SATCAT Data Analysis

Since 1985,?Celestrak (https://celestrak.com/) releases free available data to the space community. Dr. T.S. Kelso started setting up a Bulletin Board System (BBS), delivering few datasets per day. Now the page has got more than 21,000,000 access, becoming a standard in space data distribution. Among other things (such as GP data in TLE format or Space Weather information files), Celestrak makes available the SATCAT (SATellite CATalog) file. It contains an historical list of all the man-made objects starting from 1957, as well as metadata like launch date, owner, object type or inclination.

These information allow space analysists to get an eye on historical evolution of the space flights or better understand the current trends of the modern space race. This article wants to investigate on the SATCAT catalog, trying to derive useful information out of it.

The Catalog Structure

The catalog is available at https://celestrak.com/pub/satcat.csv. Once downloaded, it can be opened using Excel or any text editor. For this analysis, I imported it into a Python dataframe and I removed few columns (not used for this analysis) from it. Here below you can see a depiction of catalog's content:

The most important variables to play with are the status code (marked with 'D' for decayed objects, the object type (enumerated as debris, payload or rocket body) and the available Keplerian elements and orbit related information. By arranging the proper queries, you'll be able to derive the data you need to improve your knowledge on the space situation.

At the time of writing, the SATCAT catalog is composed by 52497 objects, with 26934 objects (51.3%) decayed and 25563 objects (48.7%) still in orbit.

Historical Trend Analysis

First of all, I focused on the historical trend of the space population. To do this, I needed to remove from the data set of the objects marked as debris: as result, I've got 20011 distinct objects sent in space from 1957 (this number also includes rocket bodies). Grouping the new catalog's entries by year we can see a huge increment starting from 2020: this is due to the Starlink constellation deployment (about 2240 satellites at the time of writing).

Reversing the previous approach (keeping only the object marked as debris), we can also derive how many debris have been added to the catalog by year. Unfortunately, the SATCAT catalog refers to the launch date of the parent's object for the debris classification, and this makes difficult to derive a precise timeline for the debris generation. For example, in the next figure you can see the high peak in 1999. This is the result of the Chinese anti-satellite missile test happened in 2007. The debris generated from the event have been tagged accordingly with the launch date of the target satellite (FENGYUN 1C), which is 1999. Same happens for the COSMOS 1408 shootdown, happened in 2021 and whose debris have been classified in the 1982 (year of launch of the target satellite).

In-orbit Analysis

Removing the decayed items from the catalog allows an analysis on the in-orbit objects.

• Looking at the object types, you can see how about 56% of the in orbit population is due to debris, and just one third is performing in orbit operations. Unfortunately, this trend is largely increasing over time.
• US are leading the leaderboard when classifying the objects by owner. Russia has about one third of the asset owned by US, while other countries are running a small fraction of the active assets. Starlink constellation plays a big role in these statistics.

• Decomposing the catalog by orbit regime, we see how the LEO orbits are by far the most popular ones. This decomposition has been done by using the Keplerian elements data available for each entry in the catalog.

The video below shows the top three orbit regimes using an animation from STK:

Inclination & Period Analysis

Looking at the inclination, we can see as the 95 to 100 degrees bin contains more than 7000 objects. This is related to the Sun-Synchronous orbits, whose inclination is strictly related to the semimajor axis. Once again, the Starlink constellation plays a big role, representing the second most used inclination regime (about 55 degrees).

The orbit period is directly related to the orbit size. Looking at the bar chart below, we can see once how the LEO orbit is the most congested one. The 1400 minutes bin also contains HEO orbits, but the GEO ones are prevalent here.

As further consideration, may worth telling that a dynamic analysis may be done by collecting multiple SATCAT catalogs over time and checking for day-by-day differences. SATCAT is a treasure full of useful information than can open you eyes on what's happening just above us. Thanks to Dr. Kelso for making this possible!