VIIRS I-Band 375 m Active Fire Data

What is the VIIRS 375 m Active Fire Product?

The Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m thermal anomalies / active fire product provides data from the VIIRS sensor aboard the joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites. The 375 m data complements Moderate Resolution Imaging Spectroradiometer (MODIS) fire detection; they both show good agreement in hotspot detection but the improved spatial resolution of the 375 m data provides a greater response over fires of relatively small areas and provides improved mapping of large fire perimeters. The 375 m data also has improved nighttime performance. Consequently, these data are well suited for use in support of fire management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity.

Recommended reading: VIIRS 375 m Active Fire Algorithm User Guide (updated July 2018), VNP14IMGTDL_NRT (Suomi NPP), VJ114IMGTDL_NRT (NOAA-20) and VJ214IMGTDL_NRT (NOAA-21)

View the data in the FIRMS global fire map or FIRMS US/Canada

Download the data in GIS formats.

A comparison of daily fire spread mapped by 1km Aqua/MODIS (left), 750m VIIRS (center) and 375m VIIRS (right) data at the Taim Ecological Reserve in southern Brazil. The data cover the period March 26-31, 2013, which corresponds to Julian Days 85-90. The white outline represents the burned area mapped using 30m Landsat-7 on March 31. Note the more coherent fire spread and the excellent spatial agreement of the VIIRS 375m data (right image). This figure is reproduced courtesy of Wilfrid Schroeder, and appears in Schroeder, W., Oliva, P., Giglio, L. & Csiszar, I. 2014. “The New VIIRS 375 m active fire detection data product: Algorithm description and initial assessment.” Remote Sensing of the Environment, 143(2014). doi:10.1016/j.rse.2013.12.008

Fire products from VIIRS: A complementary VIIRS M-Band 750 m active fire data product is available in HDF format from NASA's Earthdata Search. FIRMS has opted to distribute the 375 m product rather than the 750 m product as the increased spatial resolution and increased number of fires detected is of interest to the to the broader fire management community.

Attribute fields for NRT VIIRS 375 m active fire data distributed by FIRMS

Attribute Short Description Long Description
Latitude Latitude Center of nominal 375 m fire pixel
Longitude Longitude Center of nominal 375 m fire pixel
Bright_ti4 Brightness temperature I-4 VIIRS I-4 channel brightness temperature of the fire pixel measured in Kelvin
Scan Along Scan pixel size The algorithm produces approximately 375 m pixels at nadir. Scan and track reflect actual pixel size
Track Along Track pixel size The algorithm produces approximately 375 m pixels at nadir. Scan and track reflect actual pixel size
Acq_Date Acquisition Date Date of VIIRS acquisition
Acq_Time Acquisition Time Time of acquisition/overpass of the satellite (in UTC)
Satellite Satellite N= 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)
Confidence Confidence

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. These have been removed from the NRT data distributed by FIRMS.

Version Version (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_ti5 Brightness temperature I-5 I-5 Channel brightness temperature of the fire pixel measured in Kelvin
FRP Fire Radiative Power

FRP 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.

DayNight Day or Night

D= Daytime fire, N= Nighttime fire

The VIIRS pixel footprint size projected onto Earth increases away from nadir.

The VIIRS I-Band 375 m Active Fire Product Algorithm

The VIIRS 375 m active fire product is described in Schroeder et al (2014). The product builds on the MODIS fire product heritage [Kaufman et al., 1998; Giglio et al., 2003 et al.], using a multi-spectral contextual algorithm to identify sub-pixel fire activity and other thermal anomalies in the Level 1 (swath) input data. The algorithm uses all five 375 m VIIRS channels to detect fires and separate land, water, and cloud pixels in the image. Additional 750 m channels complement the available VIIRS multispectral data. Those channels are used as input to the baseline active fire detection product, which provides continuity to the EOS/MODIS 1km Fire and Thermal Anomalies product.

Some Key information about VIIRS

  • The VIIRS sensor currently onboard Suomi NPP, NOAA-20 and NOAA-21 satellites. Launched in late 2011, Suomi NPP end-of-life is anticipated to occur on or before October 2026.

  • All three satellites capture daytime observations on the ascending node and nighttime observations on the descending node.

  • The VIIRS sensor aboard the Suomi NPP satellite, crosses the equator at approximately 13:30 p.m. (ascending node) and 1:30 a.m. (descending node).

  • The orbit of NOAA-21 is about 50 minutes ahead of NOAA-20 with Soumi NPP orbiting between them. Consequently, all three sensors conduct observations within approximately 1 hour of one another.

  • The timing of observation by the three VIIRS sensors for a given point on the Earth’s surface can vary day to day. This is due to geometry of the orbit paths of the respective satellites that change daily and repeat on a 16-day cycle which affects where that given point occurs on the swath of each of VIIRS sensor observation.

  • The 3,040 km VIIRS swath enables ~15% image overlap between consecutive orbits at the equator, thereby providing full global coverage every 12 hours and mid-latitudes will experience 3-4 looks a day.

  • VIIRS has 5 high resolution Imagery channels (I-bands), 16 moderate resolution channels (M-bands) and a Day/Night Band (DNB).

  • The VIIRS detectors have a constant angular resolution that results in an increasing pixel footprint size as the scan is further from nadir (see figure 1 below). This means the actual area of each scan has the shape of a bow-tie, as consecutive scans overlap away from nadir. The bow-tie effect is reduced during processing through a combination of aggregation and deletion of overlapping pixels.

For more information on VIIRS Active data: University of Maryland VIIRS Active Fire Web page.

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