Flood risk studies in Southeast Asia often treat physical exposure and socio-economic vulnerability as separate issues. That approach misses something important: in many places, socio-economic factors matter more than physical exposure in deciding who gets hit hardest. This study introduces the Socio-Economic Asymmetry...
P. Littidej, Jiradech Majandang, Benjamabhorn Pumhirunroj et al.· Symmetry· 0 citations
Northeast Thailand’s Chi-Mun River Basin is among Southeast Asia’s most flood-prone regions, experiencing annual monsoon inundation and extreme flood events that threaten community sustainability. Despite substantial investment in flood management infrastructure, community responses to flood hazards vary considerably,...
P. Littidej, Benjamabhorn Pumhirunroj, Donald Slack· Sustainability· 0 citations
This study developed and evaluated machine learning models for flood severity prediction within a hexagonal grid system under rainy season conditions in Maha Sarakham, Thailand and recommends XGBoost for operational forecasting due to its temporal stability, computational efficiency, and interpretability.
Narueset Prasertsri, P. Littidej, Benjamabhorn Pumhirunroj et al.· Sustainability· 1 citation
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