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| VIIRS 375m Active Fire Product | |
|---|---|
| Name | VIIRS 375m Active Fire Product |
| Manufacturer | National Oceanic and Atmospheric Administration / National Aeronautics and Space Administration |
| Type | Satellite remote sensing product |
VIIRS 375m Active Fire Product The VIIRS 375m Active Fire Product is a satellite-derived detection dataset for thermal anomalies and active fires produced from the Visible Infrared Imaging Radiometer Suite instrument. It provides near-real-time mapping of hotspots with 375-meter spatial sampling to support wildfire monitoring, emissions estimation, and disaster response across global and regional scales. The product serves operational users in civil protection, environmental science, and land management.
The product is derived from observations by the Suomi National Polar-orbiting Partnership mission and supports applications used by agencies such as the United States Geological Survey, European Space Agency, Brazilian National Institute for Space Research, and Geoscience Australia. It is integrated into decision workflows alongside datasets from the Moderate Resolution Imaging Spectroradiometer, Landsat 8, Sentinel-2, and historical archives like the AVHRR record. End-users include the Federal Emergency Management Agency, NASA Earth Science Division, World Meteorological Organization, and research programs focused on events such as the Amazon rainforest fires and the Australian bushfires.
The product originates from the Visible Infrared Imaging Radiometer Suite aboard the Suomi NPP and NOAA-20 platforms, instruments developed through collaboration between NASA Goddard Space Flight Center and NOAA National Environmental Satellite, Data, and Information Service. VIIRS carries a 22-band sensor including thermal infrared channels used for fire detection; these bands complement other payloads like the Advanced Very High Resolution Radiometer and the Operational Land Imager. Data acquisition leverages polar-orbiting revisit cycles, ground stations operated by entities including EUMETSAT partners and the NOAA Satellite Operations Facility, and processing chains run at centers such as the NASA Earth Observing System Data and Information System.
Active fire detection uses a contextual thresholding algorithm applied to the midwave and longwave infrared radiances, similar in concept to methods used for MODIS active fire products. The algorithm flags thermal anomalies by testing brightness temperature contrasts and spectral indices across VIIRS thermal bands, then filters detections by spatial coherence and cloud masks generated from ancillary products such as GOES cloud retrievals. Processing workflows employ radiometric calibration standards from Joint Polar Satellite System programs and quality screening comparable to algorithms used by the Global Fire Monitoring Center and academic groups at institutions like University of Maryland and University of California, Berkeley.
The 375-meter product provides gridded detections with per-pixel metadata including detection confidence, radiative power estimates, acquisition time, and geolocation. Outputs are commonly distributed in file formats and services maintained by NASA LP DAAC, NOAA CLASS, and regional portals: Hierarchical Data Format (HDF5), GeoTIFF proxies, and web services compatible with Open Geospatial Consortium standards. Attributes follow conventions adopted by programs such as Group on Earth Observations and are used in platforms like the Global Forest Watch and the Copernicus Emergency Management Service.
Validation activities compare VIIRS detections against higher-resolution references from Landsat 8 OLI/TIRS and airborne thermal sensors flown by agencies like the USFS and research campaigns coordinated by International Association for Fire Safety Science. Accuracy assessments examine detection probability, false alarm rate, geolocation error, and radiative power bias; these are often benchmarked against MODIS Active Fire datasets and field measurements compiled by networks including the Global Fire Emissions Database. Validation studies have been reported in journals associated with American Geophysical Union and European Geosciences Union conferences.
Operational uses include near-real-time situational awareness for wildfire suppression by organizations such as the California Department of Forestry and Fire Protection and landscape-scale emissions modeling for inventories developed by Intergovernmental Panel on Climate Change assessments. Researchers employ the product for phenology and disturbance mapping in boreal regions studied by teams at University of Alaska Fairbanks and for peatland fire monitoring in peat-rich basins like those examined by Indonesian Agency for Marine Affairs and Fisheries. The dataset feeds air quality forecasting systems maintained by metropolitan agencies and global assimilation systems run by centers such as the National Center for Atmospheric Research.
Limitations include detection sensitivity reduced by cloud cover analyzed by GOES-R products, mixed-pixel effects at 375 m relative to firefighters' situational needs, and saturation issues for very high-temperature sources noted in radiometry studies from NOAA and NASA teams. Uncertainties in radiative power translate to emissions estimation errors used in inventories like the Global Fire Emissions Database, and temporal sampling constraints inherent to polar orbits affect detection timeliness compared to geostationary sensors such as GOES-16 and Himawari. Users should combine VIIRS outputs with higher-resolution imagery and ground observations from agencies like National Weather Service and local land management authorities for critical operational decisions.
Category:Satellite remote sensing