I have been involved in many bird strike investigations, and in every one, I have seen a pattern:
an experienced crew, a routine mission, and an impact that should not have happened. Many of
these investigations resulted in valuable lessons being overlooked. The aircraft is retrieved, and a
report is filed. However, the data collected is often forgotten, buried in rarely visited databases.
This is the paradox of BASH data (Bird/Wildlife Aircraft Strike Hazard). We have been keeping
strike data for years, but seldom do we fully capitalize on it. The data exists, but we’re not using it to
its maximum capacity. That underuse is usually the result of several constraints, including limited
access to data, lack of training on how to assess and use the information, and lack of standardized
reporting formats. The result is that key insights are locked up and not easily shared across
enterprises. This year’s U.S. Aviation Wildlife Management Conference in Cleveland, Ohio,
highlighted this shortfall. Wildlife strikes remain a significant concern to flight safety.
In military flight training, strikes have even more serious consequences. Low altitude flights,
high mission frequency, and predictable flight paths create training base exposure to wildlife. When
a strike means a change of route or delays in training and operational readiness, the cost is more
than just financial. Thus, AI-powered forecasting increases the value of data for addressing these
risks. One Air Force training base last year, for example, used an AI-powered system that ingested
past strike data, seasonal bird migratory patterns, and live radar feeds to predict an elevated risk of
bird activity near a main flight corridor. In response, the base temporarily modified takeoff times and
flight paths, leading to a dramatic drop in bird strike incidents during the high-risk period. Artificial
intelligence is not meant to replace the wildlife professional but rather to augment that individual’s
experience with predictive intelligence.
That’s the idea behind Avigilance FeatherWatch. The system translates wildlife strike data into
easy-to-understand risk insights, helping BASH teams spot problems early and take preventative
action. All these solutions come together today. Avian radars track near-misses, drones monitor
species and their movements, and local experts supplement the program with insights raw data alone
cannot deliver. We must use these tools and act quickly on what we learn.
That is a common challenge. Absence of standard data fields for global BASH reporting limits
risk prediction. But small steps toward standardization can be meaningful. One early step
organizations could take is to standardize a small set of key data fields, such as date, location, species,
altitude and phase of flight, across all reports. Sharing best practices for reporting formats among
bases and agencies would also make the data more consistent and useful. But the first step is not to
build a new system but to appreciate the value of the data we already have. The future of wildlife
collision prevention will be evidence-based, predictive, and collaborative. Now it's time to think of
our databases as valuable sources of information.De
References
Altringer, L., Begier, M. J., Washburn, J. E. & Shwiff, S. A. (2024). Estimating the impact of airport
wildlife hazards management on realized wildlife strike risk. Scientific Reports 14.
https://doi.org/10.1038/s41598-024-79946-3
Yiu, C. Y., Li, W.-C., Ng, K. K. H., Chi, C.-F. & Schiefele, J. (2026). Enhancing aviation safety with artificial intelligence: A systematic literature review on recent advances, challenges and future perspectives. Advanced Engineering Informatics 71(B), 104378. https://doi.org/10.1016/j.aei.2026.104378
Washburn, B. E., Maher, D., Beckerman, S. F., Majumdar, S., Pullins, C. K. & Guerrant, T. L. (2022).
Monitoring Raptor Movements with Satellite Telemetry and Avian Radar Systems: An Evaluation for
Synchronicity. Remote Sensing 14(11). https://doi.org/10.3390/rs14112658
(n.d.). Aviation Safety Reporting System (ASRS) - About ASRS Data. ASRS - About ASRS Data.
