Integrating Probabilistic Airborne Dispersion and Geospatial Vulnerability Assessment for Cascading Urban Radiological Hazards
Reno Sudibyo
Indonesian Agency for Meteorological, Climatological and Geophysics, Kemayoran, Jakarta, Indonesia; and Disaster Management Study Program, Faculty of National Security, The Republic of Indonesia Defense University, Bogor, Indonesia
Pujo Widodo
Disaster Management Study Program, Faculty of National Security, The Republic of Indonesia Defense University, Bogor, Indonesia
Syamsul Maarif
Disaster Management Study Program, Faculty of National Security, The Republic of Indonesia Defense University, Bogor, Indonesia
Anwar Kurniadi
Disaster Management Study Program, Faculty of National Security, The Republic of Indonesia Defense University, Bogor, Indonesia
Demetrius Christian Hasaro
Indonesian Agency for Meteorological, Climatological and Geophysics, Kemayoran, Jakarta, Indonesia; and Sepuluh Nopember Institute of Technology, Surabaya, Indonesia
DOI: https://doi.org/10.19184/geosi.v11i2.60012
Abstract
Cascading airborne hazards in densely populated metropolitan areas pose major challenges for disaster risk reduction (DRR). This study developed a probabilistic geospatial framework to assess potential airborne radiological hazard propagation in the Bandung metropolitan area, Indonesia, under a hypothetical Iodine-131 (I-131) release scenario. Ensemble-based Gaussian puff simulations driven by ERA5 meteorological data were integrated with probabilistic exceedance mapping, demographic vulnerability analysis, district-level spatial aggregation, and healthcare infrastructure exposure assessment using Geographic Information System (GIS) approaches. The results identified elongated airborne exposure corridors across interconnected metropolitan districts within the Bandung Basin. High probabilistic exposure zones were concentrated near the southern urban source area and extended toward northern urban sectors. District-level analysis revealed that densely populated sub-districts and several healthcare facilities, including major hospitals, were located within elevated exposure zones. The study demonstrates the potential of probabilistic geospatial modelling to support uncertainty-aware urban DRR planning in rapidly urbanizing metropolitan environments.
Keywords:cascading disaster; airborne radiological hazard; probabilistic exceedance mapping; GIS; urban disaster risk reduction; Iodine-131