Dabakala fire, January 2022 Dabakala, Bouaké, Timbé
The fire started on 16 January 2022 in Dabakala, Côte d’Ivoire, and satellites saw it burning for 11 days. Copernicus’s global GWIS system rebuilt a burnt perimeter of 3,359 hectares from heat detections, spread across 3 municipalities.
It is the 5th largest in Valle Du Bandama since 2016 (of 102 with a page). Number 15 in Côte d’Ivoire in 2022, of 127.
Compare with…
- Burnt area
- 3,359ha
- GWIS perimeter (Copernicus)
- Duration
- 11days
- 16 Jan 2022 – 26 Jan 2022
- Municipalities hit
- 3
- sub-prefectures
- Started on
- 16 Jan
- 2022
- Heat detections
- 141
- in a single hotspot: 42 MW
- Danger at start
- 42
- Very high · FWI index
- Average daily power
- 76MW
- detected power per day, on average
Where it burned
How it evolved, day by day
Fire radiative power detected each day, in megawatts, and number of hotspots. The magenta bar marks the peak day.
The weather it burned in
It had gone more than two months without rain (1 mm or more) when it started.
This area had burned before
73% of the perimeter overlaps earlier fires recorded since 2016: 1,970 ha in 2016, 1,603 ha in 2018, 1,363 ha in 2019, 1,390 ha in 2020. Part of it burned more than once, so the yearly figures add up to more than the 2,454 ha that had burned before.
- 1,970 ha Bouaké fire, January 2016 2,909 ha in total; the hectares shown are those it shares with this fire
- 1,603 ha Dabakala fire, January 2018 2,371 ha in total; the hectares shown are those it shares with this fire
- 1,390 ha Dabakala fire, February 2020 1,560 ha in total; the hectares shown are those it shares with this fire
- 1,363 ha Dabakala fire, February 2019 2,371 ha in total; the hectares shown are those it shares with this fire
How big is it?
London boundary: geoBoundaries · Office for National Statistics (Open Government Licence v3.0).
Paris boundary: geoBoundaries · Institut national de l'information géographique et forestière (IGN-F) (Etalab Open License 2.0).
Madrid boundary: geoBoundaries · Open Data ESRI, IGN Central Registry of Cartography Area (CC BY 4.0).
Berlin boundary: geoBoundaries · Federal Agency for Cartography and Geodesy (dl-de/by-2-0).
This compares size, not location: both shapes are at the same scale, north up, centred on each other.
What happened to each town
-
Dabakala where it started2,802 ha reached on 16 Jan1.4 %
-
529 ha reached on 22 Jan0.3 %
-
47 ha0.1 %
Burnt area inside each municipality, from crossing the GWIS perimeter with administrative boundaries. The distance runs from the point marking the centre of each area to the nearest fire: staying a kilometre away does not mean it reached the houses.
People and buildings inside the perimeter
GHSL 2020Inside the perimeter there were about 0.52 hectares of built-up land and about 100 residents (GHSL 2020, satellite-based estimate).
This is an estimate on 100 m cells, made from satellite imagery and census data: it does not mean that homes burned or that anyone was harmed. The perimeter also contains land that never burned.
Source: Global Human Settlement Layer (GHS-BUILT-S and GHS-POP R2023A), European Commission Joint Research Centre (JRC), © European Union, CC BY 4.0. Sum inside the perimeter computed by WorldFires. human-settlement.emergency.copernicus.eu
The weather day by day
ECMWF ERA5 reanalysis at the fire location, the standard reference for past weather, and the Canadian Fire Weather Index (the same system Copernicus uses), computed by WorldFires from that data. Days after the fire run until the first rain.
Open-Meteo.com (CC BY 4.0) · Copernicus Climate Change Service (ERA5)
| Day | High | Min. humidity | Peak gust | Rain | Danger (FWI) |
|---|---|---|---|---|---|
| 16 Jan | 35.5 °C | 18 % | 31 km/h | 0.0 mm | Very high 42 |
| 17 Jan | 36.4 °C | 14 % | 20 km/h | 0.0 mm | Very high 44 |
| 18 Jan | 33.7 °C | 12 % | 35 km/h | 0.0 mm | Very high 44 |
| 19 Jan | 34.1 °C | 14 % | 29 km/h | 0.0 mm | Very high 45 |
| 20 Jan | 34.1 °C | 16 % | 29 km/h | 0.0 mm | Very high 45 |
| 21 Jan | 33.8 °C | 14 % | 30 km/h | 0.0 mm | Very high 46 |
| 22 Jan | 34.3 °C | 15 % | 32 km/h | 0.0 mm | Very high 46 |
| 23 Jan | 33.6 °C | 11 % | 27 km/h | 0.0 mm | Very high 47 |
| 24 Jan | 34.5 °C | 11 % | 31 km/h | 0.0 mm | Very high 46 |
| 25 Jan | 34.6 °C | 12 % | 34 km/h | 0.0 mm | Very high 48 |
| 26 Jan | 34.5 °C | 12 % | 26 km/h | 0.0 mm | Very high 47 |
| 27 Jan after | 35.0 °C | 20 % | 23 km/h | 0.0 mm | Very high 44 |
| 28 Jan after | 34.8 °C | 27 % | 24 km/h | 0.0 mm | Very high 39 |
| 29 Jan after | 35.1 °C | 21 % | 34 km/h | 0.0 mm | Very high 41 |
| 30 Jan after | 35.1 °C | 13 % | 31 km/h | 0.0 mm | Very high 46 |
| 31 Jan after | 35.8 °C | 7 % | 28 km/h | 0.0 mm | Extreme 50 |
| 1 Feb after | 35.3 °C | 10 % | 32 km/h | 0.0 mm | Extreme 51 |
| 2 Feb after | 34.8 °C | 13 % | 24 km/h | 0.0 mm | Extreme 51 |
| 3 Feb after | 34.9 °C | 9 % | 30 km/h | 0.0 mm | Extreme 53 |
| 4 Feb after | 35.4 °C | 17 % | 18 km/h | 0.0 mm | Very high 48 |
| 5 Feb after | 35.0 °C | 29 % | 23 km/h | 0.0 mm | Very high 40 |
Before and after, from space
Drag the line to compare the same ground before the fire and after it.
If the day is cloudy, change the date: each satellite passes once a day. In false colour the burnt ground looks brown or red.
Detections table · 141Every satellite heat detection, one by one, with time, satellite, power and coordinates.
| Date and time | Satellite | FRP (MW) | Lat | Lon |
|---|
Other fires nearby
Frequently asked questions
- How long did the Dabakala fire last?
- According to the heat detections seen by satellite inside the perimeter, it burned from 16 January 2022 to 26 January 2022 (11 days). The perimeter dates it from 19 January 2022 to 24 January 2022.
- How much area did it burn?
- The perimeter GWIS (Copernicus) rebuilt from heat detections is 3,359 hectares (33.6 km²). It is an estimate: official national figures may differ.
- Which municipalities burned?
- The fire entered 3 municipalities: Dabakala (2,802 ha, 1.4 %); Bouaké (529 ha, 0.3 %); Timbé (47 ha, 0.1 %).
- What was the weather like?
- During the fire the temperature reached 36.4 °C, humidity dropped to 11 % and gusts hit 35 km/h. The fire danger index (FWI) reached 48, class Very high.
- Where does this data come from?
- From the GWIS (Copernicus) burnt perimeter, NASA FIRMS VIIRS hotspots and the administrative boundaries of Côte d’Ivoire (geoBoundaries). It is not an official report.
Where to verify it
A satellite detection is not an official report. Final figures and the fire’s status are published by each country’s emergency service.
Emergency number: 180 · Emergency number and official warnings ›
Satellite cross-check
History of this page Changes in area, dates, name, official record or merged pages, compared every night since 24 October 2026.
No changes since 24 October 2026.
Does something look wrong on this page?
This page is built from satellite data and official records, and it sometimes gets things wrong: the wrong dates, the wrong town, two fires merged into one, or something that was not a wildfire at all. If you know this fire first-hand (you live nearby, saw it, fought it or reported on it), tell us what really happened and we will check it.
Report an error
How we know this
- Perimeter: GWIS (Copernicus), rebuilt from heat detections rather than mapped on imagery.
- Dates adjusted with the VIIRS detections inside the perimeter, which said 19 January 2022 to 24 January 2022. 141 Suomi-NPP VIIRS detections on those dates.
- We have not matched this page with any official record.
- Weather: Copernicus ERA5 reanalysis at the fire location, in cells of about 25 km.
- Built-up area and population come from the JRC Global Human Settlement Layer (epoch 2020, 100 m cells), summed inside the perimeter: an estimate of what was there, not a damage count.
Where this data comes from
The perimeter comes from the Copernicus Global Wildfire Information System (GWIS), which rebuilds it from MODIS and VIIRS heat detections and publishes it under CC BY 4.0. It is not measured on imagery as in Europe, so it is an estimate. Heat detections come from the VIIRS sensors aboard Suomi-NPP and NOAA-20, distributed by NASA FIRMS at 375 m resolution. Municipal boundaries come from geoBoundaries ADM3 (Creative Commons Attribution 3.0 Intergovernmental Organisations (CC BY 3.0 IGO)). The area per municipality is computed by WorldFires by crossing the perimeter with those boundaries, so it may differ from each country’s official figure.