A Geospatial Approach to Modeling Airspace Risk Factors

Abstract

The airspace environment is a system that is expected to continue increasing in complexity with the projected growth of air traffic volumes and the introduction of new types of air vehicles and operations such as uncrewed aircraft. This increase in complexity brings a need for investigating and developing new models of airspace environments as a means of better understanding and managing their constituent parts. This paper presents a methodology for creating a geospatial model of complex airspace environments which can be used to study any geospatially distributed entity that is part of these systems. The methodology leverages Discrete Global Grid Systems (DGGS), a Geographic Information Systems framework often utilized in the fields of geography and urban planning. The usefulness of the model is demonstrated using two case studies investigating the risk factors associated with weather and mid-air collisions in an airspace region of interest. Since such a model needs to be able to work for any type of air vehicle and airspace region in a fully three-dimensional model capable of performing time-varying analysis in a computationally efficient manner, a rudimentary geospatial airspace risk model was also developed which satisfies these requirements. Weather radar data from the National Oceanic and Atmospheric Administration and air traffic data from the OpenSky Network were collected and integrated in the geospatial model and the geospatial airspace risk model was used to calculate the risk of collisions for geospatially distributed points in the airspace for four scenarios of increasing airspace complexity. The results from these four scenarios demonstrate that the proposed methodology can be used to study the risk associated with spatially distributed risk factors for different points in the airspace for any type of air vehicle and airspace region of interest in a fully three-dimensional model that can perform time-varying analysis in a computationally efficient manner.