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Description

The Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Anomalies (VNP14) Version 2 product is produced in 6-minute temporal satellite increments (swaths) at 750 meter resolution from the VIIRS sensor located on the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite. This product is designed after the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire data products to promote the continuity of the Earth Observation System (EOS) mission. This data product can enable users to understand the location and intensity of fire events as well as identifying thermal anomalies.

The VNP14 product includes 31 science dataset layers to analyze key factors in fire detection, including atmospheric conditions (e.g., atmospheric reflectance, solar zenith angle, brightness temperature) and fuel type for the event. The fire mask layer in the VNP14 product is the primary layer and can be used to identify fires and other thermal anomalies such as volcanoes. In addition to the fire mask, brightness temperature is provided for VIIRS channels M5, M7, M11, M13, M15, and M16.

Each swath of data is approximately 3,060 kilometers along track (long) and 3,060 kilometers across track (wide). The VNP14 product is also used to generate higher-level fire data products.

Use of the VNP03MODLL data product is required to apply accurate geolocation information to the VNP14 Science Datasets (SDS) / Variables.

Known Issues

Version Description

The following modifications and enhancements were implemented for Suomi NPP Version 2 thermal anomalies data products: (1) Improved calibration algorithm and coefficients for entire Suomi NPP mission, (2) Improved geolocation accuracy and applied updates to fix outliers around maneuver periods, (3) Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo, (4) Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data, and (5) Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS. Further details can be found in the VIIRS Land V2 Changes document (https://landweb.modaps.eosdis.nasa.gov/data/userguide/VIIRS_Land_C2_Cha…).

Product Summary

Platforms
Suomi-NPP
Instruments
VIIRS
Spatial Extent

N: 90 S: -90 E: 180 W: -180

Spatial Resolution
750 Meters x 750 Meters
Location
GLOBAL
Coordinate System
CARTESIAN
Granule Spatial Representation
GEODETIC
Temporal Extent
2012-01-17 to Present
Temporal Resolution
1 Day
Data Partner
Land Science Investigator-led Processing System, Terrestrial Information Systems Laboratory, Earth Sciences Division, Sciences and Exploration Directorate, Goddard Space Flight Center, NASA (NASA/GSFC/SED/ESD/TISL/LandSIPS) ,
Land Processes Distributed Active Archive Center (LP DAAC)
Concept ID
C2545314536-LPCLOUD
Data State
ACTIVE
Number of Files/Granules
1237899
Processing Level
2
Published
Updated
Science Keywords
Land Surface Temperature ,
Fire Occurrence ,
THERMAL ANOMALIES

Citation

Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.

Copy Citation

Giglio, L. (2023). VIIRS/NPP Thermal Anomalies/Fire 6-Min L2 Swath 750m V002 [Data set]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/VIIRS/VNP14.002 Date Accessed: 2026-04-30

File Naming Convention

VNP14.A2025227.0548.002.2025227231352.nc

The file name begins with the Product Short Name (VNP14) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2025227), the Hours and Minutes of Acquisition provided as HHMM (0548), the Version of the data collection (002), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2025227231352), and the Data Format (nc).

Documents

USER'S GUIDE

ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)

PRODUCT QUALITY ASSESSMENT

SCIENCE DATA PRODUCT VALIDATION

GENERAL DOCUMENTATION

Publications Citing This Dataset

Filters
Title Year Author Topic
Comparing Next-Day Wildfire Predictability of MODIS and VIIRS Satellite Data Karlsson, Justus, Xu, Yonghao, Berg, Amanda, Haglund, Leif Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Infrared Radiance, REFLECTED INFRARED, Visible Radiance, Attitude Characteristics, ORBITAL CHARACTERISTICS, Viewing Geometry
Comprehensive chemical profile and source apportionment of Lichtig, Pablo, Gelman Constantin, Julian, Diaz Resquin, Melisa, Baraldo Victorica, Facundo, Alessandrello, Diego, Gomez, Dario, Rossler, Cristina, de Oto, Marcelo, Espada Guerrero, Ramiro, Bajano, Hector, Bajano, Facundo, Herrera-Murillo, Jorge, Dawidowski, Laura Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Infrared Radiance, REFLECTED INFRARED, Visible Radiance
Simulating the air quality impact of prescribed fires using graph neural network-based PM2.5 forecasts Liao, Kyleen, Buch, Jatan, Lamb, Kara D., Gentine, Pierre Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES
Characterizing fire and fire atmospheric states from space using collocated hyperspectral infrared sounding and narrow-band imagery Zhou, Xuyang, Yue, Qing, Li, King-Fai, Fishbein, Evan, Chen, Xiuhong, Tan, Lin, Newman, Sally, Fetzer, Eric, Yung, Yuk L. Tropospheric Ozone, Tropopause, Atmospheric Chemistry, Carbon And Hydrocarbon Compounds, Methane, Outgoing Longwave Radiation, Atmospheric Temperature, Surface Temperature, Air Temperature, Skin Temperature, Upper Air Temperature, Vertical Profiles, Atmospheric Water Vapor, Layered Precipitable Water, Total Precipitable Water, Cloud Properties, Cloud Fraction, Cloud Top Temperature, Precipitation, Skin Temperature, Ocean Temperature, Sea Surface Skin Temperature, Clouds, Brightness Temperature, Infrared Radiance, Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES
ARGUS: Rapid Wildfire Tracking Using Satellite Data Collections Mitra, Saptashwa, Khandelwal, Paahuni, Pallickara, Shrideep, Pallickara, Sangmi Lee Land Surface Temperature, Emissivity, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES
Characterizing Aerosols during Forest Fires over Uttarakhand Region in India using Multi-Satellite Remote Sensing Data Verma, Sunita, Soni, Manish, Kumar, Harshbardhan, Payra, Swagata, Mishra, Manoj K, Bhawar, Rohini Aerosol Optical Depth/Thickness, Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES
Quantifying Carbon Monoxide Emissions on the Scale of Large Wildfires Bela, M. M., Kille, N., McKeen, S. A., RomeroAlvarez, J., Ahmadov, R., James, E., Pereira, G., Schmidt, C., Pierce, R. B., ONeill, S. M., Zhang, X., Kondragunta, S., Wiedinmyer, C., Volkamer, R. Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES
Satellite thermographies as an essential tool for the identification of cold air pools: an example from SE Spain Espin Sanchez, David, Olcina Cantos, Jorge, Conesa Garcia, Carmelo Land Surface Temperature, Emissivity, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES
Estimation of byrams fire intensity and rate of spread from spaceborne remote sensing data in a savanna landscape Ruecker, Gernot, Leimbach, David, Tiemann, Joachim Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES
Detection of fire smoke plumes based on aerosol scattering using viirs data over global fire-prone regions Lu, Xiaoman, Zhang, Xiaoyang, Li, Fangjun, Cochrane, Mark A., Ciren, Pubu Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES
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Variables

The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.

For questions on a specific variable, please use the Earthdata Forum.

Name Description Units Data Type Fill Value Valid Range Scale Factor Offset
CMG_day Day flag N/A uint16 N/A N/A N/A N/A
CMG_night Night flag N/A uint16 N/A N/A N/A N/A
fire mask Confidence of Fire Class Flag uint8 N/A 0 to 9 N/A N/A
fire_qa Pixel quality indicators Bit Field uint32 N/A 0 to 4294967295 N/A N/A
FP_AdjCloud Number of adjacent cloud pixels N/A uint8 N/A 0 to 8 N/A N/A
FP_AdjWater Number of adjacent water pixels N/A uint8 N/A 0 to 8 N/A N/A
FP_CMG_col Climate modeling grid column N/A int16 N/A N/A N/A N/A
FP_CMG_row Climate modeling grid row N/A int16 N/A N/A N/A N/A
FP_confidence Detection confidence Percent uint8 N/A 0 to 100 N/A N/A
FP_land Land pixel flag N/A uint8 N/A N/A N/A N/A
FP_latitude Latitude of fire pixel Degree float32 N/A -90 to 90 N/A N/A
FP_line Fire pixel line, valid range 0 to (16 x N)-1 Number int16 N/A 0 N/A N/A
FP_longitude Longitude of fire pixel Degree float32 N/A -180 to 180 N/A N/A
FP_MAD_DT Background M13-M15 brightness temperature difference mean absolute deviation ~ > 0 to 20 Kelvin float32 0 0 to 20 N/A N/A
FP_MAD_R7 Background M7 reflectance mean absolute deviation ~ > 0 to 0.2 N/A float32 -1 0 to 0.2 N/A N/A
FP_MAD_T13 Background M13 brightness temperature mean absolute deviation ~ > 0 to 20 Kelvin float32 0 0 to 20 N/A N/A
FP_MAD_T15 Background M15 brightness temperature mean absolute deviation ~ > 0 to 20 Kelvin float32 0 0 to 20 N/A N/A
FP_MeanDT Mean background brightness temperature difference ~ > -10 to 40 Kelvin float32 0 -10 to 40 N/A N/A
FP_MeanR7 Background M7 reflectance ~ > 0 to 0.6 N/A float32 -1 0 to 0.6 N/A N/A
FP_MeanT13 M13 brightness temperature of background Kelvin float32 0 260 to 340 N/A N/A
FP_MeanT15 M15  brightness temperature of background Kelvin float32 0 260 to 340 N/A N/A
FP_NumValid Number of valid background pixels Number int16 N/A N/A N/A N/A
FP_power Fire radiative power ~ > 0 to 5000 Megawatts float32 0 0 to 5000 N/A N/A
FP_R7 M7 fire reflectance pixels ~ > 0 to 0.35 N/A float32 -1 0 to 0.35 N/A N/A
FP_RelAzAng Relative Azimuth Angle Degree float32 N/A -180 to 180 N/A N/A
FP_sample Fire Pixel Sample N/A int16 N/A 0 to 3199 N/A N/A
FP_SolZenAng Solar Zenith Angle of fire pixel Degree float32 N/A 0 to 180 N/A N/A
FP_T13 M13 brightness temperature of fire pixel. ~ 300 to 634 Kelvin float32 N/A 300 to 634 N/A N/A
FP_T15 M15 brightness temperature of fire pixel ~ 265 to 330 Kelvin float32 N/A 265 to 330 N/A N/A
FP_ViewZenAng View Zenith Angle of fire pixel ~ 0 to 70 Degree float32 N/A 0 to 70 N/A N/A
FP_WinSize Background Window Size N/A uint8 N/A 5 to 21 N/A N/A
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