VNP14A1 v002

VIIRS/NPP Thermal Anomalies and Fire Daily L3 Global 1 km SIN Grid

PI: Louis Giglio


The daily NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Thermal Anomalies and Fire (VNP14A1) Version 2 data product provides daily information about active fires and other thermal anomalies. The VNP14A1 data product is a global, 1 kilometer (km) gridded composite of fire pixels detected from VIIRS 750 meter (m) bands over a daily (24-hour) period. The VNP14 data products are designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies/Fire product suite.

The VNP14A1 product provides a total of four Science Dataset (SDS) layers for the confidence of fire, maximum fire radiative power (FRP), quality assessment (QA), and position of fire within scan. Each data product file is provided in HDF-EOS5 format. A low resolution browse is also provided showing the fire mask layer with a color map applied in JPEG format.

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Improvements/Changes from Previous Versions

  • Improved calibration algorithm and coefficients for entire Suomi NPP mission.
  • Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.
  • 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.
  • Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data.
  • Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.

More details can be found in this VIIRS Land V2 Changes document.

Product Maturity

Validation at stage 1 has been achieved for the VIIRS Thermal Anomalies & Fire product suite. Visit the VIIRS Land Product Quality Assessment website for additional information on validation and product maturity status.

Collection and Granule


Characteristic Description
CollectionSuomi NPP VIIRS
File Size~0.55 MB
Temporal ResolutionDaily
Temporal Extent2012-01-17 to Present
Spatial ExtentGlobal
Coordinate SystemSinusoidal
File FormatHDF-EOS5
Geographic Dimensions1200 km x 1200 km


Characteristic Description
Number of Science Dataset (SDS) Layers4
Columns/Rows1200 x 1200
Pixel Size1000 m

Layers / Variables

SDS Name Description Units Data Type Fill Value No Data Value Valid Range Scale Factor
FireMask Fire Mask Class 8-bit unsigned integer N/A N/A 0 to 9 N/A
MaxFRP Maximum Fire Radiative Power Megawatts 32-bit signed integer 0 N/A N/A 0.1
QA Pixel quality indicators Bit Field 8-bit unsigned integer N/A N/A 0 to 6 N/A
sample Sample number within a swath N/A 16-bit signed integer -1 N/A 0 to 3199 N/A

Fire Mask Data Set Classes

Value Label
0 not processed (missing input data)
1 not processed (trim)
2 not processed (obsolete)
3 non-fire water
4 cloud (land or water)
5 non-fire land
6 unknown
7 fire (low confidence)
8 fire (nominal confidence)
9 fire (high confidence)

Product Quality

The Quality Assurance (QA) bit flags for the quality layer are provided in Section 2.4.1 of the User Guide.

The quality layer is stored in an efficient bit-encoded manner. The unpack_sds_bits executable from the LDOPE Tools is available to the user community to help parse and interpret the quality layer.

Quality assurance information should be considered when determining the usability of data for a particular science application. The ArcGIS MODIS-VIIRS Python Toolbox contains tools capable of decoding quality data layers while producing thematic quality raster files for each quality attribute.

For complete information about product quality, refer to the VIIRS Land Product Quality Assessment website.

Known Issues

For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.

About the image

VNP14A1 thermal anomalies and fire product over the western United States on July 23, 2023.

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User Guide

Algorithm Theoretical Basis Document (ATBD)

File Specification

Using the Data

Access Data


DOI: 10.5067/VIIRS/VNP14A1.002