Global characterization of fire activity: toward defining fire regimes from Earth observation data
Abstract
There is interest in the global community on how fire regimes are changing as a function of changing demographics and climate. The ground‐based data to monitor such trends in fire activity are inadequate at the global scale. Satellite observations provide a basis for such a monitoring system. In this study, a set of metrics were developed from 6 years of MODIS active fire data. The metrics were grouped into eight classes representing three axes of fire activity: density, season duration and interannual variability. These groups were compared with biophysical and human explanatory variables on a global scale. We found that more than 30% of the land surface has a significant fire frequency. The most extensive fire class exhibited high fire density, low duration and high variability and was found in boreal and tropical wet and dry environments. A high association was found between population distribution and fire persistence. Low GDP km −2 was associated with fire classes with high interannual variability and low seasonal duration. In areas with more economic resources, fires tend to be more regular and last longer. High fire duration and low interannual variability were associated with croplands, but often with low fire density. The study was constrained by the limited length of satellite data record but is a first step toward developing a comprehensive global assessment of fire regimes. However, more attention is needed by the global observing systems to provide the underpinning socio‐economic observations to better quantify and analyze the human characteristics of fire regimes.
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To date, global-scale understanding of fire is largely limited to the annual extent of burning as detected by satellites.
“To date, global analyses have used satellite-derived active fire and burned area data to describe the extent, interannual variability, and seasonality of burning (3, 7–9).”
From Defining pyromes and global syndromes of fire regimes (2013) · cites this paper as [9]
Chuvieco et al., using three active fire data metrics, successfully distinguished boreal forest but found no clear patterns with other vegetation classes.
“Chuvieco et al. (9), by using three active fire data metrics, successfully distinguished boreal forest but found no clear patterns with other vegetation classes.”
From Defining pyromes and global syndromes of fire regimes (2013) · cites this paper as [9]
Cites
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“Several major causes are responsible for changing fire regimes in the last decades, including global warming (Running, 2006; Westerling et al., 2006), which has global implications, but appears to be mostly affecting boreal regions (Stocks et al.”
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The human dimension of fire regimes on Earth
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“Such comparative studies require the development of a lexicon and methodology to describe fire regimes, their biophysical consequences, their political and cultural contexts, and economic costs and benefits (Chuvieco et al., 2008).”
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Driving factors of fire density can spatially vary at the local scale in south-eastern France
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- Authors
- CHUVIECO, E., GIGLIO, L., & JUSTICE, C.
- Affiliations
- Universidad de Alcalá (ES)
- Science Systems and Applications (United States) (US)
- University of Maryland, College Park (US)
- Corresponding author
- CHUVIECO, EMILIO
- Venue
- Global Change Biology
- Publisher
- Wiley
- Published
- 2008-02-27
- Volume
- 14
- Issue
- 7
- Pages
- 1488-1502
- ISSN
- 1354-1013 (ISSN-L)
- 1365-2486
- OpenAlex
- W1979313917
- Cited by
- 371
- References
- 1
- Citations by year
- 2026: 16 · 2025: 21 · 2024: 21 · 2023: 15 · 2022: 28 · 2021: 22 · 2020: 19 · 2019: 37 · 2018: 17 · 2017: 25 · 2016: 20 · 2015: 26 · 2014: 16 · 2013: 25 · 2012: 24
- FWCI
- 11.70
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Global Change Biology (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Fire Detection and Safety Systems
- Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
- Keywords
- fire regimes, fire frequency, fire density, cropland, satellite fire monitoring
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