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Education and Disaster Vulnerability in Southeast Asia: Evidence and Policy Implications
This article summarizes the growing theoretical and empirical literature on the impact of education on disaster vulnerability with a focus on Southeast Asia. Education and learning can take place in different environments in more or less formalized ways. They can influence disaster vulnerability as the capacity to anticipate, cope with, resist, and recover from natural hazard in direct and indirect ways. Directly, through education and learning, individuals acquire knowledge, abilities, skills and perceptions that allow them to effectively prepare for and cope with the consequences of disaster shocks. Indirectly, education gives individuals and households access to material, informational and social resources, which can help reducing disaster vulnerability. We highlight central concepts and terminologies and discuss the different theoretical mechanisms through which education may have an impact. Supportive empirical evidence is presented and discussed with a particular focus on the role of inclusiveness in education and challenges in achieving universal access to high-quality education. Based on situation analysis and best practice cases, policy implications are derived that can inform the design and implementation of education and learning-based disaster risk reduction efforts in the region.
Multi-temporal analysis of forest fire probability using socio-economic and environmental variables
As most of the forest fires in South Korea are related to human activity, socio-economic factors are critical in estimating their probability. To estimate and analyze how human activity is influencing forest fire probability, this study considered not only environmental factors such as precipitation, elevation, topographic wetness index, and forest type, but also socio-economic factors such as population density and distance from urban area. The machine learning Maximum Entropy (Maxent) and Random Forest models were used to predict and analyze the spatial distribution of forest fire probability in South Korea. The model performance was evaluated using the receiver operating characteristic (ROC) curve method, and models’ outputs were compared based on the area under the ROC curve (AUC). In addition, a multi-temporal analysis was conducted to determine the relationships between forest fire probability and socio-economic or environmental changes from the 1980s to the 2000s. The analysis revealed that the spatial distribution was concentrated in or around cities, and the probability had a strong correlation with variables related to human activity and accessibility over the decades. The AUC values for validation were higher in the Random Forest result compared to the Maxent result throughout the decades. Our findings can be useful for developing preventive measures for forest fire risk reduction considering socio-economic development and environmental conditions.