Estimating fireball luminous tracks using citizen observations

Ursa Astronomical Association (https://www.ursa.fi/english.html) (founded 1921) is the biggest astronomical association in Finland. By membership count (over 19000 members) it is also one of the largest scientific associations in the world. Ursa runs an observational database called “Skywarden” (or “Taivaanvahti” in Finnish). Citizen observations of many types of celestial phenomena are collected including fireballs.  The system is accessible both in English and Finnish. Ursa Astronomical Association also provides an umbrella organization for Finnish Fireball Network connecting scientists from different universities, camera station owners and citizen scientists.

The database contains about 20000 fireball observations in May 2025 (the system was established in 2011). Quite many of those observations are linked to the same fireball event even though there are also sporadic cases. The authors have developed an algorithm to group the fireballs belonging to a certain event. The algorithm runs automatically in the background. Altogether there are a few hundred cases of fireball events.

The Skywarden system had a crucial role in finding the Annama meteorite (Trigo-Rodriguez et al.). The video images posted to the database were used to determine the strewn field. In addition, a meteor on a hyperbolical track was identified from the user submitted images and the orbit of the meteor could be determined (Peña-Asensio et al.).

However, most of the observations in the database are without video images since they come from laymen. Usually, special hardware is required to retrieve images of meteors but nowadays surveillance cameras and dashcams do provide some material. In some cases, the citizen observations can provide auxiliary information to video images like if sound phenomena were observed. Daytime fireballs are rarely recorded since the special cameras are too sensitive during daylight. The authors wanted to investigate how well the citizen observations without any photos can be used to estimate the luminous track of the fireball.

The database collects information of the observer, date, location, duration of the phenomenon, bearing of the fireball, the apparent altitude, and the angle it came down. More information can be provided such as images, information on the sound phenomena etc. If the location is provided as a name, the system polls coordinate from Google Maps API. Skywarden provides data through its own API. It is possible to search for fireball events or displays and then fetch all the observations easily.

To analyze the data the data is fetched from Skywarden API. A Python Pandas based script preprocesses the data. All information that contains angular data (bearing, altitude, inclination angle) is added to the table. The data can then be exported in many formats like json, csv etc.

The authors developed two methods to analyze the data. The first one gives a crude estimate of the geographical location of the end of the luminous track only. For each observation pair the cross points of a major circle using bearings are calculated. Only those over Finland are preserved. The vector average of the point cloud is taken as the estimate. This is system is fast and is implemented as a web service that can calculate the estimate on the fly and visualize it on a map.

The authors developed also a second method that guesses a large set of the coordinates of the luminous track, then projects it to all observers and using least squares the best fit is then selected for the next round. This continues until the estimate isn’t improved significantly anymore. This method is slower and doesn’t give near real time results. However, it is possible to run in the background and thus provide an estimate for every fireball case automatically.

The Finnish Fireball Network does the estimation of the meteor tracks using video images. Some prominent fireballs with potential meteorite were used to compare the results obtained from the citizen observations only. The worst-case distance with the fast method was 73 km whereas with the least squares method the distance was 45 km. In average the quick method was off 44 km and the least squares method 26 km. A prominent fireball was seen in Vätsäri, Finnish Lapland on Nov 16, 2017.  In Fig. 1 the results are presented on a map.

Figure 1 Results of Vätsäri case (Nov 16, 2017) on a map (Map data copyrighted OpenStreetMap contributors and available from https://www.openstreetmap.org). Red arrow denotes the flight path estimated from video observations, green path is the least squares estimated flight path, blue is obtained using the quick algorithm. The ellipsoid is the video based estimated strewn field.

 

The results were surprisingly good even though alone they are not sufficient to justify a field trip. The least squares algorithm is rather easy to use with mixed set of citizen observations and video-based estimates. In some cases, there is only one video observation and augmenting with citizen data would give at least some idea of the luminous track.

The spherical Earth model was used so integrating ellipsoid model and DEM would probably be a good next step of development. Also, the bearings are presented in quite a coarse manner. Maybe a mobile phone app would be appropriate to mitigate this. It would also help to improve the accuracy of grouping of observations.

References:

Trigo-Rodríguez, J.M., Lyytinen, E., Gritsevich, M., Moreno-Ibáñez, M., Bottke, W. F., Williams, I., Lupovka, V., Dmitriev, V., Kohout, T. and Grokhovsky, V. 2015, Orbit and dynamic origin of the recently recovered Annama's H5 chondrite, Monthly Notices of the Royal Astronomical Society, vol. 449, iss. 2, May 11, pp. 2119–2127, doi: 10.1093/mnras/stv378.

Peña-Asensio, E., Visuri, J., Trigo-Rodríguez, J. M., et al. 2024, Oort cloud perturbations as a source of hyperbolic Earth impactors, Icarus, Vol. 408, doi: 10.1016/j.icarus.2023.115844.