Code accompanying "Observing formation and early evolution of contrails formed by IAGOS aircraft using high-resolution LEO satellite imagery"
This repository contains a **Python toolkit for analyzing contrail formation and early evolution** by matching data from three sources: 1. **Aircraft Measurements** - Real-time measurements of temperature, humidity, and emissions from In-service Aicraft for a Global Observing System (IAGOS) commercial aircraft. 2. **Satellite Imagery** - High-resolution images from Low Earth Orbit (LEO) satellites (Sentinel-2 and Landsat). 3. **Weather Data** - meteorological data (ECMWF Reanalysis v5 ERA5). This repository contains a series of Python scripts to study the formation and early evolution of contrails produced by IAGOS aircraft using high-resolution LEO satellite imagery. The code aligns in space and time (*collocates*) the three datasets mentioned above, in order to understand when do contrails form and how they evolve in time, including their environmental impact. More specifically, the `./src/iagos_toolkit` contains scripts to: * load and process aircraft flight trajectories from ADS-B (automatic dependent surveillance) data; * calculate and retrieve atmospheric conditions at aircraft altitude and location; * process satellite imagery to detect and measure contrails. The notebooks provided in `./notebooks/` use the `./src/iagos_toolkit` to reproduce the results published in Woldhuis et al. (2026) (see **References**). In order to execute all notebooks, download the **full dataset** from the [4TU.ResearchData](https://doi.org/10.4121/2d66d65e-8041-4435-ab3c-0af3fdfc5d23) archive (see also **References**). Keep in mind the full dataset size is **+-50 GB**. To reproduce most paper results without the full dataset, the file `./data/landsat_sentinel_collocations_20260216.csv` can be used.
Observing formation and early evolution of contrails formed by IAGOS aircraft using high-resolution LEO satellite imagery