Hundreds of near-misses between drones and aircraft revealed

Category: Best data-driven reporting (small and large newsrooms)

Country/area: United Kingdom

Organisation: i, The Yorkshire Post, The Scotsman, Sunderland Echo, Portsmouth News, and many more.

Organisation size: Big

Publication date: 26/01/2019

Credit: Claire Wilde, Flourish map by Tim Hopkinson, additional reporting by Dean Kirby, Alison Bellamy

Project description:

Anyone who had their holiday plans disrupted during runway shutdowns at Gatwick and Heathrow last winter knows the havoc drones can wreak on air travel.

But did you know pilots had previously reported hundreds of near-collisions with the devices in UK skies?

That’s one of the frankly alarming findings of my data-led investigation into the growing number of near-misses between drones and aircraft being reported to officials.

Local versions of this story were run across dozens of JPIMedia’s regional and local news titles.

Impact reached:

I produced a story pack as part of my role running the JPIMedia Data Unit. 

The investigation ran in more than 60 JPIMedia titles.

This included national newspaper the i, which was also one of a number of titles to run an accompanying op-ed article about the issue.

Coverage across the UK included three front-page splashes, nearly 20 double-page spreads and numerous op-eds.

The case studies I provided proved particularly hard-hitting. 

There was the paraglider in Derbyshire left terrified after an unknown drone pilot persistently flew a quadcopter just feet away from him in flight, seemingly to obtain film footage but threatening to collide with the thin canopy-to-harness lines keeping him safe.

There was also the drone flown deliberately over the centre of Gatwick’s runway which nearly hit an Airbus A321 coming into land, a full three years before the chaos caused at the airport before Christmas 2018.

Techniques/technologies used:

The UK Airprox Board publishes on its website a basic spreadsheet listing each of the country’s near-misses involving drones and aircraft.

I used this as a starting point for my project, delving into the reports of each individual incident.

These are irritatingly published online in a variety of formats, from PDF to web table.

I scraped web tables using Google Sheets’ importHTML function and converted PDFs to machine-readable format using online converter services to build the basic spreadsheet up into an information-rich database. 

By doing this, I could begin adding in crucial details from individual incident reports. Was the aircraft involved a passenger plane? Was the drone being flown in restricted airspace? What was the pilot’s account of what happened?

I then took the coordinates of each incident and used these to determine which UK county they had happened in. This allowed me to reveal how many near-misses had happened in each county and region of the UK.

The full reports on each incident are published online, using hyperlinks which are formulaic in nature.

This allowed me to add to my spreadsheet a column giving the hyperlinks to each report. That way, a local reporter wanting to read more about a given incident could simply click through.

Using data given on the severity of each incident, as well as pilot accounts given in the full reports, I identified some of the most dramatic near-misses and turned them into case studies, also writing interviews with experts and background articles.

My colleague Tim Hopkinson used the coordinate data to create a Flourish map showing how the near-misses have been increasing in number over time. He also produced two JPG graphics.

What was the hardest part of this project?

Gathering open data spread across a variety of formats and using it to build my own database was certainly far more time-consuming than simply downloading a spreadsheet. However, here it gave readers of JPIMedia titles across the UK a real understanding of how a growing national issue was affecting their local area.

What can others learn from this project?

This investigation relied on open data that was hard to access and spread across a variety of sources and formats. By bringing it all together, I could shed new light on an issue that was high in the news agenda at the time, without having to rely on Freedom of Information requests.

This project demonstrates the value of combining data sources to alow for new analyses and also of learning skills such as web scraping to access open data.

The work of the JPIMedia Data Unit, of which this was the first project, shows how data can be used to generate stories of national interest but also numerous stories of local interest using one dataset.

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