Aerodrome Geodata & The Aerodrome Local Ownership Plan (ALOP)

In light of COVID-19, partly because of it or exacerbated by it, the Australian Government has published an issues paper on the Future of Australia’s Aviation Sector with public consultation open until 13 November 2020. The paper is looking at a range of issues and not just COVID-recovery-related topics. They are also looking at regional access, airport regulation and funding.

One section in particular caught my eye and that was looking into the Aerodrome Local Ownership Plan (ALOP) and possible changes designed to free-up local government options. There is an interesting comment in this section that I wanted to explore using data-driven decision making (D3M) and some pretty cool data-visualisation tools that I have recently discovered.

Background: The Aerodrome Local Ownership Plan

Back in the day, aerodromes were usually built by the federal government. But, pretty quickly, the federal government started handing these facilities over to local government bodies and some local companies to operate - initially with assistance. By the early 1990s, full responsibility for the operation and funding of these aerodromes was handed over to the local operator.

However, they were not free to do whatever with these facilities. The ALOP transfer deeds imposed the obligation to continue to operate the aerodrome. These aerodromes are known as (former) ALOP aerodromes and they cover a wide range of facilities from very remote and tiny airstrips to large airports.

The paper does not list the 244 ALOP aerodromes but a publication from the Australian Airports’ Association does provide a list of ALOP aerodromes but this list includes 261 aerodromes. Three aerodromes on the AAA list have been closed since they were handed over. For our data analysis today, I’ll use this AAA list.

Issue at Hand: Decision Making

The diversity I mentioned a moment ago is the crux of the issue. Some of these aerodromes are bustling going concerns that contribute to the local economy through jobs, freight, tourism, business, etc. And others run at a financial loss putting strain on the local government.* These aerodromes do not and/or are considered unlikely to receive a commercial air service.

The paper is suggesting that it is time to consider options for these aerodrome operators to make decisions on their aerodrome’s future. It doesn’t say it but it seems pretty clear that the government is considering removing the obligation to operate the aerodrome and thus free up the land for non-aviation purposes.

The statement that set me on this data-driven decision making path was that:

In some parts of Australia, multiple aerodromes are also in reasonably close proximity to one another, and do not have sufficient demand to justify RPT services.

Now, Australia is a really big country and 250-odd aerodromes is not a lot.** So, I wondered how many of these ALOP aerodromes are within 50km of another aerodrome?

Introducing Python

Python is a computer programming language that is good at communicating with different data sources, manipulating the data to “talk” to each other and then create amazing visuals. It is particularly good at geographical data (geodata). There are some great free tools available including Google Colab, which doesn’t require any installation at all - it is completely online.

I have found that there is a little bit of a learning curve to get over but after a day or two of training, there is plenty of free help on the Internet to keep your skills developing. Recently, I was lucky enough to attend a course through my university and with some well-worded searches, I’ve been able to pull together some interesting programs over the last couple of months.

It is on this platform that I would seek to answer my question above.

The Data

There are a couple of places you can get data on Australian aerodromes online. The ICAO iStars system is pretty good and provides up to 100 “calls” to their database per month for free. I used a combination of sources to create a file of 393 aerodromes.

This file included the ALOP aerodromes from the AAA publication and any other certified aerodrome that was not ALOP. In addition to the aerodrome name and ALOP status, I also captured basic ownership data (local government, other government, resource company, federally-leased or private company), regulatory status (certified or not certified) and its geo-location (latitude and longitude).

There was a bit of manual work here to make sure I had pretty good data. I wouldn’t use it for academic analysis but for this project, I think it is pretty good.

Crunching the Numbers

With my data uploaded into Google Drive, I switched over to programming mode.

Now, my programming skills are somewhere between rudimentary and intermediate. I know I am not using the inbuilt power of Python to do the heavy lifting as I tend to program as if I was manually doing the work. I gain, of course, by not having to do the work a thousand times but I am sure there is a way to get it to run faster if I thought like a computer.

If you are interested, here is my code in a text file or here is a picture of what it looks like, if it’s not your thing.

In short, the program calculates the distance from every ALOP aerodrome to every other aerodrome and if that distance is less than 50km, it adds it to the list. If an ALOP aerodrome is within 50km of more than one aerodrome, it adds the result each time.

Plotting

Okay, I get it. If you’re not into programming, the bit above is boring. But here comes the cool part - an interactive, colour-coded map of all the aerodrome locations and which ones have nearby aerodromes.

Analysis

The cool plot isn’t really the answer to the question. The answer is in the data that created it. That data was also spat out as a separate file and with the help of the map, I could analyse the results of the program to see how valid they were. Because there are other factors to consider beyond the direct distance as outlined below.

Overall, there are 78 ALOP aerodromes within 50km of another aerodrome (not including primarily military facilities). That’s about 30% and worthy of further analysis.

I did a line-by-line review of each relationship using Internet sources and my previous experience to have a guess at which aerodromes might want to close. I looked whether the nearby aerodromes served the same niche, whether they would be available (as in not a private mine site aerodrome), and whether the owner had been putting in any effort or resources recently.

I flagged 24 aerodromes that could look at closure, if released from their ALOP obligations. That is approximately 10% of the original list. I looked at more than just air transport services. Especially where two aerodromes worked together to provide separation of aviation activities that might be in conflict if at the same aerodrome.

Have Your Say

If you have made it this far into this blog post, you are probably interested in Australia aviation policy and I would recommend you check out the issues paper and have your say. I’m not sure that ALOP obligations are necessarily big on the list of issues with our industry but there are other discussion pints worthy of input from all stakeholders.

Comments close on 13 November 2020 and can be sent to aviationconsultation@infrastructure.gov.au, or in hard copy, addressed to:

Attention:
Director, Strategic and Economic Policy Projects
Data, Analytics and Policy Division
GPO BOX 594
CANBERRA ACT 2601

And you can always have your say about my blog post in the comment section below.

* One such aerodrome would be Kempsey, who made the argument in a court case that they did not owe a duty of care to a pilot who crashed into a kangaroo because they are a public authority with limited resources.

** There are over 5,000 in the United States.

Image credit: Catarina Sousa (via Pexels)