Seamless Weather Data Integration in Trajectory-Based Operations Utilizing Geospatial Information - Sang-Il Kim; Donghyun Jin; Jiyeon Kim; Do-Seob Ahn; Kyung-Soo Han (Remote Sensing)
In this study, a 4D trajectory weather (4DT-Wx) prototype system was developed and evaluated for effective weather information integration in trajectory-based operation (TBO) environments. The system has two key distinguishing features: multi-model-based trajectory services and buffer zone information provision. We constructed a distributed processing system using Apache Spark, enabling the efficient processing of large-scale weather data. The performance evaluation demonstrated excellent scalability and efficiency in processing large-scale data. An analysis of the buffer configurations highlighted that buffer zone information is valuable in decision-making processes and has the potential to enhance the system performance. The system’s practical applicability is presented through visualizations of the extracted weather information. This system is expected to enhance aviation safety and operational efficiency, providing a foundation for addressing increasingly complex weather conditions and flight scenarios in the future. The approach presented in this study marks a significant step toward effective TBO implementation and the advancement of future air traffic management. The evaluation of the 4DT-Wx system analyzed the accuracy of weather data processing and the performance of distributed processing, finding that the temperature (T) estimation had the highest accuracy, and that the parallel processing using Apache Spark was most effectively modeled by Ahmed et al.’s model. The findings suggest the potential for further optimization in integrating various weather models and developing algorithms to enhance their utilization.