Machine learning remote sensing using the random forest classifier to detect the building damage caused by the Anak Krakatau Volcano tsunami

Machine learning remote sensing using the random forest classifier to detect the building damage caused by the Anak Krakatau Volcano tsunami

AbstractIn Indonesia, tsunamis are frequent events. In 2000–2016, there were 44 tsunami events in Indonesia, with financial losses reaching 43.38 trillion. In 2018, a tsunami occurred in the Sunda Strait due to the eruption of the Anak Krakatau Volcano, which caused many fatalities and much building...

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Bibliographic Details
Main Authors: Riantini Virtriana, Agung Budi Harto, Fiza Wira Atmaja, Irwan Meilano, Kamal Nur Fauzan, Tania Septi Anggraini, Kalingga Titon Nur Ihsan, Fatwa Cahya Mustika, Wulan Suminar
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Geomatics, Natural Hazards & Risk
Subjects:
Building damage detection
machine learning
random forest
remote sensing
tsunami
Online Access:https://www.tandfonline.com/doi/10.1080/19475705.2022.2147455

Internet

https://www.tandfonline.com/doi/10.1080/19475705.2022.2147455

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