What data visualization can tell us about laser strikes to make air travel safer
For people all over the world, November and December are traveling months. A great deal of that traveling is done in planes, and because it is winter in many parts of the world, we all tend to think a little more about air safety. And, even though safety at all times is the primary focus of any aviation experience, there are hazards that cannot be avoided or controlled, with the usual suspects being weather, mechanical issues and pilot errors.
A new category of hazard has emerged over the past few years: laser strikes. Strong lasers beamed from the ground at an airborne plane have caused an uproar due because they can impact the pilot’s vision in flight, either injuring him or at a minimum, cause disturbance to a smooth flight by blinding the pilot for a moment. In one week in 2015, 34 commercial flights reported to the FAA that lasers were pointed at them over New Jersey.
In 2015, to find out more about laser incidents, I uploaded the FAA laser strikes data set, which contains information regarding all reported laser strikes for the US from 2010 to 2014, into Watson Analytics. First of all, I wanted to find out which places have the highest amount of reported incidents. As soon as I clicked on the imported data set, the guided approach of the solution kicked in. Watson Analytics suggested avenues to explore without any prompting on my part. (Because I did this research in 2015, the data visualizations you will see are from the classic version of Watson Analytics).
Data visualization 1: Incidents by state
One of the insights Watson Analytics suggested for me was Total Incidents by State – exactly what I was looking for. As I clicked the recommended insight, Watson Analytics presented the information in a data visualization map that highlighted the key areas where the incidents took place over the years. I found with the help of Watson Analytics that California has the highest recorded incidents for laser strikes followed closely by Texas and Florida. The findings align with the general FAA research that laser strikes occur frequently in warmer weather with beach or resort communities.
Data visualization 2: Incident by city
Next, I wanted to drill down into the cities that report the highest incidents. My expectation was to find one of the cities in California as the major offender. However, when I changed my selection to city instead of state, I found, to my surprise, that the city of Phoenix had the highest number of laser strikes recorded over the last four years. An interesting and unexpected insight found by Watson Analytics.
Data visualization 3: Insight snippet showing total incidents by altitude
On the highlight bar on the top of the interface, Watson Analytics kept suggesting relevant insights as I conducted my own analysis. One of the snippets of insight was the breakdown of total incidents by altitude. There is a higher number of total incidents reported at lower altitudes than there are at higher altitudes. Whether this is because pilots are more affected by the laser at lower altitudes or that most lasers have a good reach only up to lower altitudes, Watson Analytics signaled an area that granted me a deeper view into my data.
Data visualization 4: Incident by color
I also wanted to find out whether lasers of a certain color were used more than others. So, I typed in my question, which asked Watson Analytics to show me total incidents by color. Watson Analytics provided a breakdown of all total incidents reported by color where green seemed to be the predominant color of laser used in laser strikes. That green was the prominent color is interesting because the human eye is much more sensitive to hues such as yellow and green at night and that often leads to temporary blindness or injury to the eyesight. Do offenders choose green lasers because they know this? Or do pilots report more incidents when encountering green laser because it is more disruptive to the flight and possibly injurious to pilots? By typing in a simple question, Watson Analytics helped me understand the signals in my data that could aid in uncovering the cause of why incidents of a certain color are much more highly reported than others.
Data visualization and discovery saved me a lot of time – and could help the FAA
In a matter of a few minutes, Watson Analytics helped me uncover some of the key insights in my data, such as:
- Where laser strikes are more prominent
- Which altitudes pose the greatest threat of disruption in flight should a laser strike occur
- Which colors are predominantly used in laser strikes
Data visualizations created automatically by Watson Analytics enabled me to quickly identify points of interest, validate my research and discover new insights in my data by means of simple interactions. You can imagine how this might help pilots, airlines and the FAA concentrate efforts to curtail laser incidents or reroute flights to areas where incidents are less likely to improve safety.
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