N: 90 S: -90 E: 180 W: -180
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.
Version Description
Product Summary
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.
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File Naming Convention
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
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
PRODUCT QUALITY ASSESSMENT
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Estimation of Fire Counts and Fire Radiative Power Using Satellite | Duan, Jiawei, Hu, Jiheng, Fu, Yuyun, Liu, Qingyang, Li, Rui, Wang, Yipu | Land Use/Land Cover Classification, Vegetation Index, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES | |
| Biomass burning emission analysis based on MODIS aerosol optical depth and AeroCom multi-model simulations: implications for model constraints and emission ... | Petrenko, Mariya, Kahn, Ralph, Chin, Mian, Bauer, Susanne E., Bergman, Tommi, Bian, Huisheng, Curci, Gabriele, Johnson, Ben, Kaiser, Johannes W., Kipling, Zak, Kokkola, Harri, Liu, Xiaohong, Mezuman, Keren, Mielonen, Tero, Myhre, Gunnar, Pan, Xiaohua, Protonotariou, Anna, Remy, Samuel, Skeie, Ragnhild Bieltvedt, Stier, Philip, Takemura, Toshihiko, Tsigaridis, Kostas, Wang, Hailong, Watson-Parris, Duncan, Zhang, Kai | Photosynthesis, Primary Production, Vegetation Productivity, Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES, Aerosol Backscatter, Aerosol Extinction, Aerosol Optical Depth/Thickness, Angstrom Exponent, Aerosol Particle Properties, Aerosol Radiance, Carbonaceous Aerosols, Dust/Ash/Smoke, Nitrate Particles, Organic Particles, Particulate Matter, Sulfate Particles, Optical Depth/Thickness, Radiative Flux, Reflectance, Nitrogen Oxides, Particulates, Hydrogen Cyanide, Emissions, Non-methane Hydrocarbons/Volatile Organic Compounds, Nitrogen Oxides, Sulfur Dioxide, Carbon And Hydrocarbon Compounds, Infrared Radiance, REFLECTED INFRARED, Visible Radiance, Cloud Condensation Nuclei | |
| 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 | |
| Regional wildfire smoke reduces boreal forest carbon uptake | Van Huizen, B, Thompson, D K, Wilkinson, S L, Petrone, R M, Chasmer, L E, Kljun, N, Flannigan, M D, Devito, K J, Waddington, J M | Aerosol Backscatter, Aerosol Extinction, Aerosol Optical Depth/Thickness, Angstrom Exponent, Aerosol Particle Properties, Aerosol Radiance, Carbonaceous Aerosols, Dust/Ash/Smoke, Nitrate Particles, Organic Particles, Particulate Matter, Sulfate Particles, Optical Depth/Thickness, Radiative Flux, Reflectance, Leaf Characteristics, Photosynthetically Active Radiation, Leaf Area Index (LAI), Fraction Of Absorbed Photosynthetically Active Radiation (fapar), Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES | |
| Improved estimates of smoke exposure during Australia fire seasons: importance of quantifying plume injection heights | Feng, Xu, Mickley, Loretta J., Bell, Michelle L., Liu, Tianjia, Fisher, Jenny A., Val Martin, Maria | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Land Use/Land Cover Classification | |
| Active fire-based dating accuracy for Landsat burned area maps is high in boreal and Mediterranean biomes and low in grasslands and savannas | Neves, Alana K., Pereira, Jose M.C., Silva, Joao M.N., Catarino, Silvia, Oliva, Patricia, Chuvieco, Emilio, Campagnolo, Manuel L. | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Fire Ecology, Biomass Burning, Wildfires, Burned Area | |
| Estimating NH<inf>3</inf> and PM<inf>2.5</inf> emissions from the Australia mega wildfires and the impact of plume transport on air quality in Australia and New Zealand | Akdemir, Ece Ari, Battye, William H., Myers, Casey Bray, Aneja, Viney P. | Land Use/Land Cover Classification, Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Open biomass burning emissions and their contribution to ambient formaldehyde in Guangdong province, China | Zhang, Chunlin, Li, Jiangyong, Zhao, Wenlong, Yao, Qian, Wang, Hao, Wang, Boguang | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| A model for expressing industrial information based on object-oriented industrial heat sources detected using multi-source thermal anomaly data in China | Ma, Caihong, Yang, Jin, Xia, Wei, Liu, Jianbo, Zhang, Yifan, Sui, Xin | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Assessing forest fire properties in Northeastern Asia and Southern China with satellite microwave Emissivity Difference Vegetation Index (EDVI) | Li, Rui, Fu, Yuyun, Bergeron, Yves, Valeria, Osvaldo, Chavardes, Raphael D., Hu, Jiheng, Wang, Yipu, Duan, Jiawei, Li, Dong, Cheng, Yuanxi | Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES | |
| Remote sensing mapping of peat-fire-burnt areasIdentification among other wildfires | Sirin, Andrey, Medvedeva, Maria | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| The New Transamazonian Highway: BR-319 and Its Current Environmental Degradation | Lima, Mendelson, Santana, Dthenifer Cordeiro, Junior, Ismael Cavalcante Maciel, Costa, Patricia Monique Crivelari da, Oliveira, Pedro Paulo Gomes de, Azevedo, Raul Pio de, Silva, Rogerio de Souza, Marinho, Ubiranei de Freitas, Silva, Valdinete da, Souza, Juliana Aparecida Arantes de, Rossi, Fernando Saragosa, Delgado, Rafael Coll, Teodoro, Larissa Pereira Ribeiro, Teodoro, Paulo Eduardo, Silva Junior, Carlos Antonio da | Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES, Fire Ecology, Biomass Burning, Wildfires, Burned Area | |
| Crop residue burning in northeast china and its impact on pm2.5 concentrations in South Korea | Lee, Jin-Ju, Lee, Jae-Bum, Kim, Okgil, Heo, Gookyoung, Lee, Hankyung, Lee, DaeGyun, Kim, Dai-gon, Lee, Sang-Deok | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Current trend of carbon emissions from wildfires in Siberia | Ponomarev, Evgenii, Yakimov, Nikita, Ponomareva, Tatiana, Yakubailik, Oleg, Conard, Susan G. | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Fire risk assessment, spatiotemporal clustering and hotspot analysis in the Luki biosphere reserve region, western DR Congo | Cizungu, Nadege Cirezi, Tshibasu, Elvis, Lutete, Eric, Mushagalusa, Ciza Arsene, Mugumaarhahama, Yannick, Ganza, Deckas, Karume, Katcho, Michel, Baudouin, Lumbuenamo, Raymond, Bogaert, Jan | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Highly anomalous fire emissions from the 2019-2020 Australian bushfires | Li, Fangjun, Zhang, Xiaoyang, Kondragunta, Shobha | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Detecting low-intensity fires in east asia using viirs dataAn improved contextual algorithm | Zhang, Ning, Sun, Lin, Sun, Zhendong, Qu, Yu | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Numerical investigation of atmosphere-fire interactions during high-impact wildland fire events in Greece | Kartsios, Stergios, Karacostas, Theodore, Pytharoulis, Ioannis, Dimitrakopoulos, Alexandros P. | Land Use/Land Cover Classification, RADAR IMAGERY, Terrain Elevation, Topographical Relief Maps, Digital Elevation/Terrain Model (DEM), Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Inter-annual and seasonal variations in optical and physical characteristics of columnar aerosols over the Pokhara Valley in the Himalayan foothills | Ramachandran, S., Rupakheti, Maheswar | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Increasing fire and logging disturbances in Siberian boreal forestsA case study of the Angara region | Shvetsov, Evgeny G, Kukavskaya, Elena A, Shestakova, Tatiana A, Laflamme, Jocelyne, Rogers, Brendan M | Terrain Elevation, Digital Elevation/Terrain Model (DEM), Topographical Relief Maps, Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Surface Water Features | |
| Insights into the aging of biomass burning aerosol from satellite observations and 3D atmospheric modeling: evolution of the aerosol optical properties in ... | Konovalov, Igor B., Golovushkin, Nikolai A., Beekmann, Matthias, Andreae, Meinrat O. | Aerosol Extinction, Aerosol Optical Depth/Thickness, Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Aerosol Backscatter, Aerosol Extinction, Angstrom Exponent, Aerosol Particle Properties, Aerosol Radiance, Carbonaceous Aerosols, Dust/Ash/Smoke, Nitrate Particles, Organic Particles, Particulate Matter, Sulfate Particles, Optical Depth/Thickness, Radiative Flux, Reflectance | |
| Local emission and long-range transport impacts on the CO, CO2, and CH4 concentrations at a tropical rural site | Jain, Chaithanya D., Singh, Vikas, Akhil Raj, S.T., Madhavan, B.L., Ratnam, M. Venkat | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES, Carbon Monoxide, Geopotential Height, Tropopause, Methane, Atmospheric Ozone, Surface Pressure, Outgoing Longwave Radiation, Air Temperature, Upper Air Temperature, Humidity, Total Precipitable Water, Water Vapor, Water Vapor Profiles, Cloud Liquid Water/Ice, Cloud Height, Cloud Top Pressure, Cloud Top Temperature, Cloud Vertical Distribution, Emissivity, Skin Temperature, Sea Surface Temperature | |
| Understanding agricultural fire dynamics in the southern Yucatan Peninsular Region using the MODIS (C6) active fire product | Pagan, Andrew, Rogan, John, Schmook, Birgit, Christman, Zachary, Sangermano, Florencia | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| The outflow of Asian biomass burning carbonaceous aerosol into the upper troposphere and lower stratosphere in springRadiative effects seen in a global model | Chavan, Prashant, Fadnavis, Suvarna, Chakroborty, Tanusri, Sioris, Christopher E., Griessbach, Sabine, Muller, Rolf | Fire Occurrence, Surface Thermal Properties, Land Surface Temperature, THERMAL ANOMALIES | |
| Fire detection and fire radiative power in forests and low-biomass lands in northeast AsiaMODIS versus VIIRS fire products | Fu, Yuyun, Li, Rui, Wang, Xuewen, Bergeron, Yves, Valeria, Osvaldo, Chavardes, Raphael D., Wang, Yipu, Hu, Jiheng | Land Surface Temperature, Fire Occurrence, Surface Thermal Properties, THERMAL ANOMALIES, Attitude Characteristics, ORBITAL CHARACTERISTICS, Viewing Geometry |
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 Sort descending | Description | Units | Data Type | Fill Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|
| Algorithm QA | Pixel quality indicators | Bit Field | uint32 | 4 | 0 to 4294966531 | 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 | 0 | 1 to 9 | 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 | CMG column | N/A | int16 | N/A | N/A | N/A | N/A |
| FP_CMG_row | CMG row | N/A | int16 | N/A | N/A | N/A | N/A |
| FP_confidence | Detection confidence estimate | Percent | uint8 | N/A | 1 to 100 | N/A | N/A |
| FP_land | Land flag (0 = water pixel; 1 = land pixel) | N/A | uint8 | N/A | N/A | N/A | N/A |
| FP_latitude | Latitude at center of fire pixel | Degree | float32 | N/A | -90 to 90 | N/A | N/A |
| FP_line | Granule line of fire pixel | N/A | int16 | N/A | N/A | N/A | N/A |
| FP_longitude | Longitude at center of fire pixel | Degree | float32 | N/A | -180 to 180 | N/A | N/A |
| FP_MAD_DT | Background brightness temperature difference mean absolute deviation | Kelvin | float64 | N/A | 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 | N/A |
| FP_MAD_T21 | Background channel 21/22 brightness temperature mean absolute deviation | Kelvin | float32 | N/A | 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 | N/A |
| FP_MeanDT | Background brightness temperature difference | Kelvin | float32 | N/A | N/A | N/A | N/A |
| FP_MeanR2 | Background channel 2 reflectance | N/A | float32 | N/A | N/A | N/A | N/A |
| FP_MeanT21 | Background channel 21/22 brightness temperature | Kelvin | float32 | N/A | N/A | N/A | N/A |
| FP_MeanT31 | Background channel 31 brightness temperature | Kelvin | float32 | N/A | N/A | N/A | N/A |
| FP_NumValid | Number of valid background pixels | N/A | int16 | N/A | N/A | N/A | N/A |
| FP_power | Fire radiative power | Megawatts | float64 | N/A | 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 | N/A |
| FP_RelAzAng | Relative azimuth angle | Degree | float32 | N/A | -180 to 180 | N/A | N/A |
| FP_sample | Granule sample of fire pixel | N/A | int16 | N/A | N/A | N/A | N/A |
| FP_SolZenAng | Solar zenith angle | Degree | float32 | N/A | 0 to 180 | N/A | N/A |
| FP_T21 | Channel 21/22 brightness temperature of fire pixel | Kelvin | float32 | N/A | N/A | N/A | N/A |
| FP_T31 | Channel 31 brightness temperature of fire pixel | Kelvin | float32 | N/A | N/A | N/A | N/A |
| FP_ViewZenAng | View zenith angle | Degree | float32 | N/A | N/A | N/A | N/A |
| FP_WinSize | Background window size | N/A | uint8 | N/A | N/A | N/A | N/A |