Satellite launch traffic forecast based on the global Gross Domestic Product and constellation plans

Satellite launch traffic is an important input into space debris evolutionary models. Slight variations in launch traffic can have a large impact on the space landscape as a whole, since the number of satellites in orbit directly influences collision risk. In recent years the trend has been going towards employing satellite constellations such as Starlink. Information about planned constellations is publicly available and is used in this work to predict the future launch traffic. The 8 largest constellations launched so far and 35 future planned constellations are considered. For non-constellation launches instead economic time series methods such as the Seasonal Auto Regressive Integrated Moving Average model and the Long Short-Term Memory model are employed. It is shown that the Seasonal Auto Regressive Integrated Moving Average model clearly outperforms the Long Short-Term Memory model. The increase in launch traffic does not happen in a vacuum and is greatly influenced by outside factors such as the general economy. As a novelty, this work also includes the global Gross Domestic Product as an economic influence on the satellite launch traffic. Including the Gross Domestic Product as an influence in the launch traffic improved predictions by 53%. Combining both constellations and non-constellation, the yearly number of objects launched could reach up to 12,000. This huge number demonstrates the need for guidelines for future launches and mitigation measures. • Satellite launch traffic forecast for both constellation and non-constellation objects. • Deterministic forecast for constellation launches based on publicly available launch plans. • Time series analysis for non-constellation launches. • GDP included as an external factor to improve non-constellation launch predictions. • Three scenarios developed representing low, mean and high launch rates.