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With the rapid development of the global aviation industry, the number of aircraft flying in the airspace has continuously increased. Although aviation safety has been improved in the last several decades, many general aviation and a few commercial aviation accidents occur every year, resulting in fatalities and significant economic loss. Aircraft crash accidents not only cause fatalities of crew members and passengers onboard, but also seriously affect people and property on the ground, especially if the crashed aircraft falls into dense urban areas. However, unlike emergencies caused by natural disasters such as floods, hurricanes, or a terrorist attack, very little research looked into the potential consequences of aviation accidents to people and property on the ground from the view of urban planning and emergency management. The object of this study is to propose a model for identifying potential ground risk areas of aviation crash accidents. Different from studies in existing literature, actual flight trajectories obtained from automatic dependent surveillance—broadcast (ADS-B) data was introduced in this study and incorporated in modeling development. With the trajectory information, a GIS density analysis method was applied to obtain a regional aircraft flight-path line density distribution map and to model crash trajectories of aircraft falling to the ground if a crash occurred or aircraft malfunctioned in the air. Combining relevant socio-economic factors that are sensitive to disasters, a ground potential risk mapping model for aircraft crashes was built. Risk areas were divided into five categories indicating the crash severities of potential aviation crash-caused impacts. To demonstrate the research approach, the State of Florida is used as an example. The outcomes of the proposed model can be used by emergency management departments to develop management plans for better responding to potential risks and provide decision support for city managers on zoning and land use planning.

Research on potential ground risk regions of aircraft crashes based on ADS-B flight tracking data and GIS