Mlele fire, 28 August 2019 Mlele
The fire started on 28 August 2019 in Mlele, Tanzania, and satellites saw it burning for 11 days. Copernicus’s global GWIS system rebuilt a burnt perimeter of 11,555 hectares from heat detections, spread across a single municipality.
It is the 21th largest in Katavi since 2016 (of 271 with a page). Number 15 in Tanzania in 2019, of 123.
Compare with…
Suggestions: Mlele · 2016Mlele · 2017Mlele · 2018Mlele · 2016
- Burnt area
- 11,555ha
- GWIS perimeter (Copernicus)
- Duration
- 11days
- 28 Aug 2019 – 7 Sept 2019
- Municipalities hit
- 1
- districts
- Started on
- 28 Aug
- 2019
- Heat detections
- 384
- in a single hotspot: 36 MW
- Danger at start
- 28
- High · FWI index
- Average daily power
- 159MW
- 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. Rain came after the fire: 1.8 mm on 12 Sept.
This area had burned before
88% of the perimeter overlaps earlier fires recorded since 2016: 8,120 ha in 2016, 3,976 ha in 2017, 5,577 ha in 2018. Part of it burned more than once, so the yearly figures add up to more than the 10,197 ha that had burned before.
- 7,217 ha Mlele fire, August 2016 8,486 ha in total; the hectares shown are those it shares with this fire
- 3,637 ha Mlele fire, August 2017 10,537 ha in total; the hectares shown are those it shares with this fire
- 2,946 ha Mlele fire, August 2018 3,497 ha in total; the hectares shown are those it shares with this fire
- 289 ha Mlele fire, July 2016 10,472 ha in total; the hectares shown are those it shares with this fire
- 146 ha Mlele fire, July 2016 3,041 ha in total; the hectares shown are those it shares with this fire
- 2 ha Mlele fire, August 2016 3,608 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
-
Mlele where it started11,645 ha reached on 23 Aug0.4 %
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 was no noticeable built-up land and almost nobody lived there (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) |
|---|---|---|---|---|---|
| 28 Aug | 29.0 °C | 35 % | 30 km/h | 0.0 mm | High 28 |
| 29 Aug | 28.4 °C | 36 % | 30 km/h | 0.0 mm | High 27 |
| 30 Aug | 29.2 °C | 33 % | 31 km/h | 0.0 mm | High 30 |
| 31 Aug | 29.9 °C | 31 % | 25 km/h | 0.0 mm | High 28 |
| 1 Sept | 30.2 °C | 30 % | 24 km/h | 0.0 mm | High 30 |
| 2 Sept | 28.3 °C | 44 % | 29 km/h | 0.0 mm | High 28 |
| 3 Sept | 28.4 °C | 33 % | 36 km/h | 0.0 mm | High 31 |
| 4 Sept | 27.8 °C | 34 % | 34 km/h | 0.0 mm | High 30 |
| 5 Sept | 29.0 °C | 36 % | 34 km/h | 0.0 mm | High 31 |
| 6 Sept | 29.3 °C | 35 % | 37 km/h | 0.0 mm | High 32 |
| 7 Sept | 27.6 °C | 36 % | 49 km/h | 0.0 mm | High 38 |
| 8 Sept after | 25.6 °C | 41 % | 51 km/h | 0.0 mm | Very high 39 |
| 9 Sept after | 26.1 °C | 36 % | 40 km/h | 0.0 mm | High 33 |
| 10 Sept after | 29.2 °C | 38 % | 30 km/h | 0.1 mm | High 29 |
| 11 Sept after | 28.9 °C | 39 % | 32 km/h | 0.0 mm | High 28 |
| 12 Sept after | 30.1 °C | 38 % | 30 km/h | 1.8 mm | Moderate 16 |
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 · 384Every satellite heat detection, one by one, with time, satellite, power and coordinates.
| Date and time | Satellite | FRP (MW) | Lat | Lon |
|---|
Other fires nearby
- 21,840 haMlele12 September 2025 · 26 days · 25 km away
- 14,689 haMlele9 September 2022 · 19 days · 27 km away
- 34,561 haMlele28 June 2016 · 25 days · 30 km away
- 20,520 haMlele17 June 2017 · 13 days · 33 km away
- 12,919 haMlele10 July 2017 · 15 days · 34 km away
- 28,157 haMlele28 August 2017 · 19 days · 38 km away
Frequently asked questions
- How long did the Mlele fire last?
- GWIS (Copernicus) dates it between 28 August 2019 and 7 September 2019: 11 days between the first and last heat detection of the perimeter.
- How much area did it burn?
- The perimeter GWIS (Copernicus) rebuilt from heat detections is 11,555 hectares (115.6 km²). It is an estimate: official national figures may differ.
- Which municipalities burned?
- The fire only entered Mlele (11,645 ha, 0.4 %).
- What was the weather like?
- During the fire the temperature reached 30.2 °C, humidity dropped to 30 % and gusts hit 49 km/h. The fire danger index (FWI) reached 38, class High.
- Where does this data come from?
- From the GWIS (Copernicus) burnt perimeter, NASA FIRMS VIIRS hotspots and the administrative boundaries of Tanzania (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: 112 · 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 from the perimeter: the VIIRS detections inside it did not change them. 384 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 ADM2 (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.