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Discover FIRMS

The Fire Information for Resource Management System (FIRMS) enables access to global near real-time satellite imagery, active fire/hotspots, and related products to identify the location, extent, and intensity of wildfire activity. FIRMS tools and applications provide geospatial data, products, and services to support the broader fire management community and to inform the general public. 

There are two platforms: FIRMS Global and FIRMS US/Canada.

Global data are available within 3 hours of satellite observation; some U.S. and Canada active fire detections are available in real-time.

The Fire Information for Resource Management System (FIRMS) was developed to provide near real-time active fire locations to natural resource managers that faced challenges obtaining timely satellite-derived fire information. In partnership with the U.S. Forest Service, a FIRMS US/Canada map service was launched in January 2021.

FIRMS was developed in 2007 by the University of Maryland, with funds from NASA’s Applied Sciences Program and the United Nations Food and Agriculture Organization (UN FAO), to provide near real-time active fire locations to natural resource managers that faced challenges obtaining timely satellite-derived fire information.

A version of FIRMS, known as the Global Fire Information Management System (GFIMS) ran at the UN FAO from 2010–2012, where it complemented the FAO’s existing suite of projects that deliver near real-time information to ongoing monitoring and emergency projects, to other UN organizations as well as providing information to the general public. GFIMS is no longer actively supported.

FIRMS US/Canada

FIRMS US/Canada provides the USDA Forest Service, partner agencies, and the general public access to tools and data to visualize and monitor the location, extent, intensity, and impacts of wildfire activity in the U.S. and Canada. The source of low latency satellite imagery, science data products, and enabling technologies to FIRMS US/Canada include: the NASA Land, Atmosphere Near real-time Capability for EO (LANCE) and other partners. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) are the foundational satellite data sources of the current FIRMS US/Canada application. Additional geospatial data and information from various agencies are also integrated to provide context for current/recent wildfire activity. Sources for these additional data include the National Interagency Fire Center, Department of the Interior Office of Wildland Fire, National Oceanic and Atmospheric Administration, National Weather Service, Canadian Interagency Fire Centre, and Natural Resources Canada

FIRMS US/Canada builds on a longstanding partnership between NASA and the Forest Service. In 2001, NASA's Goddard Space Flight Center in Greenbelt, Maryland, (GSFC) and the University of Maryland (UMD) developed the MODIS Land Rapid Response System to provide time-critical, science grade data products to the Forest Service and other users. That same year, the Forest Service implemented the Active Fire Mapping (AFM) Program to ingest near real-time data from the, now decommissioned, MODIS Land Rapid Response System to produce and disseminate value-added geospatial fire products. AFM since evolved to leverage and ingest MODIS and VIIRS satellite direct readout data and the NASA LANCE MODIS/VIIRS data stream.

FIRMS US/Canada is a joint NASA/Forest Service effort to modernize and optimize the legacy AFM Program data and product delivery capabilities that have provided imagery and geospatial fire products for the United States and Canada since 2001. The initial release of FIRMS US/Canada was launched in January 2021 and provides an updated platform for delivery of near real-time satellite data products as well as mapping and visualization capabilities. Data from additional near real-time satellite sources and other technical capabilities are also planned for the FIRMS US/Canada application after the initial early-2021 release.

MODIS Active Fire Products

Each MODIS active fire/thermal hotspot location represents the center of a 1km pixel that is flagged by the algorithm as containing one or more fires within the pixel. Combined (Terra and Aqua) MODIS NRT active fire products (MCD14DL) are processed using the standard MOD14/MYD14 Fire and Thermal Anomalies algorithm.

MODIS Collection 61 has been available since April 2021. C61 processing does not contain any change to the science algorithm; the update is from changes and enhancements to the calibration approach used in the generation of the Terra and Aqua MODIS Level 1B products. For further details on C61 calibration changes and other changes user is encouraged to refer to the PDF summarizing Collection 6.1 specific changes. For the most up to date information, please refer to the MODIS Collection 6 and 6.1 Version 1.0 Active Fire Product User's Guide (updated May 2021).

Attribute Fields for NRT MODIS Active Fire Data Distributed by FIRMS

AttributeShort DescriptionLong Description
LatitudeLatitudeCenter of 1 km fire pixel, but not necessarily the actual location of the fire as one or more fires can be detected within the 1 km pixel.
LongitudeLongitudeCenter of 1 km fire pixel, but not necessarily the actual location of the fire as one or more fires can be detected within the 1 km pixel.
BrightnessBrightness temperature 21 (Kelvin)Channel 21/22 brightness temperature of the fire pixel measured in Kelvin.
ScanAlong Scan pixel sizeThe algorithm produces 1 km fire pixels, but MODIS pixels get bigger toward the edge of scan. Scan and track reflect actual pixel size.
TrackAlong Track pixel sizeThe algorithm produces 1 km fire pixels, but MODIS pixels get bigger toward the edge of scan. Scan and track reflect actual pixel size.
Acq_DateAcquisition DateData of MODIS acquisition.
Acq_TimeAcquisition TimeTime of acquisition/overpass of the satellite (in UTC).
SatelliteSatelliteA = Aqua and T = Terra.
ConfidenceConfidence (0-100%)This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence estimates range between 0 and 100% and are assigned one of the three fire classes (low-confidence fire, nominal-confidence fire, or high-confidence fire).
VersionVersion (Collection and source)

Version identifies the collection (e.g., MODIS Collection 6.1) and source of data processing (Ultra Real-Time (URT suffix added to collection), Real-Time (RT suffix), Near Real-Time (NRT suffix) or Standard Processing (collection only). For example:

"6.1URT" - Collection 6.1 Ultra Real-Time processing.
"6.1RT" -  Collection 6.1 Real-Time processing.
"6.1NRT" - Collection 61 Near Real-Time processing.
"6.1" - Collection 61 Standard processing.
Find out more on collections and on the differences between FIRMS data sourced from LANCE FIRMS and the University of Maryland in the FIRMS FAQ.

Bright_T31Brightness temperature 31 (Kelvin)Channel 31 brightness temperature of the fire pixel measured in Kelvin.
FRPFire Radiative Power (MW - megawatts)Depicts the pixel-integrated fire radiative power in MW (megawatts).
Type*Inferred hot spot type0 = presumed vegetation fire
1 = active volcano
2 = other static land source
3 = offshore
DayNightDay or NightD= Daytime fire, N= Nighttime fire

*This attribute is only available for MCD14ML (standard quality) data

VIIRS (375m) Active Fire Products

Each VIIRS active fire/thermal hotspot location represents the center of a 375m pixel. The VIIRS data complement the MODIS fire detections but the improved spatial resolution of the 375 m data provides a greater response of fires over relatively small areas and has improved nighttime performance. Read more on VIIRS active fire products.

VIIRS NRT 375 m active fire products are from: Suomi NPP (VNP14IMGTDL_NRT); NOAA-20, formally known as JPSS-1 (VJ114IMGTDL_NRT); and NOAA-21, formally known as JPSS-2 (VJ214IMGTDL_NRT).

Attribute Fields for NRT VIIRS 375m Active Fire Data Distributed by FIRMS

AttributeShort DescriptionLong Description
LatitudeLatitudeCenter of nominal 375 m fire pixel
LongitudeLongitudeCenter of nominal 375 m fire pixel
Bright_ti4Brightness temperature I-4VIIRS I-4 channel brightness temperature of the fire pixel measured in Kelvin
ScanAlong Scan pixel sizeThe algorithm produces approximately 375 m pixels at nadir. Scan and track reflect actual pixel size
TrackAlong Track pixel sizeThe algorithm produces approximately 375 m pixels at nadir. Scan and track reflect actual pixel size
Acq_DateAcquisition DateDate of VIIRS acquisition
Acq_TimeAcquisition TimeTime of acquisition/overpass of the satellite (in UTC)
SatelliteSatelliteN= Suomi National Polar-orbiting Partnership (Suomi NPP), N20=NOAA-20 (designated JPSS-1 prior to launch), N21=NOAA-21 (designated JPSS-2 prior to launch)
ConfidenceConfidence

This value is based on a collection of intermediate algorithm quantities used in the detection process. It is intended to help users gauge the quality of individual hotspot/fire pixels. Confidence values are set to low, nominal and high. Low confidence daytime fire pixels are typically associated with areas of sun glint and lower relative temperature anomaly (<15K) in the mid-infrared channel I4. Nominal confidence pixels are those free of potential sun glint contamination during the day and marked by strong (>15K) temperature anomaly in either day or nighttime data. High confidence fire pixels are associated with day or nighttime saturated pixels.

Please note: Low confidence nighttime pixels occur only over the geographic area extending from 11deg E to 110 deg W and 7 deg N to 55 deg S. This area describes the region of influence of the South Atlantic Magnetic Anomaly which can cause spurious brightness temperatures in the mid-infrared channel I4 leading to potential false positive alarms. Note: These have been removed from the NRT data distributed by FIRMS.

VersionVersion (Collection and source)Version identifies the collection (e.g. VIIRS Collection 1) and source of data processing: Near Real-Time (NRT suffix added to collection) or Standard Processing (collection only)
"1.0NRT" - Collection 1 NRT processing
"1.0" - Collection 1 Standard processing
Bright_ti5Brightness temperature I-5I-5 Channel brightness temperature of the fire pixel measured in Kelvin
FRPFire Radiative PowerFRP depicts the pixel-integrated fire radiative power in MW (megawatts). FRP depicts the pixel-integrated fire radiative power in MW (megawatts). Given the unique spatial and spectral resolution of the data, the VIIRS 375 m fire detection algorithm was customized and tuned in order to optimize its response over small fires while balancing the occurrence of false alarms. Frequent saturation of the mid-infrared I4 channel (3.55-3.93 µm) driving the detection of active fires requires additional tests and procedures to avoid pixel classification errors. As a result, sub-pixel fire characterization (e.g., fire radiative power [FRP] retrieval) is only viable across small and/or low-intensity fires. Systematic FRP retrievals are based on a hybrid approach combining 375 and 750 m data. In fact, starting in 2015 the algorithm incorporated additional VIIRS channel M13 (3.973-4.128 µm) 750 m data in both aggregated and unaggregated format.
DayNightDay or NightD= Daytime fire, N= Nighttime fire

User Guides

Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m Active Fire Algorithm User Guide (Updated July 2018)

MODIS Collection 6 Active Fire Product User's Guide, Revision B (Updated December 2018)

MODIS Collection 5 Active Fire Product User’s Guide, v2.5 (Updated 31 March 2013)

FIRMS, Active Fire, and Burned Area Publications

The publications listed below describe FIRMS, the MODIS Active Fire and Burned Area Products, and explore the level of accuracy of the products.

Read about FIRMS in the Earthdata article Fires from Space, and how near real-time MODIS fire detections are used in NASA's Sensing Our Planet publication Orbiting Watchtowers.

Giglio L., Schroeder, W., & Justice, C.O. (2016). The collection 6 MODIS active fire detection algorithm and fire products. Remote Sensing of Environment, 178: 31-41. doi:10.1016/j.rse.2016.02.054 PDF

Schroeder, W., Oliva, P., Giglio, L., & Csiszar, I. A. (2014). The New VIIRS 375m active fire detection data product: algorithm description and initial assessment. Remote Sensing of Environment, 143: 85-96. doi:10.1016/j.rse.2013.12.008 PDF

Justice, C.O., Giglio, L., et al. (2011). MODIS-Derived Global Fire Products. Land Remote Sensing and Global Environmental Change. B. Ramachandran, C.O. Justice, and M.J. Abrams, Springer New York. 11: 661-679. doi:10.1007/978-1-4419-6749-7_29

Davies, D.K., Ilavajhala, S., Wong, M.M., & Justice, C.O. (2009). Fire Information for Resource Management System: Archiving and Distributing MODIS Active Fire Data. IEEE Transactions on Geoscience and Remote Sensing, 47(1): 72-79. doi:10.1109/TGRS.2008.2002076

Schroeder, W., Prins, E., Giglio, L., Csiszar, I., Schimdt, C., Morisette, J., & Morton, D. (2008). Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data. Remote Sensing of Environment, 112 (2008): 2711-2726. doi:10.1016/j.rse.2008.01.005

Csiszar, I., Morisette, J., & Giglio, L. (2006). Validation of active fire detection from moderate resolution satellite sensors: the MODIS example in Northern Eurasia. IEEE Transactions on Geoscience and Remote Sensing, 44(7): 1757-1764. doi:10.1109/TGRS.2006.875941

Giglio, L., van derWerf, G.R., Randerson, J.T., Collatz, G.J., & Kasibhatla, P. (2006). Global estimation of burned area using MODIS active fire observations. Atmospheric Chemistry and Physics, 6: 957-974. doi:10.5194/acp-6-957-2006

Wooster, M.J., Roberts, G., Perry, G.L.W., & Kaufman, Y.J. (2005). Retrieval of biomass combustion rates and totals from fire radiative power observations: FRP derivation and calibration relationships between biomass consumption and fire radiative energy release. Journal of Geophysical Research, 110, D24311. doi:10.1029/2005JD006318

Morisette, J.T., Giglio, L., Csiszar, I., Setzer, A., Schroeder, W., Morton, D., & Justice, C.O. (2005). Validation of MODIS active fire detection products derived from two algorithms. Earth Interactions, 9(9): 1-25. doi: 10.1175/EI141.1

Morisette, J.T., Giglio, L., Csiszar, I., & Justice, C.O. (2005). Validation of the MODIS Active fire product over Southern Africa with ASTER data. International Journal of Remote Sensing, 26: 4239-4264. doi:10.1080/01431160500113526

Wooster, M.J., Zhukov, B., & Oertel, D. (2003). Fire radiative energy for quantitative study of biomass burning: Derivation from the BIRD experimental satellite and comparison to MODIS fire products. Remote Sensing of Environment, 86(1): 83-107. doi:10.1016/S0034-4257(03)00070-1 PDF

Giglio, L., Descloitres, J., Justice, C.O., & Kaufman, Y. (2003). An enhanced contextual fire detection algorithm for MODIS. Remote Sensing of Environment, 87: 273-282. doi: 10.1016/S0034-4257(03)00184-6

Justice, C.O., Giglio, L., Korontzi, S., Owens, J., Morisette, J., Roy, D., Descloitres, J., Alleaume, S., Petitcolin, F., & Kaufman, Y.J. (2002). The MODIS fire products. Remote Sensing of Environment, 83: 244-262. doi:10.1016/S0034-4257(02)00076-7

Kaufman, Y.J., Justice, C.O., Flynn, L.P., Kendall, J.D., Prins, E.M., Giglio, L., Ward, D.E., Menzel, W.P., & Setzer, A.W. (1998). Potential global fire monitoring from EOS‐MODIS.Journal of Geophysical Research: Atmospheres (1984–2012), 103(D24): 32215-32238. doi:10.1029/98jd01644

The following links maybe useful for users wanting to learn more or connect with other fire networks/see other fire applications.

Background/Framework

Global Observations of Forest and Land Cover Dynamics (GOFC-GOLD) Fire Monitoring and Mapping Implementation (GOFC-Fire)

Science

Other regional fire applications may provide users with additional value-added products.  These include:

Tool at a Glance

Related Service

Near real-time data (NRT)

Related Topic

Fire Management
Wildfires

FIRMS News

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False-color corrected reflectance image of the Elk Fire in Wyoming on 16 October 2024 from the VIIRS instrument aboard the NOAA-20 satellite

Elk Fire, Wyoming

This image of the Elk Fire in Wyoming was captured on Oct 16, 2024, by the VIIRS instrument aboard the joint NASA/NOAA NOAA-21 platform.
Worldview Image of the Week
A global map is divided into sections by colorful dotted lines; each section represents the spatial coverage of a geostationary satellite used in FIRMS.

Geostationary Active Fire Detection Data in FIRMS

Active fire detection data from five geostationary sensors are available in NASA's Fire Information for Resource Management System (FIRMS) and collectively provide global coverage.
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FIRMS global fire location map

Introduction to FIRMS

In this video tutorial, learn the basic and advanced features of NASA’s Fire Information for Resource Management System (FIRMS).
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