Data

Annual area burnt by wildfires by region

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What you should know about this indicator

Wildfires are detected through the use of satellite imagery based on the NASA MCD64 MODIS product which offers global assessments of burned areas and fire occurrences. Although widely used, this product is known to consistently underestimate both the extent of burned areas and the frequency of fires. However, in terms of historical trends, it stands out as the most comprehensive dataset, offering the longest time series compared to other available options.

Annual area burnt by wildfires by region
Total area of forests, savannas, shrublands/grasslands, croplands, and other land that have been burned as a result of .
Source
Global Wildfire Information System (2022)with minor processing by Our World in Data
Last updated
February 19, 2024
Next expected update
May 2026
Date range
2002–2022
Unit
hectares

Sources and processing

Global Wildfire Information System – Global Monthly Burned Area

Monthly burned area in hectares by landcover class for years 2002-2022 for all countries and sub-country administrative units (GADM level 0 and level 1 administrative units).

Retrieved on
February 19, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Global Wildfire Information System

Monthly burned area in hectares by landcover class for years 2002-2022 for all countries and sub-country administrative units (GADM level 0 and level 1 administrative units).

Retrieved on
February 19, 2024
Citation
This is the citation of the original data obtained from the source, prior to any processing or adaptation by Our World in Data. To cite data downloaded from this page, please use the suggested citation given in Reuse This Work below.
Global Wildfire Information System

All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline

How to cite this page

To cite this page overall, including any descriptions, FAQs or explanations of the data authored by Our World in Data, please use the following citation:

“Data Page: Annual area burnt by wildfires by region”, part of the following publication: Hannah Ritchie, Pablo Rosado, and Veronika Samborska (2024) - “Climate Change”. Data adapted from Global Wildfire Information System. Retrieved from https://archive.ourworldindata.org/20260325-171315/grapher/annual-area-burnt-by-wildfires-gwis.html [online resource] (archived on March 25, 2026).

How to cite this data

In-line citationIf you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Global Wildfire Information System (2022) – with minor processing by Our World in Data

Full citation

Global Wildfire Information System (2022) – with minor processing by Our World in Data. “Annual area burnt by wildfires by region” [dataset]. Global Wildfire Information System, “Global Monthly Burned Area” [original data]. Retrieved April 1, 2026 from https://archive.ourworldindata.org/20260325-171315/grapher/annual-area-burnt-by-wildfires-gwis.html (archived on March 25, 2026).

Quick download

Download the data shown in this chart as a ZIP file containing a CSV file, metadata in JSON format, and a README. The CSV file can be opened in Excel, Google Sheets, and other data analysis tools.

Data API

Use these URLs to programmatically access this chart's data and configure your requests with the options below. Our documentation provides more information on how to use the API, and you can find a few code examples below.

Data URL (CSV format)
https://ourworldindata.org/grapher/annual-area-burnt-by-wildfires-gwis.csv?v=1&csvType=full&useColumnShortNames=false
Metadata URL (JSON format)
https://ourworldindata.org/grapher/annual-area-burnt-by-wildfires-gwis.metadata.json?v=1&csvType=full&useColumnShortNames=false

Code examples

Examples of how to load this data into different data analysis tools.

Excel / Google Sheets
=IMPORTDATA("https://ourworldindata.org/grapher/annual-area-burnt-by-wildfires-gwis.csv?v=1&csvType=full&useColumnShortNames=false")
Python with Pandas
import pandas as pd
import requests

# Fetch the data.
df = pd.read_csv("https://ourworldindata.org/grapher/annual-area-burnt-by-wildfires-gwis.csv?v=1&csvType=full&useColumnShortNames=false", storage_options = {'User-Agent': 'Our World In Data data fetch/1.0'})

# Fetch the metadata
metadata = requests.get("https://ourworldindata.org/grapher/annual-area-burnt-by-wildfires-gwis.metadata.json?v=1&csvType=full&useColumnShortNames=false").json()
R
library(jsonlite)

# Fetch the data
df <- read.csv("https://ourworldindata.org/grapher/annual-area-burnt-by-wildfires-gwis.csv?v=1&csvType=full&useColumnShortNames=false")

# Fetch the metadata
metadata <- fromJSON("https://ourworldindata.org/grapher/annual-area-burnt-by-wildfires-gwis.metadata.json?v=1&csvType=full&useColumnShortNames=false")
Stata
import delimited "https://ourworldindata.org/grapher/annual-area-burnt-by-wildfires-gwis.csv?v=1&csvType=full&useColumnShortNames=false", encoding("utf-8") clear