The Economist's Ukraine War-fire (daily Update)

This data is updated daily from the Economist's Ukraine war-fire GitHub repository: https://github.com/TheEconomist/the-economist-war-fire-model

See the latest data, updating several times daily, here: Tracking the Ukraine war: where is the latest fighting?

Limitations

Many war events do not produce heat at a level detectable by the satellite systems we use, and even if they do, events may go unrecorded because they happen under cloud cover, which regularly obscures much of the country from such satellite monitoring, or have cooled by the time the satellites pass overhead. This means not all war events are detected.

Moreover, our statistical method classifying events as war-related (or not war-related) is probabilistic. This means that it will sometimes categorise events which were unrelated to the war as war-related, and more frequently, given our strict thresholds, classify events related to the fighting as insufficiently abnormal to be labelled war-related.

Finally, we cannot currently produce accurate classifications of war-related events during periods of extreme heat (defined as when average temperatures are higher than the upper end of the 95% confidence interval of temperatures in Ukraine). During such periods (so far, only once, from April 4th to April 11th, 2023), no events are classified as war-related.

Variables in main exports

The files ukraine_fires.csv and ukraine_war_fires.csv contain the following columns, with each row being a fire event:

LATITUDE: Latitude of fire event in decimal degrees
LONGITUDE: Longitude of fire event in decimal degrees
date: Date of fire event in "year-month-day" format. E.g. "2023-09-15"
ACQ_TIME: Time of data acquisition by satellitte in 24-hour format. I.e. 2205 equals 10:05 pm
id_w_time: ID of cell fire is detected in (given by longitude, latitude, day of year, and year, separated by underscores)
id: ID of cell fire is detected in (given by longitude, latitude, separted by underscore)
x: Longitude of cell fire is detected in (decimal degrees - midpoint)
y: Latitude of cell fire is detected in (decimal degrees - midpoint)
year: Year
time_of_year: Day of year (January 3rd = 3)
fire: Whether fire was detected at this location at this time. (Always 1 in these exports)
pop_density: Average population density of cell fire was detected in
city: City fire was detected in, if assessed (generally not calculated)
in_urban_area: TRUE if fire was detected as being within an urban area, otherwise FALSE
pop_exact: Population density at fire location. Note distinction between pop_exact (fire location) and pop_density (cell fire was detected within)
excess_fire: Number of fires in cell beyond prediction for that cell for that date, assuming no cloud cover
predicted_fire: Number of fires in cell predicted for that cell for that date, assuming no cloud cover
fire_in_window: Observed fires in that cell on that date
war_fire: Whether this specific fire is assessed as war-related by the model
sustained_excess: Whether this cell has seen sustained excess fire activity. This is used by the model to assess whether activity there is likely to be war-related
id_big: Location rounded to nearest degree longitude and latitude, given as rounded longitude and latitude separated by an underscore
length_of_war_fire_area: Number of separate days with fires assessed as war-related in area, defined by rounding locations to nearest degree longitude and latitude
war_fire_restrictive: Whether this specific fire was assessed as abnormal. (The model classifies fires taking place in areas immediately following abnormal fire activity as probably war-related, even if they are not themselves classified as abnormal)
in_ukraine_held_area: Whether fire took place in area assessed as Ukraine-controlled. Specifically, whether it took place within Ukraine but not within areas assessed as controlled by Russia by the Institute for the Study of War on the date in question
fires_per_day: Number of fires in Ukraine on date
war_fires_per_day: Number of fires classified as war-related in Ukraine on date
fires_per_day_in_ukraine_held_area: Number of fires in Ukraine on date in areas assessed as Ukraine-controlled
war_fires_per_day_in_ukraine_held_area: Number of fires classified as war-related in Ukraine on date
fires_per_day_in_russia_held_area: Number of fires in Ukraine on date in areas not assessed as Ukraine-controlled
war_fires_per_day_in_russia_held_area: Number of fires classified as war-related in Ukraine on date in areas not assessed as Ukraine-controlled

Historical versions

This model was first published on February 23th, 2023.

Acknowledgements

The Economist gratefully acknowledge helpful discussions with Daniel Arribas-Bel and Francisco Rowe of the University of Liverpool on the construction of training features and modelling approach.

If you have any suggestions or questions, please email sondresolstad@economist.com or open an issue.

Licence

This software is published by The Economist under the MIT licence. The data generated by The Economist are available under the Creative Commons Attribution 4.0 International License.

The data and files that we have generated from open sources are freely available for public use, as long as The Economist is cited as a source.

Suggested citation
The Economist and Solstad, Sondre (corresponding author), 2023. The Economist war-fire model. First published in the article "A hail of destruction", The Economist, February 25th issue, 2023.