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Detail

An Artificial Intelligence Application for Post-Earthquake Damage Mapping in Palu, Central Sulawesi, Indonesia

Lebih Lengkapnya : https://www.mdpi.com/1424-8220/19/3/542
  • Author : Mutiara Syifa (Division of Science Education, Kangwon National University, Chuncheon-si, Gangwon-do 24341, Korea), Prima Riza Kadavi (Division of Science Education, Kangwon National University, Chuncheon-si, Gangwon-do 24341, Korea), Chang-Wook Lee (Division of Science Education, Kangwon National University, Chuncheon-si, Gangwon-do 24341, Korea)
  • DOI : 10.3390/s19030542

Abstrak

A Mw 7.4 earthquake hit Donggala County, Central Sulawesi Province, Indonesia, on 28 September 2018, triggering a tsunami and liquefaction in Palu City and Donggala. Around 2101 fatalities ensued and 68,451 houses were damaged by the earthquake. In light of this devastating event, a post-earthquake map is required to establish the first step in the evacuation and mitigation plan. In this study, remote sensing imagery from the Landsat-8 and Sentinel-2 satellites was used. Pre- and post-earthquake satellite images were classified using artificial neural network (ANN) and support vector machine (SVM) classifiers and processed using a decorrelation method to generate the post-earthquake damage map. The affected areas were compared to the field data, the percentage conformity between the ANN and SVM results was analyzed, and four post-earthquake damage maps were generated. Based on the conformity analysis, the Landsat-8 imagery (85.83%) was superior to that of Sentinel-2 (63.88%). The resulting post-earthquake damage map can be used to assess the distribution of seismic damage following the Palu earthquake and may be used to mitigate damage in the event of future earthquakes. Show More

Detail

  • Tahun :2019
  • Tipe Publikasi :Penelitian
  • Tanggal Publikasi :
  • Sumber :caribencana