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Data

Annual area burnt by wildfires by region

GWIS (MODIS)
See all data and research on:
Climate ChangeWildfires

What you should know about this indicator

  • Burned areas are detected from satellite imagery. NASA's MODIS satellite sensors scan the entire Earth's surface every one to two days, and the burned area product identifies land that shows the characteristic spectral signature of recent fire.
  • Each area of land is assigned to a land cover type — such as forest, savanna, or cropland — based on annual satellite-derived land cover maps.
  • Satellite detection of burned areas is known to underestimate the true extent of fire. Small fires and fires obscured by cloud cover or tree canopy are often missed. Despite this, the dataset provides the longest consistent global record available, making it well suited for tracking long-term trends.
Annual area burnt by wildfires by region
GWIS (MODIS)
Total land area burnt by each year, in hectares, across all land cover types.
Source
Global Wildfire Information System (2026) – with minor processing by Our World in Data
Last updated
April 20, 2026
Next expected update
April 2027
Date range
2002–2024
Unit
hectares

Sources and processing

This data is based on the following sources

Global Wildfire Information System – Global Yearly Burned Area by Land Cover Type

Yearly burned area in hectares by land cover class (2002–2024) for all countries. Data comes from the MODIS satellite sensor (1km resolution), which has been collecting data since the early 2000s. This makes it well-suited for analyzing long-run trends in burned area by land cover type. Because of MODIS's coarser resolution, smaller fires may not be detected.

Data is fetched via the GWIS country profile API (cprof.effis.emergency.copernicus.eu). Note: the API contains more recent data than the bulk download ZIP on the downloads page, which currently has all-zero values for 2024.

Retrieved on
April 20, 2026
Retrieved from
https://gwis.jrc.ec.europa.eu/apps/country.profile/downloads
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

Yearly burned area in hectares by land cover class (2002–2024) for all countries. Data comes from the MODIS satellite sensor (1km resolution), which has been collecting data since the early 2000s. This makes it well-suited for analyzing long-run trends in burned area by land cover type. Because of MODIS's coarser resolution, smaller fires may not be detected.

Data is fetched via the GWIS country profile API (cprof.effis.emergency.copernicus.eu). Note: the API contains more recent data than the bulk download ZIP on the downloads page, which currently has all-zero values for 2024.

Retrieved on
April 20, 2026
Retrieved from
https://gwis.jrc.ec.europa.eu/apps/country.profile/downloads
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

How we process data at Our World in Data

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

Reuse this work

  • All data produced by third-party providers and made available by Our World in Data are subject to the license terms from the original providers. Our work would not be possible without the data providers we rely on, so we ask you to always cite them appropriately (see below). This is crucial to allow data providers to continue doing their work, enhancing, maintaining and updating valuable data.
  • All data, visualizations, and code produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited.

Citations

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/20260429-133538/grapher/annual-area-burnt-by-wildfires-gwis.html [online resource] (archived on April 29, 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 (2026) – with minor processing by Our World in Data

Full citation

Global Wildfire Information System (2026) – with minor processing by Our World in Data. “Annual area burnt by wildfires by region – GWIS (MODIS)” [dataset]. Global Wildfire Information System, “Global Yearly Burned Area by Land Cover Type” [original data]. Retrieved April 30, 2026 from https://archive.ourworldindata.org/20260429-133538/grapher/annual-area-burnt-by-wildfires-gwis.html (archived on April 29, 2026).

Download

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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.

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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