them namely the District of Pauh, South Padang, Bungus Teluk Begalung, Koto Tangah and Kuranji experienced substantial land movements or shifts from other districts which ranged from 0,825 to 2,31 cm /year. The magnitude of land movements and the high level of rainfall causes the five districts often experience landslides in quite vulnerable categories.
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