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Description

The MYD14 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MYD14 Version 6.1 data product.

The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire MYD14 Version 6 product is produced daily in 5-minute temporal satellite increments (swaths). The MYD14 product is used to generate all of the higher level fire products, but can also be used to identify fires and other thermal anomalies, such as volcanoes. Each swath of data is approximately 2,030 kilometers along track (long), and 2,300 kilometers across track (wide).

Known Issues

  • Known issues are described on the MODIS/VIIRS Land Quality Assessment website and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua Outage.

Improvements/Changes from Previous Versions

  • Refinements to internal cloud mask, which sometimes flags heavy smoke as clouds.
  • Fix for frequent false alarms occurring in the Amazon that are caused by small (~1 km²) clearings within forests.
  • Fix to correct a bug that causes incorrect assessment of cloud and water pixels adjacent to fire pixels near the scan edge.
  • Detects small fires using dynamic thresholding.
  • Processes ocean and coastline pixels to detect fire from oil rigs.
  • The Version 6 fire mask has the potential to detect fire over water pixels. Therefore, class 3 pixel values have been changed to be classified as “non-fire water pixels.”

Version Description

The MYD14 Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MYD14 Version 6.1 data product (https://doi.org/10.5067/MODIS/MYD14.061).

Product Summary

Platforms
Aqua
Instruments
MODIS
Spatial Extent
N: 90 S: -90 E: 180 W: -180
Spatial Resolution
1000 Meters x 1000 Meters
Geographic Region
GLOBAL
Coordinate System
CARTESIAN
Granule Spatial Representation
GEODETIC
Temporal Extent
2002-07-04 to 2023-02-26
Temporal Resolution
1 Day
Data Partner
Land Processes Distributed Active Archive Center (LP DAAC)
MODIS Adaptive Processing System, Terrestrial Information Systems Laboratory, Earth Sciences Division, Science and Exploration Directorate, Goddard Space Flight Center, NASA (NASA/GSFC/SED/ESD/TISL/MODAPS)
Concept ID
C2763370241-LPCLOUD
Data State
DEPRECATED
Processing Level
2
Published
Updated
Science Keywords
Land Surface Temperature,
Fire Occurrence,
Surface Thermal Properties

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., & Justice, C. (2015). MYD14 MODIS/Aqua Thermal Anomalies/Fire 5-Min L2 Swath 1km V006 [Data set]. NASA Land Processes Distributed Active Archive Center. https://doi.org/10.5067/MODIS/MYD14.006 Date Accessed: 2025-10-29

File Naming Convention

MYD14.A2002281.2350.006.2015056111150.hdf

The file name begins with the Product Short Name (MYD14) followed by the Julian Date of Acquisition formatted as AYYYYDDD (A2002281), the Hours and Minutes of Acquisition provided as HHMM (2350), the Version of the data collection (006), the Julian Date and Time of Production designated as YYYYDDDHHMMSS (2015056111150), and the Data Format (hdf).

Documents

SHOWING 2 OF 2

Publications Citing This Dataset

Filters
Title Year Author
Assessing forest fire properties in Northeastern Asia and Southern China with satellite microwave Emissivity Difference Vegetation Index (EDVI) Li, R.
A model for expressing industrial information based on object-oriented industrial heat sources detected using multi-source thermal anomaly data in China Ma, C.
Open biomass burning emissions and their contribution to ambient formaldehyde in Guangdong province, China Zhang, C.
Remote sensing mapping of peat-fire-burnt areas—Identification among other wildfires Sirin, A.
Estimating NH3 and PM2.5 emissions from the Australia mega wildfires and the impact of plume transport on air quality in Australia and New Zealand Akdemir, E. A.
Detecting low-intensity fires in east asia using viirs data—An improved contextual algorithm Zhang, N.
Fire risk assessment, spatiotemporal clustering and hotspot analysis in the Luki biosphere reserve region, western DR Congo Cizungu, N. C.
Inter-annual and seasonal variations in optical and physical characteristics of columnar aerosols over the Pokhara Valley in the Himalayan foothills Ramachandran, S.
The outflow of Asian biomass burning carbonaceous aerosol into the upper troposphere and lower stratosphere in spring—Radiative effects seen in a global model Chavan, P.
Current trend of carbon emissions from wildfires in Siberia Ponomarev, E.
SHOWING 10 OF 42

Variables

Variables are a set of physical properties whose values determine the characteristics or behavior of something. For example, temperature and pressure are variables of the atmosphere. Parameters and variables can be used interchangeably. Variable level attributes provide individual information for each variable.

The Name in this table is the variable name. Fill value indicates missing or undefined data points in a variable. Valid range is the range of values the variable can store. Scale factor is used to increase or decrease the size of an object and can be used to correct for distortion. For questions on a specific variable, please use the Earthdata Forum.

Name Description Units Data Type Fill Value Valid Range Scale Factor
Algorithm QA Pixel quality indicators Bit Field uint32 4 4 to 4294966531 N/A
CMG_night Night flag N/A uint16 N/A N/A N/A
Fire Mask Confidence of fire Class Flag uint8 0 0 to 9 N/A
FP_AdjCloud Number of adjacent cloud pixels N/A uint8 N/A N/A to 8 N/A
FP_AdjWater Number of adjacent water pixels N/A uint8 N/A N/A to 8 N/A
FP_CMG_col CMG column N/A int16 N/A N/A N/A
FP_CMG_row CMG row N/A int16 N/A N/A N/A
FP_confidence Detection confidence estimate Percent uint8 N/A N/A to 100 N/A
FP_land Land flag (0 = water pixel; 1 = land pixel) N/A uint8 N/A N/A N/A
FP_latitude Latitude at center of fire pixel Degree float32 N/A N/A to 90 N/A
FP_line Granule line of fire pixel N/A int16 N/A N/A N/A
FP_longitude Longitude at center of fire pixel Degree float32 N/A N/A to 180 N/A
FP_MAD_DT Background  brightness temperature difference mean absolute deviation Kelvin float64 N/A N/A N/A
FP_MAD_R2 Background channel 2 reflectance mean absolute deviation N/A float32 N/A N/A N/A
FP_MAD_T21 Background channel 21/22 brightness temperature mean absolute deviation Kelvin float32 N/A N/A N/A
FP_MAD_T31 Background channel 31 brightness temperature mean absolute deviation Kelvin float64 N/A N/A N/A
FP_MeanDT Background brightness temperature difference Kelvin float32 N/A N/A N/A
FP_MeanR2 Background channel 2 reflectance N/A float32 N/A N/A N/A
FP_MeanT21 Background channel 21/22 brightness temperature Kelvin float32 N/A N/A N/A
FP_MeanT31 Background channel 31 brightness temperature Kelvin float32 N/A N/A N/A
FP_NumValid Number of valid background pixels N/A int16 N/A N/A N/A
FP_power Fire radiative power Megawatts float64 N/A N/A N/A
FP_R2 Near-IR (band 2) reflectance of fire pixel (daytime only) N/A float32 N/A N/A N/A
FP_RelAzAng Relative azimuth angle Degree float32 N/A N/A to 180 N/A
FP_sample Granule sample of fire pixel N/A int16 N/A N/A N/A
FP_SolZenAng Solar zenith angle Degree float32 N/A N/A to 180 N/A
FP_T21 Channel 21/22 brightness temperature of fire pixel Kelvin float32 N/A N/A N/A
FP_T31 Channel 31 brightness temperature of fire pixel Kelvin float32 N/A N/A N/A
FP_ViewZenAng View zenith angle Degree float32 N/A N/A N/A
FP_WinSize Background window size N/A uint8 N/A N/A N/A
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