文章基本信息

标题：Predicting Factors Affecting Preparedness of Volcanic Eruption for a Sustainable Community: A Case Study in the Philippines
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作者：German, Josephine D. ; Redi, Anak Agung Ngurah Perwira ; Ong, Ardvin Kester S. 等
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2022
卷号：14
期号：18
页码：1-24
DOI：10.3390/su141811329
语种：English
出版社：MDPI, Open Access Journal
摘要：Volcanic eruption activity across the world has been increasing. The recent eruption of Taal volcano and Mt. Bulusan in the Philippines affected several people due to the lack of resources, awareness, and preparedness activities. Volcanic eruption disrupts the sustainability of a community. This study assessed people’s preparedness for volcanic eruption using a machine learning ensemble. With the high accuracy of prediction from the ensemble of random forest classifier (93%) and ANN (98.86%), it was deduced that media, as a latent variable, presented as the most significant factor affecting preparedness for volcanic eruption. This was evident as the community was urged to find related information about volcanic eruption warnings from media sources. Perceived severity and vulnerability led to very high preparedness, followed by the intention to evacuate. In addition, proximity, subjective norm, and hazard knowledge for volcanic eruption significantly affected people’s preparedness. Control over individual behavior and positive attitude led to a significant effect on preparedness. It could be posited that the government’s effective mitigation and action plan would be adhered to by the people when disasters, such as volcanic eruptions, persist. With the threat of climate change, there is a need to reevaluate behavior and mitigation plans. The findings provide evidence of the community’s resilience and adoption of mitigation and preparedness for a sustainable community. The methodology provided evidence for application in assessing human behavior and prediction of factors affecting preparedness for natural disasters. Finally, the results and findings of this study could be applied and extended to other related natural disasters worldwide.
关键词：volcanic eruption; artificial neural network; random forest classifier; natural disaster; machine learning algorithm