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Dirba fire, 29 October 2016 Dirba, Sunam, Patran

Out · last detection 12 Nov 2016, 08:09 UTC

The fire started on 29 October 2016 in Dirba, India, and satellites saw it burning for 14 days. Copernicus’s global GWIS system rebuilt a burnt perimeter of 5,225 hectares from heat detections, spread across 3 municipalities.

It is the 31th largest in Punjab since 2016 (of 33 with a page). Number 42 in India in 2016, of 47.

Burnt area
5,225ha
GWIS perimeter (Copernicus)
Duration
14days
29 Oct 2016 – 11 Nov 2016
Municipalities hit
3
subdistricts
Started on
29 Oct
2016
Heat detections
461
in a single hotspot: 64 MW
Danger at start
38
Very high · FWI index
Energy released
3.0GW
sum of detected power

Where it burned

12 Nov 2016
HOTSPOTS BY DAY 29 Oct11 Nov

How it evolved, day by day

293031123456789101112

Fire radiative power detected each day, in megawatts, and number of hotspots. The magenta bar marks the peak day.

The weather it burned in

34°high
35km/h · peak gust
23%lowest humidity

It had gone 50 days without rain (1 mm or more) when it started.

This area had burned before

No earlier perimeters overlap this fire since 2016, when the satellite record begins.

What happened to each town

  1. Dirba where it started
    3,200 ha reached on 22 Oct
    13 %
  2. Sunam
    2,008 ha reached on 23 Oct
    3.9 %
  3. Patran
    33 ha reached on 7 Nov
    0.1 %

Burnt area inside each municipality, from crossing the GWIS perimeter with administrative boundaries. The distance is from the town centre to the nearest fire: staying a kilometre away does not mean it reached the houses.

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)
22 Oct 34.5 °C 29 % 27 km/h 0.0 mm Very high 38
23 Oct 33.9 °C 28 % 32 km/h 0.0 mm Very high 42
24 Oct 34.0 °C 24 % 31 km/h 0.0 mm Very high 40
25 Oct 33.6 °C 29 % 26 km/h 0.0 mm High 37
26 Oct 33.4 °C 27 % 27 km/h 0.0 mm High 37
27 Oct 33.1 °C 24 % 34 km/h 0.0 mm Very high 43
28 Oct 32.5 °C 25 % 29 km/h 0.0 mm Very high 39
29 Oct 32.5 °C 26 % 22 km/h 0.0 mm High 37
30 Oct 31.4 °C 32 % 17 km/h 0.0 mm High 33
31 Oct 31.1 °C 30 % 20 km/h 0.0 mm High 33
1 Nov 30.6 °C 35 % 24 km/h 0.0 mm High 31
2 Nov 30.7 °C 37 % 20 km/h 0.0 mm High 29
3 Nov 30.8 °C 35 % 19 km/h 0.0 mm High 29
4 Nov 30.6 °C 35 % 27 km/h 0.0 mm High 35
5 Nov 30.0 °C 35 % 26 km/h 0.0 mm High 34
6 Nov 30.0 °C 32 % 19 km/h 0.0 mm High 31
7 Nov 29.5 °C 32 % 33 km/h 0.0 mm High 37
8 Nov 30.4 °C 26 % 35 km/h 0.0 mm High 37
9 Nov 31.3 °C 23 % 29 km/h 0.0 mm High 37
10 Nov 30.7 °C 26 % 21 km/h 0.0 mm High 34
11 Nov 30.6 °C 27 % 25 km/h 0.0 mm High 35
12 Nov after 30.5 °C 27 % 28 km/h 0.0 mm High 37
13 Nov after 29.3 °C 32 % 18 km/h 0.0 mm High 34
14 Nov after 28.7 °C 30 % 22 km/h 0.0 mm High 32
15 Nov after 27.8 °C 33 % 25 km/h 0.0 mm High 33
16 Nov after 27.7 °C 29 % 30 km/h 0.0 mm High 35
17 Nov after 28.2 °C 27 % 35 km/h 0.0 mm Very high 38
18 Nov after 28.4 °C 29 % 31 km/h 0.0 mm High 36
19 Nov after 28.6 °C 28 % 24 km/h 0.0 mm High 32
20 Nov after 29.2 °C 29 % 20 km/h 0.0 mm High 32
21 Nov after 30.2 °C 26 % 17 km/h 0.0 mm High 32
22 Nov after 30.2 °C 27 % 24 km/h 0.0 mm High 34
23 Nov after 28.1 °C 34 % 27 km/h 0.0 mm High 33
24 Nov after 28.0 °C 26 % 31 km/h 0.0 mm High 36

Before and after, from space

Drag the line to compare the same ground before the fire and after it.

Before · 22 Oct 2016
After · 18 Nov 2016

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 · 461Every satellite heat detection, one by one, with time, satellite, power and coordinates.
⬇ Download CSV Times in UTC. Each detection is a 375 m pixel: a large fire yields hundreds per pass.
Date and timeSatelliteFRP (MW)LatLon

Other fires nearby

All fires in India ›

Frequently asked questions

How long did the Dirba fire last?
GWIS (Copernicus) dates it between 29 October 2016 and 11 November 2016: 14 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 5,225 hectares (52.2 km²). It is an estimate: official national figures may differ.
Which municipalities burned?
The fire entered 3 municipalities: Dirba (3,200 ha, 13 %); Sunam (2,008 ha, 3.9 %); Patran (33 ha, 0.1 %).
What was the weather like?
During the fire the temperature reached 34.5 °C, humidity dropped to 23 % and gusts hit 35 km/h. The fire danger index (FWI) reached 43, class Very high.
Where does this data come from?
From the GWIS (Copernicus) burnt perimeter, NASA FIRMS VIIRS hotspots and the administrative boundaries of India (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

Satellite cross-check

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
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We will only use your email to reply about this report. Privacy. This is not an emergency service: if there is a fire now, call 112.

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 (Open Data Commons Open Database License 1.0). 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.