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Many factors contribute to a fire’s formation, intensity, and behavior. These factors include vegetation, precipitation, land surface temperature, soil moisture, topography, and wind. Continually monitoring factors that can contribute to a wildfire, such as changes in soil moisture before a fire or forecast changes in wind direction, can aid in predicting fire formation and fire behavior. NASA has numerous datasets that can help with these predictions.
Aboveground biomass density (AGBD) includes living or dead plant mass per unit area located above Earth's surface.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
1km | Global within a latitude extent of -52º to +52º | One-Time Estimate | 2019-2022 | GEDI | International Space Station | Model |
The Global Ecosystem Dynamics Investigation (GEDI) is a joint mission between NASA and the University of Maryland, with the instrument installed on the International Space Station. Data acquired using the instrument’s three lasers are used to construct detailed 3D maps of forest canopy height and the distribution of branches and leaves. GEDI data play an important role in understanding the amounts of biomass and carbon forests store and how much they lose when disturbed by fire. GEDI Level 4B data provide gridded 1km x 1km estimates of mean AGBD.
GEDI AGBD data can be interactively explored using NASA Worldview:
Model GEDI AGBD data can be accessed using Earthdata Search:
The Evaporative Stress Index (ESI) describes temporal anomalies in evapotranspiration (ET) and highlights areas with anomalously high or low rates of water use across the land surface. ESI also demonstrates the capability for capturing early signals of flash drought brought on by extended periods of hot, dry, and windy conditions that can lead to rapid soil moisture depletion.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Spectral Resolution | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|---|
30 m, 70 m |
CONUS |
Target areas every 1-7 Days |
2018-Present | 5 bands ranging from 8 µm to 12.5 μm (additional band at 1.6 μm for geolocation and cloud detection) |
ECOSTRESS | International Space Station | Observation and Model |
500 m | Global | Multi-Day | 2001-Present | 36 bands ranging from 0.4 µm to 14.4 µm | MODIS | Terra | Model |
NASA's ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), installed on the International Space Station in June 2018, measures the temperature of plants to better understand how they respond to the stress of insufficient water availability.
Research quality ECOSTRESS ET data products can be accessed directly using Earthdata Search. Datasets are available in HDF format but, in some cases, are customizable to GeoTIFF.
The Ecostress ESI product is derived from the ratio of Level 3 actual ET to potential ET (PET). ESI data can be used to assess agricultural drought and to observe vegetation stress.
Water use efficiency (WUE) is the ratio of carbon stored by plants to water evaporated by plants. This ratio is given as grams of carbon stored per kilogram of water evaporated over the course of the day from sunrise to sunset on the day when the ECOSTRESS data granule is acquired.
Level 4 (modeled) ECOSTRESS ESI and WUE products can be accessed using Earthdata Search or are available through NASA's Land Processes Distributed Active Archive Center (LP DAAC) :
MODIS ESI data can be visualized in a web map service via ArcGIS REST Service:
Evapotranspiration (ET) is the sum of evaporation from the land surface and transpiration in vegetation. ET measurements are useful in monitoring and assessing water availability, drought conditions, and crop production. ET can't be measured directly with satellite instruments because it is modeled based on variables including land surface temperature, air temperature, and solar radiation.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform |
Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
30 m, 70 m |
Global/CONUS | About 1-7 Days | 2018-Present | ECOSTRESS | International Space Station | Observation |
500 m | Global | 1-2 Days | 2000-Present | *MODIS | Terra | Observation and Model |
500 m | Global | 1-2 Days | 2002-Present | *MODIS | Aqua | Observation and Model |
30 m | Global | 16-Day | 1982-Present | OLI/TIERS, ETM+, TM | Landsat 4, 5, 7, 8, 9 | Observation |
0.01°, 0.1°, 0.125°, 0.25°, 1° | Global | Hourly, 3-Hour, Daily, Monthly | 1984-Present | LDAS | N/A | Model |
NASA's ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), installed on the International Space Station in June 2018, measures the temperature of plants to better understand how they respond to the stress of insufficient water availability. Learn more in this YouTube video: Monitoring Plant Health from Space: NASA’s ECOSTRESS Mission.
Research quality ECOSTRESS ET data products can be accessed directly using Earthdata Search or the Data Pool at NASA's Land Processes Distributed Active Archive Center (LP DAAC). Datasets are available in HDF format and, in some cases, are customizable to GeoTIFF:
The Moderate Resolution Imaging Spectroradiometer (MODIS) aboard NASA's Terra and Aqua satellites yields data that can be used to estimate global terrestrial ET using the MOD16 global evapotranspiration product:
The Landsat Provisional Actual Evapotranspiration (ETa) product can be used to better understand the spatiotemporal dynamics of water use over land surfaces. Provisional ETa science products are available globally for Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) scenes that can be processed to Landsat Collection 2 Level-2 Surface Temperature products.
The Landsat 7 and 8 satellites orbit Earth every eight days. Each satellite carries a thermal sensor that can measure the temperature of areas over which they pass. The sensor swath is 115 miles (185 kilometers) and the data in these images are provided at a resolution of about a quarter of an acre, or roughly about the size of a baseball infield. By combining these temperature measurements with other satellite and weather data, scientists can calculate how much evapotranspiration is taking place. This provides an orbital view of how much water is being used across the landscape and allows information to be provided for individual fields and farms just about once a week.
Research quality land surface reflectance data products can be accessed directly through the USGS:
Research quality MODIS Level 4 ET products are available in yearly and 8-day temporal resolutions with 500 m pixel size:
NASA's Land Data Assimilation System (LDAS) provides model-based ET data and includes a global collection (GLDAS) and a North American collection (NLDAS). LDAS uses measurements of precipitation, soil texture, topography, and leaf area index (LAI) to model soil moisture and ET. When calculating ET, there are biases around seasonality or local-specific effects, but the model developers try to account for these and calibrate accordingly. Estimates of ET are provided every day and integrated to get monthly, seasonal, or annual information.
GLDAS data products can be visualized using a NASA interactive data analysis tool called Giovanni:
Research quality ET data are available through NASA’s Goddard Earth Sciences Data and Information Services Center (GES DISC):
Land surface temperature (LST) is used as a measurement of vegetative stress, with higher LST values being indicative of more stressed vegetation. Since temperature is a main controller of fuel moisture content, areas with higher LST values may have lower fuel moisture. Dry fuel, such as vegetation with low moisture values in areas with high LST, plays a large factor in fire ignition, fire spread, and other fire behavior.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
1 km, 0.05° | Global | 1-2 Days | 2000-Present | *MODIS | Terra, Aqua | Observation |
750 km, 1 km | Global | Daily, Multi-Day, Monthly | 2012-Present | *VIIRS | Suomi NPP | Observation |
30 m | Global | 16-Day | 2013-Present | OLI, OLI-2 | Landsat 8, 9 | Observation |
15 m | Global | Varies | 2000-Present | ASTER | Terra | Observation |
~70 m | Global | Varies | 2018-Present | ECOSTRESS | International Space Station | Observation |
0.01°, 0.1°, 0.125°, 0.25° | Global | Hourly, 3-Hour, Daily, Monthly | 1948-Present | LDAS | N/A | Model |
0.5° x 0.625° | Global | Monthly | 1980-Present | MERRA-2 | N/A | Reanalysis |
0.25º | Global | Daily | 1950-2100 | NEX-GDDP-CMIP6 | N/A | Model/Downscaled Model Outputs |
Moderate Resolution Imaging Spectroradiometer (MODIS) LST data can be visualized and interactively explored using NASA Worldview:
Research quality LST data products can be accessed directly from Earthdata Search and also are available through the Data Pool at NASA’s Land Processes DAAC (LP DAAC).
The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) tool and MODIS subsetting tools can be used to quickly extract a subset of MODIS data for a region of interest.
MODIS LST data are available through Earthdata Search:
Near real-time (NRT) MODIS LST data are available through LANCE within 60 to 125 minutes after a satellite observation.
Research quality LST data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are available in HDF-EOS format through Earthdata Search:
A suite of MODIS LST and Emissivity (LST&E) products are available that combine MODIS data with ASTER data to leverage the strengths from both sensors. These integrated LST data can be visualized and interactively explored using NASA Worldview and can be downloaded through Earthdata Search:
The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS data can be downloaded through Earthdata Search:
The AppEEARS tool and MODIS subsetting tools can be used to quickly extract a subset of ECOSTRESS data for a region of interest.
The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites.
Research quality LST data products from VIIRS are available through Earthdata Search:
Near real-time (NRT) VIRS LST data are available through LANCE within 60 to 125 minutes after a satellite observation:
LST data are produced as part of the NASA/USGS Landsat series of Earth observing missions and are acquired by the Operational Land Imager (OLI) and OLI-2 instruments.
Landsat LST data are available through the USGS EarthExplorer:
The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Program provides LST model data derived from the MODIS and VIIRS Low Earth Orbit (LEO) satellite data record as well as LST error estimates for both day and night.
NASA’s Land Data Assimilation System (LDAS) uses sophisticated numerical models of physical processes to integrate multiple satellite and ground-based data products. LDAS uses advanced land surface modeling and assimilation techniques to deliver physically consistent and spatially and temporally continuous data.
LDAS and its various projects have a variety of uses:
LDAS components and projects:
LDAS LST data can be visualized in Giovanni. Monthly data are available from 2002:
Research quality NLDAS LST data products are available through Earthdata Search:
Please see the LDAS FAQ for additional ways to obtain, subset, and view LDAS datasets, including fast time series "data rods", file format conversion, and other web services that provide LDAS data.
The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of high-resolution, bias-corrected global downscaled climate projections derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across all four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs).
This dataset provides a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions. Uses include: air temperature, precipitation volume, humidity, stellar radiation, and atmospheric wind speed.
NEX-GDDP-CMIP6 data are available through the NASA Center for Climate Simulation (NCCS):
Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) is the latest version of global atmospheric satellite data reanalysis produced by NASA’s Global Modeling and Assimilation Office (GMAO). The dataset covers 1980-present with the latency of approximately three weeks after the end of a month.
NRT imagery of LST data can be interactively explored using NASA Worldview:
MERRA-2 data can be visualized in Giovanni:
MERRA-2 LST data are available for download using Earthdata Search.
Leaf Area Index (LAI) is a ratio of leaf surface area to ground surface area. This assigns a quantifiable value to the amount of vegetation on the ground and is an important indicator of the condition the plant. Knowing the total leaf area in a plant canopy helps scientists determine how much water will be stored and released by an ecosystem, how much leaf litter it will generate, and how much photosynthesis is occurring.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
275 m at all off-nadir angles | Global | Monthly, Seasonal | 2007-Present | MISR | Terra | Observation |
500 m | Global | 1-2 Days | 2000-Present | MODIS | Terra and Aqua | Observation |
500 m | Global | 1-2 Days | 2012-Present | VIIRS | Suomi NPP | Observation |
0.5° x 0.625° | Global | Monthly | 1980-Present | MERRA-2 | N/A | Reanalysis |
The Multi-angle Imaging SpectroRadiometer (MISR) Level 3 FIRSTLOOK Global Land product in netCDF format features LAI. This data product is a global summary of the Level 2 land/surface parameters of interest averaged over a month and reported on a geographic grid.
Global MISR LAI data are available to browse, visualize, and download through the MISR Level 3 Data Browser.
Research quality data are available through Earthdata Search:
Moderate Resolution Imaging Spectroradiometer (MODIS) LAI data can be visualized and interactively explored using NASA Worldview:
MODIS LAI Level 4 data are available starting in 2000 through Earthdata Search:
Visible Infrared Imaging Radiometer Suite (VIIRS) LAI Level 4 data are available starting in 2012 through Earthdata Search:
LAI data products created from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:
MERRA-2 data are available for download in Earthdata Search:
NASA’s satellite-based estimates of global precipitation can provide valuable information to officials monitoring wildfires. Lack of rain and low humidity dry out trees and vegetation, providing fuel for fires. In these conditions, a spark from lightning, electrical failures, human error, or planned fires can quickly get out of control. Satellite-based precipitation estimates are particularly valuable because of precipitation's relationship to wildfire hazards.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
15 km | Global | 2-Day | 2012-Near Present | *AMSR-2 | SHIZUKU (GCOM-W1) | Observation |
0.5° | Global | Daily | 1983-2021 | Varies | GPCP | Observation |
0.1° | Global | 30-Minute, Daily, Monthly | 2000-Present | Varies | GPM IMERG | Observation |
5 km | 50° N to 50° S, 180° W to 180° E | 5-Day, 10-Day, 15-Day | 2000-Present | CHIRPS-GEFS | N/A | Model |
1 km | North America, Hawaii, Puerto Rico | Daily | North America, Hawaii: 1980-Present Puerto Rico: 1950-Present |
Daymet | N/A | Model |
0.01°, 0.1°, 0.125°, 0.25°, 1° | Global | Hourly, 3-Hour, Daily, Monthly | 2000-2022 | LDAS | N/A | Model |
0.5° x 0.625° | Global | Hourly, Daily, Monthly | 1980-Present | MERRA-2 | N/A | Reanalysis |
0.25º x 0.312° | Global | 15-Minutes, Hourly | Near-real time assimilation (DAS), 10-day forecast at 00z, and 5-day forecast at 12z | GEOS-5 FP | N/A | Model |
Various | Global | Varies | 1981-Present | GFWED | N/A | Various |
0.25° | Global | Daily | 1950-2100 | NEX-GDDP-CMIP6 | N/A | Model/Downscaled Model Outputs |
The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer aboard NASA's Aqua satellite. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors.
The AIRS Precipitation Estimate is an estimate of daily precipitation measured in millimeters using cloud-related parameters of cloud-top pressure, fractional cloud cover, and cloud-layer relative humidity. The precipitation algorithm is a regression between these parameters and observed precipitation data. It is an estimate from AIRS and is intended for merging into the precipitation product of the Global Precipitation Climatology Project (GPCP).
Create and share layered maps with AIRS data using the AIRS Applications Browse Tool.
Research-quality data products can be accessed using Earthdata Search:
The Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument collects data that indicate the rate at which precipitation is falling on the ocean surface in millimeters per hour (mm/hr).
Data can be accessed and interactively explored using NASA Worldview:
Create and share layered maps with AMSR2 data using the AIRS Applications Browse Tool.
Research-quality data products can be accessed using Earthdata Search:
Near real-time (NRT) Surface Precipitation products are generated within 3 hours by the Land, Atmosphere Near real-time Capability for EOS (LANCE). The NRT products are generated in HDF-EOS-5 augmented with netCDF-4/CF metadata and are available via HTTPS. If data latency is not a primary concern, please use science quality products, which are an internally consistent, well-calibrated record of Earth's geophysical properties to support science. AMSR2 NRT data also are available through Earthdata Search:
NASA's Precipitation Measurement Missions (PMM) provide a continuous record of precipitation data through the Tropical Rainfall Measuring Mission (TRMM; operational 1997 to 2015) and the Global Precipitation Measurement mission (GPM; launched in 2014). GPM, the TRMM successor mission, provides more accurate measurements, improved detection of light rain and snow, and extended spatial coverage.
Data products from TRMM and GPM are available individually and have been integrated with data from a global constellation of satellites to yield precipitation estimates with improved spatial coverage and temporal resolution. The first integrated product was the TRMM Multi-satellite Precipitation Analysis (TMPA), which has been superseded by the Integrated Multi-satellitE Retrievals for GPM (IMERG). IMERG's multiple runs accommodate different user requirements for accuracy and latency (Early = 4 hours, e.g., for flash flood events; Late = 12 hours, e.g., for crop forecasting; and Final = 3 months, with the incorporation of rain gauge data, for research).
GPM data can be visualized using NASA Worldview:
The Short-term Prediction Research and Transition (SPoRT) project at NASA's Marshall Space Flight Center in Huntsville, Alabama, is a NASA- and NOAA-funded activity to transition experimental and quasi-operational satellite observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale. SPoRT offers a Near Real-Time Viewer for IMERG data:
Users may access and visualize these data directly through ClimateSERV. Additional datasets include IMERG, Evaporative Stress Index, Soil Moisture Active Passive (SMAP) Soil Moisture, Rainfall, and Normalized Difference Vegetation Index (NDVI).
An online interactive tool called Giovanni allows users to map visualizations of IMERG data products. These visualizations can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
NASA Earthdata GIS Products:
Near-real time (NRT) data:
Research-quality data products can be accessed using Earthdata Search:
The Global Fire WEather Database (GFWED) integrates different weather factors influencing the likelihood of a vegetation fire starting and spreading. It is based on the Fire Weather Index (FWI) System, the most widely used fire weather system in the world. The FWI System was developed in Canada, and is composed of three moisture codes and three fire behavior indices. The moisture codes capture the moisture content of three generalized fuel classes and the behavior indices reflect the spread rate, fuel consumption, and intensity of a fire if it were to start.
Another NASA source for precipitation data is Daymet, which can be accessed through NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). Daymet is a collection of gridded estimates of daily weather parameters including minimum and maximum temperature, precipitation, vapor pressure, radiation, snow water equivalent, and day length at 1 km resolution over North America, Puerto Rico, and Hawaii. Daymet data are available from 1980 to present (North America and Hawaii) and from 1950 to present (Puerto Rico). Data can be retrieved in a variety of ways, including: Earthdata Search; an API available through ORNL DAAC; ORNL DAAC tools; and through the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) application. Along with daily data, annual Daymet climatologies also are available.
NASA's Goddard Earth Observing System, Version 5 (GEOS-5) is an atmospheric model used to study the physics of the atmosphere. GEOS-5 has a series of weather maps that can be used to predict parameters such as wind speed up to 240 hours out, which can be used to forecast the movement of a smoke plume over time.
SERVIR (a joint initiative of NASA, USAID, and geospatial organizations in Asia, Africa, and Latin America) and the Climate Hazards Group (CHG) at University of California at Santa Barbara have developed an improved rainfall forecast dataset that merges two highly recognized datasets: Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and the NCEP’s Global Ensemble Forecasting System (GEFS). GEFS is a weather forecast system that provides daily forecasts out to 16 days at 1º X 1º resolution at 6-hour intervals. The combined CHIRPS-GEFS dataset uses the higher spatial resolution of CHIRPS and the advanced forecasting ability of GEFS to provide up to a 16-day forecast updated every five days at a global spatial resolution of 5 km. CHIRPS-GEFS model data are available for analysis and download through the SERVIR Product Catalog. Users may access and visualize these data directly through ClimateSERV.
The Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set that combines observations and satellite precipitation data.
Using an online interactive tool called Giovanni, users can map visualizations of GPCP Precipitation data products and download these visualizations as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
The Land Data Assimilation System (LDAS) includes a global collection (GLDAS), a North American collection (NLDAS), National Climate Assessment-Land Data Assimilation System (NCA-LDAS), and a Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). LDAS uses measurements including air temperature, precipitation, soil texture, and topography. GLDAS modeled data are available from January 1948 to present. NLDAS modeled datasets are available from January 1979 to present. FLDAS modeled datasets are available from January 1982 to present.
Data can be accessed and interactively explored using NASA Worldview:
Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:
The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of high-resolution, bias-corrected global downscaled climate projections derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across all four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs).
This dataset provides a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions. Uses include: air temperature, precipitation volume, humidity, stellar radiation, and atmospheric wind speed.
NEX-GDDP-CMIP6 data are available through the NASA Center for Climate Simulation (NCCS):
The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns as well as anomalies. There are several options available: 1-hourly, 3-hourly, 6-hourly, daily, and monthly. These options provide information on precipitation.
Data can be accessed and interactively explored using NASA Worldview:
Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Precipitation data products can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
Geographic Information Systems (GIS) products using MERRA-2 reanalysis data are produced by NASA's Prediction of Worldwide Energy Resources (POWER) project:
Research-quality air surface temperature data products can be accessed using Earthdata Search:
The NASA POWER Data Access Viewer provides MERRA-2 meteorological parameters through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are also available via API as well as via OPeNDAP:
Soil moisture is important in forecasting fire events as the dryness of the soil contributes to fire potential. Satellite data can provide a global view of soil moisture. Although ground-based measurements provide data at a higher resolution, these data are often sparse and have limited coverage. The preferred measurement (satellite vs. ground-based) should be chosen based upon your needs.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
9 km to 40 km | Near global | Daily, 3-Day | 2015-Present | Radar (active; no longer functional) *Microwave radiometer (passive) |
SMAP | Observation and Model |
25 km | Global | 50 min | 2012-Near Present | *AMSR-2 | SHIZUKU (GCOM-W1) | Observation |
0.01°, 0.1°, 0.125°, 0.25°, 1° | Global | Hourly, 3-Hour, Daily, Monthly | 1948-Present | LDAS | N/A | Model |
3 km | Continental U.S., Alaska, Puerto Rico | Daily | 2003-2021 | SPoRT-LiS | N/A | Model |
9 km | Global | 3-Hour | 2015-Present | GMAO SMAP | N/A | Model |
0.5° x 0.625° | Global | Hourly, Daily, Monthly | 1980-Present | MERRA-2 | N/A | Reanalysis |
0.125° | North America | 7-Day | 2002-Present | GRACE-DA-DM | N/A | Model |
NASA's Soil Moisture Active Passive (SMAP) satellite, launched in 2015, measures the moisture in the top 5 cm of soil globally daily and every 2 to 3 days at a resolution of 9 to 36 km.
Near real-time SMAP imagery can be interactively explored using NASA Worldview:
The Soil Moisture Visualizer, available at NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC), integrates ground-based, SMAP, and other soil moisture data into a visualization and data distribution tool.
Research quality data products can be accessed using Earthdata Search:
Near real-time (NRT) SMAP data are available through NASA’s LANCE within 60 to 125 minutes after a satellite observation:
The Advanced Microwave Scanning Radiometer (AMSR) for EOS (AMSR-E) and the AMSR-2 instruments provide volumetric soil moisture data. AMSR2 provides global passive microwave measurements of Surface Soil Moisture. Near real-time (NRT) products are generated within 3 hours of the last observations in the file.
Data can be visualized using NASA Worldview:
Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series using a NASA interactive tool called Giovanni:
Near-real time data:
Research-quality data products can be accessed using Earthdata Search:
The Short-term Prediction Research and Transition (SPoRT) project at NASA's Marshall Space Flight Center in Huntsville, Alabama, is a NASA- and NOAA-funded activity to transition experimental and quasi-operational satellite observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale.
The SPoRT-Land Information System (SPoRT-LiS) provides real-time 3 km LiS data on the following parameters: volumetric soil moisture, relative soil moisture, column-integrated relative soil moisture, and green vegetation fraction.
SPoRT offers a Near Real-Time Viewer that includes SMAP datasets for the following regions:
NASA, in collaboration with other agencies, has developed models of soil moisture content that incorporate satellite information with ground-based data (when ground-based data are available). These models are part of the Land Data Assimilation System (LDAS), which includes a global collection (GLDAS) and a North American collection (NLDAS). The Famine Early Warning Systems Network (FEWS NET) LDAS (FLDAS) datasets offer global monthly data with a 0.1º x 0.1º spatial resolution covering the period from January 1982 to present. FLDAS Soil Moisture data are available from the surface to the depth of 10 cm and 100 cm, and re-expressed as volumetric water content percent. LDAS takes inputs of measurements like precipitation, soil texture, topography, and leaf area index and uses these inputs to model output estimates of soil moisture and evapotranspiration.
FLDAS datasets also are available on the Early Warning eXplorer (EWX): Next Generation Viewer.
LDAS data are available through NASA Worldview:
The NLDAS experimental drought monitor is derived from near real-time soil moisture output model data:
Soil MERGE (SMERGE) is a root-zone soil moisture product developed by merging NLDAS land surface model output with surface satellite retrievals from the ESA (European Space Agency) Climate Change Initiative. This data product contains root-zone soil moisture of 0-40 cm layer, Climate Change Initiative (CCI)-derived soil moisture anomalies of 0-40 cm layer, and a soil moisture data estimation flag:
NLDAS, GLDAS, and SMERGE data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:
LDAS Soil Moisture data from GLDAS, NLDAS and FLDAS are available in Earthdata Search:
Weekly soil moisture and groundwater drought indicators are available each week based on terrestrial water storage observations derived from GRACE satellite data and integrated with other observations, using a sophisticated numerical model of land surface water and energy processes, referred to as GRACE Data Assimilation for Drought Monitoring (GRACE-DA-DM). GRACE-DA-DM data are available through Earthdata Search:
NASA’S Global Modeling And Assimilation Office (GMAO), in collaboration with The University of Montana and NASA's Jet Propulsion Laboratory, provides value-added Level 4 data products. These Level 4 datasets rely on the merger of Soil Moisture Active Passive (SMAP) observations into physically-based numerical models of the land surface water, energy, and carbon cycles. Available Level 4 data include global, 9-km, 3-hourly estimates of surface and root zone soil moisture, surface and soil temperature, and land surface fluxes, along with algorithm diagnostics from the ensemble-based data assimilation system. Level 4 data also include global, 9-km, daily estimates of net ecosystem carbon dioxide (CO2) exchange, component carbon stocks and fluxes, and sub-grid information broken down by plant functional types.
Near real-time SMAP imagery can be interactively explored using NASA Worldview:
These data products are available from Earthdata Search:
The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns, as well as anomalies. Hourly and monthly data options are available.
MERRA -2 Soil Moisture data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:
MERRA-2 Soil Moisture data in Earthdata Search:
Detailed topography data and imagery help fire managers and emergency management professionals anticipate areas of risk to themselves and assess the impacts of topography on fire behavior, such as topographic influences on wind direction, landslide potential, or runoff.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
30 m for U.S., 60 m, 90 m, 1 km for global | Global | One-Time Estimate | 2000 | SRTM | Space Shuttle | Observation |
30 m | Global | Multi-Year | 2000-2013 | ASTER | Terra | Observation |
25 m diameter | 51.6° N to 51.6° S | One-Time Estimate | 2019-2022 | GEDI | International Space Station | Observation and Model |
30 m | All land between 60° N and 56° S latitude. | Multi-Day | 2000 | Inputs from multiple sensors including SRTM, ASTER, GLAS, and PRISM | NASADEM | Model |
One of the most common topography data sources is the Shuttle Radar Topography Mission (SRTM). SRTM provides a digital elevation model (DEM) of all land between 60° north and 56° south latitude, which encompasses about 80% of Earth's landmass. The spatial resolution is 30 m in the horizontal plane.
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM provides a global DEM of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator). The ASTER Global DEM (GDEM) coverage spans from 83º north to 83º south latitude, encompassing 99% of Earth's landmass. The spatial resolution is 30 m in the horizontal plane.
DEM data accuracy is typically very sensitive to vegetation cover; however, data from the ASTER instrument tend to perform better over specific landcover types. Applications include identifying crop stress, mapping surface temperatures of soils and geology, and measuring surface heat balance.
The NASADEM data product was released in February 2020 and provides 1 arc-second resolution. NASADEM extends the legacy of the SRTM by improving the DEM height accuracy and data coverage as well as providing additional SRTM radar-related data products.
Imagery can be interactively explored using NASA Worldview:
Research quality topography data products are available from Earthdata Search:
In addition to Earthdata Search, SRTM and ASTER data can be accessed through the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS).
The Global Ecosystem Dynamics Investigation (GEDI) Level 3 Land Surface Metrics dataset provides gridded mean canopy height, standard deviation of canopy height, mean ground elevation, standard deviation of ground elevation, and counts of laser footprints per 1 km x 1 km grid cells within 52° north and south latitude. Data are available from April 2019 through 2022. Level 3 gridded products can be used to create digital elevation models, characterize important carbon and water cycling processes, and more.
Users may download customized subsets (Level 3 and Level 4) of GEDI data using the Spatial Data Access Tool (SDAT) available through NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC).
GEDI L3 Gridded Land Surface Metrics data can be visualized and interactively explored using NASA Worldview:
Research quality data can be accessed using Earthdata Search:
Green vegetation is generally considered healthy vegetation, and assessments of vegetation greenness are used as a proxy for vegetative health. Vegetation indices can be used to measure the amount of green vegetation over a given area, which is used as an assessment of vegetation health or stress, as well as canopy water content. Commonly used vegetation indices are the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and EVI2. The NDVI takes the difference between near-infrared (NIR) and red reflectance divided by their sum: NDVI = (NIR - VIS)/(NIR + VIS). Resulting values range from -1 to 1. Low values of NDVI correspond to low photosynthetic activity (e.g., unhealthy vegetation) or non-vegetated surfaces, such as areas of rock, sand, exposed soils, or snow. Higher NDVI values generally indicate greener, more lush vegetation, including forests, croplands, and wetlands. The EVI minimizes canopy-soil variations and improves sensitivity over dense vegetation. The EVI2 minimizes atmospheric effects.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
250 m, 500 m, 1 km | Global | 1-2 Days | 2000-Present | *MODIS | Terra and Aqua | Observation |
500 m, 1 km, 0.05° | Global | 1-2 Days | 2012-Present | *VIIRS | Suomi NPP | Observation |
0.5° x 0.625° | Global | Monthly | 1980-Present | MERRA-2 | N/A | Reanalysis |
Moderate Resolution Imaging Spectroradiometer (MODIS) Imagery can be interactively explored using NASA Worldview:
Note: The Terra/MODIS NDVI (rolling 8-day) and EVI (rolling 8-day) products are only available in Worldview for the last 20 days; older NDVI or EVI imagery are available using use the Level 3, 16-Day, or Monthly Vegetation Index and EVI layers.
NDVI data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA online interactive data analysis tool called Giovanni:
Multiple Geographic Information Systems (GIS) MODIS Surface Reflectance data layers with different band combinations are available through Esri’s ArcGIS OnLine (AGOL). NASA GIS data may be used with open-source GIS software such as Quantum GIS or Geographic Resources Analysis Support System (GRASS) GIS at no cost:
NRT MODIS vegetation data can be accessed and downloaded through LANCE:
MODIS vegetation products are available through Earthdata Search:
Vegetation products created from data acquired by the Visible Infrared Imaging Radiometer Suite (VIIRS) can be accessed in several ways.
The VNP13 and VJ113 algorithm process produces three vegetation indices: NDVI, EVI, and EVI2.
Research quality vegetation indices can be accessed directly using Earthdata Search (data are available in HDF format but in some cases are customizable to GeoTIFF):
Vegetation greenness data products created from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series using a NASA interactive data analysis tool called Giovanni:
Vegetation structure refers to the physical arrangement and organization of plant elements within a given area, such as a forest, grassland, or wetland. It encompasses the spatial distribution, size, shape, and density of various plant components, including leaves, branches, stems, and roots. Understanding vegetation structure provides valuable insights into ecosystem dynamics, biodiversity, habitat suitability, and ecological functions.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
Various | Global | Varies | 2019-Present | GEDI | International Space Station | Observation |
Various | Global | Varies | 2019-Present | ATLAS | ICESat-2 | Observation |
The Global Ecosystem Dynamics Investigation (GEDI) is a joint mission between NASA and the University of Maryland, with the instrument installed on the International Space Station. Data acquired using the instrument’s three lasers are used to construct detailed 3D maps of forest canopy height and the distribution of branches and leaves. GEDI data play an important role in understanding the amounts of biomass and carbon forests store and how much they lose when disturbed by fire.
GEDI data are available through Earthdata Search:
The Advanced Topographic Laser Altimeter System (ATLAS) aboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) measures the height of a changing Earth, one laser pulse at a time, 10,000 laser pulses a second. Launched September 15, 2018, ICESat-2 data enable scientists to measure the elevation of ice sheets, glaciers, sea ice—along with vegetation in temperate and tropical forests—in unprecedented detail.
ICESat-2 data are available through Earthdata Search:
Vegetation type, cover, and phenology are often used to monitor and evaluate fire hazards, forecast fire behavior, and develop strategies for addressing wildfire impacts.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Measurement | Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|---|
Phenology | 500 m | Global | Yearly | 2000-Present | MODIS, VIIRS | Terra and Aqua, Suomi NPP | Observation |
Plant stress indices, Canopy water content | 250 m | Global | Yearly | 2001-Present | MODIS | Terra and Aqua | Observation |
Solar Induced Fluorescence | 0.05º | Global | 16-Day | 2014-2020 | Spectrometer, MODIS | OCO-2/OCO-3, Terra and Aqua | Observation and Model |
Vegetation | 30 m | Boreal (latitudes above 50º) | One Time | 2020 | ATLAS | ICESat-2 | Observation |
Vegetation Cover | 250 m | Global | Yearly | 2001-Present | MODIS | Terra and Aqua | Observation |
Vegetation Type | 500 m | Global | Yearly | 2001-Present | MODIS | Terra and Aqua | Observation |
The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) Version 6.1 data product provides global land cover types at yearly intervals (2001-2021).
Yearly Land Cover Type data from MODIS can be interactively explored in NASA Worldview:
Level 3 Yearly Land Cover Type data from MODIS is available for download from Earthdata Search:
The Terra/MODIS Vegetation Continuous Fields (VCF) MOD44B Version 6.1 yearly product is a global representation of surface vegetation cover as gradations of three ground cover components: percent tree cover, percent non-tree cover, and percent non-vegetated surface (bare). VCF products provide a continuous, quantitative portrayal of land surface cover at 250 meter (m) pixel resolution, with a sub-pixel depiction of percent cover. The sub-pixel mixture of ground cover estimates can be used to enhance inputs to environmental modeling and monitoring applications.
Terra/MODIS vegetation data are available for download from Earthdata Search:
The Terra and Aqua combined MODIS Land Cover Dynamics (MCD12Q2) Version 6.1 data product provides global land surface phenology metrics at yearly intervals from 2001 to 2021 and is available for download through Earthdata Search:
The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Land Cover Dynamics data product provides global land surface phenology (GLSP) metrics at yearly intervals. Vegetation phenology metrics at 500 meter spatial resolution are identified for up to two detected growing cycles per year. The product contains six phenological transition dates: onset of greenness increase, onset of greenness maximum, onset of greenness decrease, onset of greenness minimum, dates of mid-greenup, and senescence phases. The product also includes the growing season length. The greenness related metrics consist of Enhanced Vegetation Index 2 (EVI2) onset of greenness increase, EVI2 onset of greenness maximum, EVI2 growing season, rate of greenness increase and rate of greenness decrease. The confidence of phenology detection is provided as greenness agreement growing season, proportion of good quality (PGQ) growing season, PGQ onset greenness increase, PGQ onset greenness maximum, PGQ onset greenness decrease, and PGQ onset greenness minimum. The final layer is quality control specifying the overall quality of the product.
VIIRS phenology data are available for download from Earthdata Search:
The Orbiting Carbon Observatory (OCO) is the first NASA mission designed to collect space-based measurements of atmospheric carbon dioxide with the precision, resolution, and coverage needed to characterize the processes controlling its buildup in the atmosphere. The Orbiting Carbon Observatory 2 (OCO-2) launched July 2, 2014.The Orbiting Carbon Observatory-3 (OCO-3) was deployed to the International Space Station in May, 2019. OCO-3 is technically a single instrument that is virtually identical to OCO-2.
OCO-2 and OCO-3 measure Solar Induced Fluorescence (SIF). SIF is a byproduct of plant photosynthesis and is a direct measurement of plant response during respiration. During photosynthesis, among the other light reactions, a photon can be re-emitted and this energy decay is known as chlorophyll fluorescence. SIF is a complement to existing greenness indicators such as the normalized difference vegetation index (NDVI) and can be used to serve as a functional proxy for Gross Primary Productivity (GPP).
OCO-2 and OCO-3 SIF data can be interactively explored in NASA Worldview:
Research-quality OCO-2 and OCO-3 Level 2 data are available for download from Earthdata Search:
This dataset provides spatially-contiguous global mean daily SIF estimates at 0.05º (approximately 5 km at the equator) spatial and 16-day temporal resolution from September 2014 through July 2020. This dataset's high resolution and global contiguous coverage enhance the synergy between satellite SIF and photosynthesis measured on the ground at consistent spatial scales.
SIF data are available for download from Earthdata Search:
Wind is a critical fire element, especially as it affects fire behavior. Knowledge of prevailing wind direction is key information for managing a fire response. In addition, the temperature differences inside and outside a fire perimeter create differences in pressure, which can lead to dangerous wind shifts.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
5 km, 10 km | Global | Hourly, Daily | 2012-Present | *AMSR-2 | SHIZUKU (GCOM-W1) | Observation |
25 km | Near-Global | Hourly, Near-Daily | 2017-Present | DDMI | CYGNSS | Observation |
0.5° x 0.625° | Global | Monthly | 1980-Present | MERRA-2 | N/A | Reanalysis |
0.25º x 0.312° | Global | 3-hourly | Near-real time assimilation (DAS), 10-day forecast at 00z and 5-day forecast at 12z | GEOS-5 | N/A | Model |
Various | Global | Varies | 1981-Present | GFWED | N/A | Various |
0.25° | Global | Daily | 1950-2100 | NEX-GDDP-CMIP6 | N/A | Model/Downscaled Model Outputs |
Data from the Advanced Microwave Scanning Radiometer 2 (AMSR2), often in near real-time (NRT), can be accessed and interactively explored using NASA Worldview:
Create and share layered maps with AMSR2 data using the AIRS Applications Browse Tool.
Research-quality AMSR-2 Wind, Level 2 NRT data are available in Earthdata Search from NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) 75 to 140 minutes after a satellite observation.
The Delay Doppler Mapping Instrument (DDMI) is the single instrument aboard the eight individual satellites comprising NASA’s Cyclone Global Navigation Satellite System (CYGNSS) constellation. Each DDMI contains both a traditional Global Positioning System (GPS) navigation receiver integrated with a reflections processor. The DDMI aboard each of the eight CYGNSS micro-satellites receives signals broadcast from four orbiting GPS satellites along with the return of the same GPS satellite’s signal reflected from Earth. These signals are used to provide measurements of wind speed over the ocean to better understand and predict tropical cyclones.
Data can be accessed and interactively explored using NASA Worldview:
Research-quality data products can be accessed using Earthdata Search:
The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is the latest atmospheric reanalysis of the modern satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO). Surface wind data are available through MERRA-2 beginning in 1980 and running a few weeks behind real time.
The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns as well as anomalies. There are several options available: 1-hourly, 3-hourly, 6-hourly, daily, and monthly. These options provide information on precipitation.
Monthly data can be accessed and interactively explored using NASA Worldview:
MERRA-2 Weather Analyses Maps
Using an online interactive tool called Giovanni, users can map visualizations of MERRA-2 wind data products and download them as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
Geographic Information Systems (GIS) products using MERRA-2 reanalysis data are produced by NASA's Prediction of Worldwide Energy Resources (POWER) Project:
Research-quality data products can be accessed using Earthdata Search:
The NASA POWER Data Access Viewer provides MERRA-2 meteorological parameters (including wind direction at 2, 10, and 50 meters) through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are also available via API, GIS enabled, as well as via OPeNDAP.
NASA's Goddard Earth Observing System, Version 5 (GEOS-5) is an atmospheric model used to study the physics of the atmosphere. GEOS-5 has a series of weather maps that can be used to predict parameters such as wind speed up to 240 hours out, which can be used to forecast the movement of a smoke plume over time.
The Global Fire WEather Database (GFWED) integrates different weather factors influencing the likelihood of a vegetation fire starting and spreading. It is based on the Fire Weather Index (FWI) System, the most widely used fire weather system in the world. The FWI System was developed in Canada, and is composed of three moisture codes and three fire behavior indices. The moisture codes capture the moisture content of three generalized fuel classes and the behavior indices reflect the spread rate, fuel consumption and intensity of a fire if it were to start.
The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of high-resolution, bias-corrected global downscaled climate projections derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across all four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs).
This dataset provides a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions. Uses include: air temperature, precipitation volume, humidity, stellar radiation, and atmospheric wind speed.
NEX-GDDP-CMIP6 data are available through the NASA Center for Climate Simulation (NCCS):
Near real-time (NRT) data for Corrected Reflectance, Surface Reflectance, Thermal Anomalies/Fire, Aerosols, and Lightning are available. NRT data enable monitoring and decision making during ongoing events.
Aerosols are fine suspended particles (such as smoke or ash) that absorb and scatter incoming sunlight. This absorption and scattering of light reduces visibility and increases the optical depth. Satellite-derived aerosol index (AI) products are useful for identifying and tracking the long-range transport of smoke from wildfires or biomass burning. AI indicates the presence of ultraviolet (UV)-absorbing aerosols; the higher the AI, the higher the concentration in the atmosphere. Currently, there are two near real-time AI data products available: one from the Ozone Monitoring Instrument (OMI) aboard NASA’s Aura satellite and one from the Ozone Mapping and Profiler Suite (OMPS) aboard the joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite. For both satellites, the spatial resolution is 2 km and the temporal resolution is daily.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
13 km x 24 km, 13 x 12 km 0.25°, 1° |
Global | 98 minutes, 32 days |
2004-Present | *OMI | Aura | Observation |
50 km* | Global | 101 Minutes, Daily | 2018-Present | *OMPS | Suomi NPP | Observation |
7 km x 3.5 km, 5.5 km x 3.5 km |
Global | 101.5 Minutes, Daily | 2017-Present | TROPOMI | Sentinel-5P | Observation |
0.5º x 0.625° | Global | Monthly | 1980-Present | MERRA-2 | N/A | Reanalysis |
The Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite provides data at individual wavelengths from the ultraviolet (UV) to the visible. This is important because pollutants have different spectral signatures. For example, a wavelength range around 400 nm can be used to detect elevated layers of absorbing aerosols such as biomass burning and desert dust plumes.
Daily data can be accessed and interactively explored using NASA Worldview:
Using an online interactive tool called Giovanni, map visualizations of OMI AI data products can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
Level 2 data are available
The OMPS AI layer indicates the presence of UV-absorbing particles in the air. AI from OMPS also includes the PyroCumuloNimbus (pyroCb) product, which makes it easier to track the extent and spread of smoke from wildfires, volcanic eruptions, and other events that create exceptionally high AI values. Typically the AI signal remains below 5.0 for most smoke and dust events and the OMPS AI product with an AI range of 0.0 to 5.0 satisfies the needs of most users. However, the AI signal for pyroCb events, which are both dense and high in the atmosphere, easily can be much higher than 5.0; the pyroCb product has an AI range from 0 to >=50.
Daily data can be accessed and interactively explored using NASA Worldview:
Level 2 data are available in Earthdata Search:
The Tropospheric Monitoring Instrument (TROPOMI) was co-funded by ESA (European Space Agency) and the Netherlands, and is the single payload aboard ESA's Sentinel-5P spacecraft. TROPOMI measures solar radiation reflected by and radiated from Earth.
Research quality data from Earthdata Search:
The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is the latest version of global atmospheric reanalysis for the satellite era produced by NASA's Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980 to present with the latency of about 3 weeks after the end of a month.
Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Aerosol Index data products can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
Aerosol optical depth (AOD) is a measure of the level to which aerosols prevent light from traveling through the atmosphere or the quantity of light removed from a beam by scattering and/or absorption during its path through a medium. The AOD value represents the loading of particles in the entire column of the atmosphere at one location from Earth's surface to the top of the atmosphere and is dependent upon particle concentration, shape, size, chemical composition, location in the atmosphere, and wavelength of measurement. As AOD increases to greater than 3.0, aerosols become so dense that the Sun is obscured. From an observer on the ground, an AOD of less than 0.1 is characteristic of clear sky, bright Sun, and maximum visibility.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
250 m, 500 m, 1 km, 10 km, 3 km | Global | Daily, 8-Day, 16-Day, Monthly, Quarterly, Yearly | 2000 (Terra)/2002 (Aqua)-Present | MODIS | Terra and Aqua | Observation |
0.25º x 0.312° | Global | 15-Minute, Hourly | Near-real time assimilation (DAS), 10-day forecast at 00z, and 5-day forecast at 12z | GEOS (GEOS-FP/GEOS-CF) | N/A | Model |
6 km, 1° | Global | *6-Minute, Daily, Monthly |
2012-Present | VIIRS: Deep Blue |
Suomi NPP and NOAA-20 |
Observation |
6 km | Global | < 1Mminute | 2012-Present |
*VIIRS: Dark Target |
Suomi NPP | Observation |
0.25°, 13 km x 24 km | Global | *~98-Minute, Daily |
2004-Present | *OMI | Aura | Observation |
10 km | Global | 12-24 Per Day | 2017-Present | EPIC | DSCOVR | Observation |
0.5° x 0.625° | Global | 1-Hour, Monthly | 1980-Near Present | MERRA -2 | N/A | Reanalysis |
N/A | Varies | Sub-Hourly | Varies by Site | AERONET | Ground-Based | Observation |
Moderate Resolution Imaging Spectroradiometer (MODIS) instruments are aboard NASA’s Terra (launched 1999) and Aqua (launched 2002) satellites and provide estimates about AOD. Terra's orbit is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon.
MODIS daily data can be visualized and interactively explored using NASA Worldview:
The non-aerosol signal of surface reflectance needs to be separated from the aerosol signal to accurately obtain AOD. Scientists have developed two algorithms for MODIS data to account for these effects: Dark Target and Deep Blue. In the latest dataset collection, these two algorithms have been merged, using the highest quality for each. For more information about the differences between these, see What is the difference between dark target and deep blue?
Dark Target and Deep Blue data can be interactively visualized using NASA Worldview:
Using an online interactive tool called Giovanni, map visualizations of MODIS AOD data products can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
Research quality MODIS data products can be accessed directly from Earthdata Search:
Near real-time (NRT) MODIS Surface Reflectance data are available through NASA’s LANCE within 60 to 125 minutes after a satellite observation.
MODIS/Terra and MODIS/Aqua NRT data in Earthdata Search:
MODIS/Terra and MODIS/Aqua Combined NRT data in Earthdata Search:
The Visible Infrared Imaging Radiometer Suite (VIIRS) instruments aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites collect AOD data at a finer spatial resolution than MODIS. VIIRS uses the Deep Blue algorithm over land and the Satellite Ocean Aerosol Retrieval (SOAR) algorithm over water to determine atmospheric aerosol loading for daytime cloud-free, snow-free scenes. Downloading a VIIRS data file provides the data with just the land algorithm, just the ocean algorithm, and the merged algorithm.
Daily data can be accessed and interactively explored using NASA Worldview:
Research quality data products can be accessed using Earthdata Search:
The Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite has a coarser spatial resolution than MODIS and VIIRS, but provides data at individual wavelengths from the ultraviolet (UV) to the visible. This is important because pollutants have different spectral signatures. For example, a wavelength range around 400 nm can be used to detect elevated layers of absorbing aerosols such as biomass burning and desert dust plumes.
Daily data can be accessed and interactively explored using NASA Worldview:
Using an online interactive tool called Giovanni, map visualizations of OMI AOD data products can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
The Earth Polychromatic Imaging Camera (EPIC) is a 10-channel spectroradiometer (317 to 780 nm) aboard NOAA’s Deep Space Climate Observatory (DSCOVR) spacecraft (which is a partnership between NASA, NOAA, and the U.S. Air Force). EPIC provides color images of the entire sunlit face of Earth at least once every two hours from 1 million miles away. DSCOVR’s location gives it a unique angular perspective that is used to measure ozone, aerosols, cloud reflectivity, cloud height, and vegetation properties and to estimate UV radiation.
Research quality data can be accessed using Earthdata Search:
The Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) offers a data assimilation of AOD analysis available every three hours from 1980 to present with a latency of about three weeks after the end of a month.
Monthly data can be accessed and explored interactively using NASA Worldview:
NASA's Global Modeling and Assimilation Office’s (GMAO) offers visualizations of MERRA-2 AOT data:
Using an online interactive tool called Giovanni, map visualizations of MERRA-2-analyzed AOD data products can be downloaded as PNG images or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
Research quality data products can be accessed using Earthdata Search and Google Earth Engine:
Thirty years of ground-based AOD measurements are available through NASA’s Aerosol Robotic Network (AERONET). AERONET is a global network of ground-based Sun photometers. These photometers calculate AOD and the amount of water vapor in the atmosphere by comparing the amount of light they detect with the amount of solar radiation that would be observed in an aerosol-free atmosphere. AERONET also takes sky brightness measurements that can be used to infer aerosol size distribution, refractive index, and single scattering albedo.
Land surface reflectance is a measure of the fraction of incoming solar radiation reflected from Earth's surface to a satellite-borne or aircraft-borne sensor. These data provide an estimate of the surface spectral reflectance as it would be measured at ground level in the absence of atmospheric scattering or absorption, which is referred to as atmospheric correction. Dark, burned areas have lower surface reflectance than areas with healthy, unburned vegetation and can be assessed using visual and thermal wavelengths.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
15 m, 30 m | Global | Varies | 2000-Present | ASTER | Terra | Observation |
500 m, 1 km, 0.05° | Global | 1-2 Day | 2000-Present | *MODIS | Terra, Aqua | Observation |
375 m, 500 m, 750 m, 1 km, 5.5 km |
Global | 1-2 Day, 8-Day | 2017-Present | *VIIRS | Suomi NPP | Observation |
375m, 750m | Global | 1-Day | 2000-Present | *VIIRS | NOAA-20 | Observation |
15 m, 30 m, 60 m | Global | 16-Day | 1982-Present (various missions) | OLI-2, OLI, ETM+, TM | Landsat 4, 5, 7, 8, 9 | Observation |
30 m | Near-Global (no Antarctic) | 2-3 Day | 2013-Present | OLI, MSI | HLS: Landsat 8, 9 + Sentinel-2A/B) | Observation |
0.5 km (0.64 µm Visible), 1.0 km (Other visible/near-IR), 2 km (Bands (>2 µm)) | West: -156.1951, East: 6.198851, South: -81.14883, North: 81.14685 | Default scan mode: Full disk every 10 minutes, contiguous U.S. every 5 minutes, and two smaller, more detailed images of areas where storm activity is present, every 60 seconds (or one every 30 seconds | 2019-Present | Advanced Baseline Imager (ABI) | GOES-18; GOES-17 | Observation |
0.5 – 1 km for visible bands and 1 – 2 km for near-infrared and infrared bands | Asia-Pacific region, including Japan, Australia, East Asia, Southeast Asia, and the western Pacific Ocean | Full disk every 10 minutes; regional every 2.5 minutes | 2020-Present | Advanced Himawari Imager (AHI) | Himawari-8 | Observation |
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument is a cooperative effort between NASA and Japan's Ministry of Economy, Trade and Industry (METI).
ASTER Surface Reflectance data can be visualized and interactively explored using NASA Worldview:
Research quality ASTER data products are available through Earthdata Search:
The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard NASA’s Terra and Aqua satellites provide global information on the location of a wildfire or thermal anomaly along with smoke plume movement by measuring surface reflectance data. For information on the difference between Corrected Reflectance and Surface Reflectance Imagery.
MODIS NRT Corrected Reflectance
The MODIS Corrected Reflectance algorithm utilizes MODIS Level 1B data (the calibrated, geolocated radiances). It is not a standard, research quality product. The purpose of this algorithm is to provide natural-looking images by removing gross atmospheric effects, such as Rayleigh scattering, from MODIS visible bands 1-7. These global data are available ongoing since 2000 for 250m, 500m, and 1km. MODIS corrected reflectance imagery are available only as NRT imagery.
Information on MODIS Corrected Reflectance Imagery layers including:
MODIS Corrected Reflectance imagery is available in NASA Worldview:
NRT MODIS Correct Reflectance products are available through Earthdata Search:
The VIIRS instrument aboard the joint NOAA/NASA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites provide global measurements of global of surface reflectance data that are used to infer location of a wildfire or thermal anomaly along with smoke plume movement.
Information on VIIRS Corrected Reflectance Imagery layers including:
VIIRS NRT Corrected Reflectance imagery is available in NASA Worldview:
NRT VIIRS Correct Reflectance products are available through Earthdata Search
The Enhanced Thematic Mapper Plus (ETM+), the Operational Land Imager (OLI) and OLI-2, and the Thermal Infrared Sensor-2 (TIRS-2) are aboard the joint NASA/USGS Landsat series of satellites.
OLI data are available through NASA Worldview:
Research quality Landsat land surface reflectance data products can be accessed directly using the USGS EarthExplorer:
A high resolution imagery option is Harmonized Landsat and Sentinel-2 (HLS). HLS provides consistent surface reflectance and top of atmosphere brightness data from the OLI and OLI-2 instruments aboard the joint NASA/USGS Landsat 8 (OLI) and Landsat 9 (OLI-2) satellites and the Multi-Spectral Instrument (MSI) aboard the ESA (European Space Agency) Copernicus Sentinel-2A and Sentinel-2B satellites. The combined measurement enables global land observations every 2 to 3 days at 30 m spatial resolution.
Research quality HLS data products can be accessed through Earthdata Search:
The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) tool offers a simple and efficient way to access, transform, and visualize geospatial data from a variety of federal data archives, including USGS Landsat Analysis Ready Data (ARD) surface reflectance products.
Fires produce a heat signature that is detectable by satellites even when the fires represent a small fraction of the satellite pixel. The Geostationary Operational Environmental Satellite (GOES)-R Series (GOES-R) Advanced Baseline Imager (ABI) measures energy at different wavelengths, which is either reflected (visible and near infrared) or emitted (infrared) from Earth’s surface. Fire properties can be measured in three ways: size, temperature, and radiative power. See the ABI Bands Technical Summary Chart for more information.
GOES ABI imagery is available through NASA Worldview:
Worldview has updated the Satellite Detections of Fire Tour Story that highlights products like vector layers, the PyroCumuloNimbus (pyroCb) Aerosol Index, the Blue/Yellow Composite Day/Night Band, and the GOES-West GeoColor animation of wildfires.
GOES ABI products are available through Google Earth Engine:
For access to all GOES-R products, users can access NOAA's Archive Information Request System (AIRS) repository (no account is required). Users may filter, search, and order up to 30 days worth of files, and access up to 1,000 files per order. An email will be sent with download instructions for the processed files, with options for web and FTP downloads.
The Japan Meteorological Agency Himawari-8 satellite is in a geostationary orbit at 140.7ºE longitude and acquires imagery covering most of the Pacific Ocean, a portion of Eastern Asia, and parts of Australasia.
Wildland fires are most often started by humans, but lightning strikes have been the cause of some of the worst wildfires in the Western United States and around the world. Wildfires caused by lightning often occur in remote locations that are not easily accessible.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
4-8 km | Global within a latitude extent of -55 to +55 degrees | 1 Minute to Less Than 1 Hour | 2017-Present | *LIS | International Space Station | Observation |
The Lightning Imaging Sensor (LIS) installed on the International Space Station (ISS) records the time of occurrence of a lightning event, measures the radiant energy, and estimates the location during both day and night conditions with high detection efficiency.
LIS imagery is available through NASA Worldview (Note: LIS Flash Count and Flash Radiance version 1 imagery layers are no longer available. Version 2 imagery will be available in Worldview in the coming months):
Near real-time (NRT) LIS data are available in LANCE within two minutes of observation.
NRT ISS LIS Browse Images are available from NASA's Global Hydrometeorology Resource Center Distributed Active Archive Center (GHRC DAAC).
ISS LIS products are available through Earthdata Search:
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
250 m, 500 m, 1 km | Global | 1-2 Day | 2000-Present | *MODIS | Terra and Aqua | Observation |
375 m, 750 m | Global | 1-2 Days | 2011-Present | VIIRS | NOAA-20 | Observation |
375 m, 750 m | Global | 1-2 Days | 2011-Present | *VIIRS | Suomi NPP | Observation |
The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) both provide location information for hotspots and other thermal anomalies, which generally indicate the approximate location of one or more active fires. MODIS and VIIRS have different spatial and temporal resolutions, which impact the fire data acquired from these instruments. MODIS data are at 1 km and are acquired daily (Terra passes over the equator in the morning; Aqua passes over the equator in the afternoon, Mean Local Time [MLT]). VIIRS data are at 375 m and are acquired daily, with improved nighttime performance over MODIS. The Suomi National Polar-orbiting Partnership (Suomi NPP) satellite crosses the equator at 1:30 a.m. and 1:30 p.m., MLT. NOAA-20 follows the same orbital track as Suomi NPP, but lags behind by about 50 minutes, crossing the equator at 2:20 a.m. and 2:20 p.m., MLT.
Thermal anomalies detected by MODIS and VIIRS are determined by a contextual algorithm that utilizes the infrared or thermal radiation emitted by hotspots or fires. Each detected MODIS active fire represents the center of a 1 km pixel that is flagged by the algorithm as containing one or more fires within the pixel (see figure to right). The higher resolution of VIIRS enables it to detect fires that MODIS might not be able to sense at its lower resolution, especially fires covering relatively small areas.
MODIS data can be interactively visualized and explored in NASA Worldview:
MODIS Active Fire and Thermal Anomalies from Earthdata Search
NASA’s Fire Information for Resource Management System (FIRMS) distributes NRT active fire data within three hours of a satellite observation from NASA’s MODIS and VIIRS. There are two primary ways of exploring NRT fire data through the FIRMS:
LANCE FIRMS developers partnered with the U.S. Forest Service’s Geospatial Technology and Applications Center to create FIRMS US/Canada. In addition to the standard FIRMS, FIRMS US/Canada meets updated Forest Service requirements by offering additional contextual layers and enhancements, including classifying fires to show time since detection to depict active fire fronts, incident locations, and other information for current large fires in the U.S. and Canada. FIRMS US/Canada provides current and historical corrected reflectance imagery from NASA and NOAA satellites, U.S. and Canadian administrative ownership boundaries, daily fire danger forecasts, and current National Weather Service fire weather watch and red flag warning areas.
For more information on FIRMS:
NASA's Earth Science Applied Sciences Program has a number of resources relevant to wildfires. The Applied Sciences Wildfire program area provides applications and tools to help communities manage the impacts of fire and is part of a network of collaborators working to reduce wildfire risks before, during, and after events. The Applied Sciences Disasters program area is the home to the NASA Disasters Mapping Portal: Wildfires. The portal provides links to NASA Disasters program resources and features Event Response StoryMaps, Event Response galleries, smoke plume height examples, and wildfire damage proxy maps.
In addition to aerosols, numerous trace gases are found in the atmosphere during and after a fire event. These trace gases, like carbon monoxide (CO) and sulfur dioxide (SO2), are harmful pollutants that can impact public health. Data for trace gases are available from several satellites.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Measurement | Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|---|
Carbon Monoxide | 50 km x 50 km | Global | 6 Minutes | 2002-Present | *AIRS | Aqua | Observation |
Carbon Monoxide | 165 km x 3 km | Near-Global | Twice Daily [day, night] | 2004-Present | *MLS | Aqua | Observation |
Carbon Monoxide | ~22 km | Global | Daily, Monthly | 2000-Present | *MOPITT | Terra | Observation |
Carbon Monoxide | 5.5 km x 7 km | Global | 101.5 Minutes | 2018-Present | TROPOMI | Sentinel-5P | Observation |
Carbon Monoxide | 0.25º x 0.25° | Global | 15 Minutes, Hourly | Daily 5-Day Forecast | GEOS-CF | N/A | Model |
Carbon Monoxide | 0.25º x 0.312° | Global | 15 Minutes, Hourly | NRT Assimilation (DAS), 10-Day Forecast at 00z, 5-Day Forecast at 12z | GEOS FP | N/A | Analysis |
Sulfur Dioxide | 50 km x 50 km | Global | 6 Minutes | 2002-2023 | *AIRS | Aqua | Observation |
Sulfur Dioxide | 13 km x 24 km, 0.25°, 1° | Global | 98 Minutes, Daily | 2004-Present | OMI | Aura | Observation |
Sulfur Dioxide | 7.5 km x 3 km | Global | 101 Minutes, Daily | 2018 | OMPS | Suomi NPP | Observation |
Sulfur Dioxide | 7 x 3.5 km for all spectral bands, with the exception of the UV1 band (7 x 28 km2) and SWIR bands (7 x 7 km2) | Global | Daily | 2017-Present | TROPOMI | Sentinel-5P | Observation |
Sulfur Dioxide | 165 km x 3 km | Near-Global (-82º to +82º latitude) | 15 Minutes, Twice Daily [day, night] |
2021-Present | *MLS | Aura | Observation |
Sulfur Dioxide | 0.5° x 0.625° | Global | Hourly, 3-Hour, Monthly |
1980-Present | MERRA-2 | N/A | Reanalysis |
Sulfur Dioxide | 0.25º x 0.25° | Global | 15 Minutes, Hourly | Daily 5-Day Forecast | GEOS-CF | N/A | Model |
Sulfur Dioxide | 0.25º x 0.312° | Global | 15 Minutes, Hourly | NRT Assimilation (DAS), 10-Day Forecast at 00z, 5-Day forecast at 12z | GEOS FP | N/A | Analysis |
NASA’s Atmospheric Infrared Sounder (AIRS), in conjunction with the Advanced Microwave Sounding Unit (AMSU), senses emitted infrared and microwave radiation from Earth to provide a 3D look at the planet's weather and climate. Working in tandem, the two instruments make simultaneous observations of the surface. With more than 2,000 channels sensing different regions of the atmosphere, the system creates a global, 3D map of atmospheric temperature and humidity, cloud amounts and heights, greenhouse gas concentrations, and many other atmospheric phenomena. Launched in 2002, the AIRS and AMSU instruments are aboard NASA's Aqua spacecraft and are managed by NASA's Jet Propulsion Laboratory in Southern California.
NRT and daily data can be accessed and interactively explored using NASA Worldview:
Create and share layered maps with AIRS data using the AIRS Browse Tool.
Research quality data products can be accessed using Earthdata Search:
The Microwave Limb Sounder (MLS) instrument aboard NASA's Aura satellite collects CO Mixing Ratio layer at 215 hPa. This indicates CO levels at the vertical atmospheric pressure level of 215 hPa and is measured in parts per billion by volume (ppbv).
Daily data can be accessed and interactively explored using NASA Worldview:
Near real-time (NRT) data are typically available within three hours of observation and are broken into files containing about 15 minutes of data. The most recent seven days of data are available online. Spatial coverage is near-global (-82º to +82º latitude) with each profile spaced 1.5º or ~165 km along the orbit track (roughly 15 orbits per day). The vertical coverage is from 215 to 0.1 hPa.
Research quality (Level 2) data are available through Earthdata Search:
The Measurement of Pollution in the Troposphere (MOPITT) instrument aboard NASA's Terra satellite is designed to enhance our knowledge of the lower atmosphere and to observe how it interacts with the land and ocean biospheres. MOPITT’s specific focus is on the distribution, transport, sources, and sinks of CO in the troposphere.
Daily and monthly data can be accessed using NASA Worldview:
Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:
Research quality data products can be accessed using Earthdata Search:
The Tropospheric Monitoring Instrument (TROPOMI) was co-funded by ESA (European Space Agency) and the Netherlands, and is a space-borne, nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. TROPOMI is the single payload aboard ESA's Sentinel-5P spacecraft and measures the solar radiation reflected by and radiated from Earth.
Research quality data products can be accessed using Earthdata Search:
The GEOS Forward Processing (GEOS FP) model and data assimilation system is GMAO’s state-of-the-science numerical weather prediction (NWP) model that assimilates conventional and satellite-based weather observations, aerosol optical depth, and ozone in NRT in order to have the best initial conditions for the forecasts: 10-day at 00 UTC and 5-day at 12 UTC. GEOS FP forecasts are used to support a wide range of NASA missions and campaigns. There is no data assimilation of CO observations in GEOS FP.
GEOS-Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This community-developed, global 3D model of atmospheric chemistry is publicly available and offers five-day forecasts. Forecasts using the GEOS system are experimental and are produced for research purposes only. There is no data assimilation of CO observations in GEOS-CF.
AIRS is a hyperspectral sounder that collects daily global measurements of water vapor and temperature profiles as one of four instruments comprising the AIRS Project Instrument Suite. When launched in 2002, the AIRS Project Instrument Suite was the most advanced atmospheric sounding system ever deployed in space. AIRS data are combined with data from the Advanced Microwave Sounding Unit (AMSU-A1 and AMSU-A2) and the Humidity Sounder for Brazil (HBS) to provide 3D measurements of temperature and water vapor through the atmospheric column along with measurements of atmospheric trace gases and surface and cloud properties. These data are used by weather prediction centers to improve forecasts and to validate climate models. They also are used in applications ranging from volcanic plume detection to drought forecasting.
NRT AIRS SO2 data can be accessed and interactively explored using NASA Worldview:
Create and share layered maps with AIRS data using the AIRS Browse Tool.
Research quality data products can be accessed using Earthdata Search:
The Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite uses an imaging spectrometer to distinguish between aerosol types, such as smoke, dust, and sulfates. It measures cloud pressure and coverage, which provides data to derive tropospheric ozone. OMI provides a record of total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI also measures criteria pollutants such as ozone, nitrogen dioxide, sulfur dioxide, and aerosols, which the U.S. Environmental Protection Agency (EPA) has designated as posing serious threats to human health and agricultural productivity.
NRT data can be accessed and interactively explored using NASA Worldview:
NASA Global Sulfur Dioxide Monitoring program that provides imagery of daily SO2 from OMI, OMPS, and TROPOMI. The site also provides information on the source of emissions.
In addition, the Historical Anthropogenic Sulfur Dioxide Emissions dataset, available through NASA's Socioeconomic Data and Applications Center (SEDAC), offers annual estimates of anthropogenic global and regional SO2 emissions spanning the period 1850-2005.
Using an online interactive tool called Giovanni, map visualizations of OMI SO2 data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
Research quality data products can be accessed using Earthdata Search:
The Ozone Mapping and Profiler Suite (OMPS) aboard the joint NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite tracks the health of Earth's ozone layer and measures the concentration of atmospheric ozone (O3).
Daily data can be accessed and interactively explored using NASA Worldview:
Research quality data products can be accessed using Earthdata Search:
The Tropospheric Monitoring Instrument (TROPOMI) was co-funded by ESA (European Space Agency) and the Netherlands, and is a space-borne, nadir-viewing, imaging spectrometer covering wavelength bands between the ultraviolet and the shortwave infrared. TROPOMI is the single payload aboard ESA's Sentinel-5P spacecraft and measures the solar radiation reflected by and radiated from Earth.
Research quality data products can be accessed using Earthdata Search:
The Microwave Limb Sounder (MLS) is a passive microwave radiometer/spectrometer that measures microwave thermal emission from the limb (edge) of Earth’s atmosphere to sense vertical profiles of atmospheric gases, temperature, pressure, and cloud ice. MLS measurements are acquired globally day and night and can be obtained in the presence of ice clouds and aerosols that prevent measurements by shorter-wavelength infrared, visible, and ultraviolet sensing techniques. MLS data support investigations in three general scientific areas: stratospheric ozone layer stability, climate change, and air quality.
MLS NRT data are typically available within three hours of observation and are broken into files containing about 15 minutes of data. The most recent seven days of data are available online.
Research quality data products can be accessed using Earthdata Search:
The GEOS Forward Processing (GEOS FP) model and data assimilation system is GMAO’s state-of-the-science numerical weather prediction (NWP) model that assimilates conventional and satellite-based weather observations, aerosol optical depth, and ozone in NRT in order to have the best initial conditions for the forecasts: 10-day at 00 UTC and 5-day at 12 UTC. GEOS FP forecasts are used to support a wide range of NASA missions and campaigns.
Goddard Earth Observing System (GEOS) GEOS-Composition Forecast (CF) system forecasts trace gas and aerosol fields using constrained meteorology from GEOS and the GEOS-Chem chemical mechanism. This community-developed, global 3D model of atmospheric chemistry is publicly available and offers five-day forecasts. Forecasts using the GEOS system are experimental and use of these forecasts for purposes other than research is not recommended.
Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) is the latest version of global atmospheric reanalysis for the satellite era produced by NASA's Global Modeling and Assimilation Office (GMAO) using the Goddard Earth Observing System Model (GEOS) version 5.12.4. The dataset covers the period of 1980-Present with the latency of about three weeks after the end of a month.
Monthly modeled data from MERRA-2 can be accessed and interactively explored using NASA Worldview:
Global Modeling and Assimilation Office’s offers visualizations of MERRA-2 SO2 data:
Using an online interactive tool called Giovanni, map visualizations of MERRA-2 SO2 data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either webm video format or animated GIF images:
The regional impacts of wildfires include burned areas, changes in runoff patterns, and landslide potential. While some areas allow for ground-based measurements of these post-fire impacts, remote locations or locations with rugged terrain can make ground-based measurements impractical. Remote sensing data provide a means to extend our knowledge in these areas.
Aboveground biomass density (AGBD) refers to living or dead plant mass per unit area.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
1 km | Global Coverage Between -52º to +52º Latitude | One-Time Estimate | 2019-2022 | GEDI | International Space Station | Model |
The Global Ecosystem Dynamics Investigation (GEDI) is a joint mission between NASA and the University of Maryland, with the instrument installed on the International Space Station. Data acquired by the instrument’s three lasers are used to construct detailed 3D maps of forest canopy height and the distribution of branches and leaves. GEDI data play an important role in understanding the amounts of biomass and carbon forests store and how much they lose when these areas are disturbed by fire.
Research quality Level 3 data can be accessed using Earthdata Search:
GEDI Level 4B (model) data provide gridded 1 km x 1 km estimates of mean aboveground biomass density (AGBD).
GEDI AGBD data can be interactively explored using NASA Worldview:
Model GEDI AGBD data can be accessed using Earthdata Search:
Burned areas are characterized by deposits of charcoal and ash, removal of vegetation, and alteration of the vegetation structure. Burn severity is a quantitative measure of the effects of a fire on the environment that generally considers damage to vegetation and the impact of the burn to the soil. Fire severity is described along a spectrum, ranging from unburned/low severity, to moderate severity, and high severity.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Measurement | Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|---|
Corrected Reflectance | 500 m, 1 km, 0.05° | Global | 1-2 Days | 2000-Present | *MODIS | Terra, Aqua | Observation |
Burned Area & Depth | 500 m | Alaska and Canada | 1 Year | 2001-2019 | ABoVE: Burned Area, Depth, and Combustion for Alaska and Canada, 2001-2019 | N/A | Model |
Burned area, emissions, fractional contributions of different fire types | 0.25º | Global | 1 Day, 1 Month, 1 Year | 1997-2016 | Global Fire Emissions Database, Version 4.1 (GFEDv4) | N/A | Model |
Fire Intensity, Burn Severity Metrics | 1/4º, 1/2º, 1º | Circumpolar boreal Eurasia and North America | 1 Year | 2001-2023 | Fire Intensity and Burn Severity Metrics for Circumpolar Boreal Forests, 2001-2013 | N/A | Model |
Hyperspectral Surface Reflectance | 5 m - 20 m | Selected flight lines in North America, Europe, and southern Asia | One Time Measurement | 2006- Present | Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) | AVIRIS-C & AVIRIS-NG (Airborne) | Observation |
Ignitions, Burned Area, Emissions | 500 m | U.S.: Alaska, Canada: Yukon and the Northwest Territories | 1 Year | 2001-2018 | ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018 | N/A | Model |
Post-Fire and Unburned Field Site Data | Field plots at every 0.5 m along a 50 m long transect | Anaktuvuk River tundra fire area on the Arctic Slope of Alaska | N/A | 2008-2011 and in 2017 | ABoVE: Post-Fire and Unburned Field Site Data, Anaktuvuk River Fire Area, 2008-2017 | Field Measurement | Observation |
The Moderate Resolution Imaging Spectroradiometer (MODIS) burned area mapping algorithm takes advantage of these spectral, temporal, and structural changes. It detects the approximate date of burning at a spatial resolution of 500 m by locating the occurrence of rapid changes in daily surface reflectance time series data. The algorithm maps the spatial extent of recent fires and not of fires that occurred in previous seasons or years.
This Fire Intensity and Burn Severity Metrics for Circumpolar Boreal Forests, 2001-2013
This ABoVE: Post-Fire and Unburned Field Site Data, Anaktuvuk River Fire Area dataset includes field measurements from 26 burned and unburned transects established in 2008 in the region of the Anaktuvuk River tundra fire on the Arctic Slope of Alaska, US. Measurements include plant cover by species, shrub and tussock density, thaw depth, and soil depth. This wildfire occurred in 2007, and sampling took place in 2008-2011 and in 2017.
Datasets referenced in this Data Pathfinder are from sensors shown in the table below and is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Observation, Model, or Reanalysis |
---|---|---|---|---|---|
0.25º | Global | 1 Day, 1 Month, 1 Year | 1997-2016 | Global Fire Emissions Database, Version 4.1 (GFEDv4) | Model |
0.25º | Global | 1 Month, 1 Year | 2000-2023 | QFED | Model |
500 m | Alaska, U.S.; Yukon and the Northwest Territories, Canada | 1 Year | 2001-2018 | ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018 | Model |
The Global Fire Emissions Database (GFED) provides global estimates of monthly burned area, monthly emissions and fractional contributions of different fire types, daily or 3-hourly fields to scale the monthly emissions to higher temporal resolutions, and data for monthly biosphere fluxes. The data are at 0.25-degree latitude by 0.25-degree longitude spatial resolution and are available from June 1995 through 2016, depending on the dataset. Emissions data are available for carbon (C), dry matter (DM), carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), hydrogen (H2), nitrous oxide (N2O), nitrogen oxides (NOx), non-methane hydrocarbons (NMHC), organic carbon (OC), black carbon (BC), particulate matter less than 2.5 microns (PM2.5), total particulate matter (TPM), and sulfur dioxide (SO2) among others. These data are yearly totals by region, globally, and by fire source for each region.
The Quick Fire Emissions Dataset (QFED) was developed to enable biomass-burning emissions of atmospheric constituents to be included in the NASA Goddard Earth Observing System (GEOS) modeling and data assimilation systems. The QFED emissions are based on the fire radiative power (FRP) approach and draw on the cloud correction method developed in the Global Fire Assimilation System (GFAS), QFED however employs more sophisticated treatment of non-observed (e.g., obscured by clouds) land areas. Location and FRP of fires are obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 fire products (MOD14 and MYD14) and the MODIS Geolocation products (MOD03 and MYD03). Major advantages of QFED are the high spatial and temporal resolutions, and near-real time availability. Currently, QFED provides daily-mean emissions of black carbon, organic carbon, sulfur dioxide, carbon monoxide, carbon dioxide, PM2.5, ammonia, nitrogen oxides, methyl ethyl ketone, propylene, ethane, propane, n- and i-butane, acetaldehyde, formaldehyde, acetone and methane.
The ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT dataset provides estimates of daily burned area, carbon emissions, and uncertainty, and daily fire ignition locations for boreal fires in Alaska, U.S., and in the Yukon and Northwest Territories, Canada. The data are at 500 m resolution for the 18-year period from 2001-2018. Burned area was retrieved from combining fire perimeter data from the Alaskan and Canadian Large Fire Databases with surface reflectance and active fire data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6. Per-pixel carbon consumption was estimated based on a statistical relationship between field estimates of pyrogenic consumption and several environmental variables. To derive the carbon consumption estimates, the approach from Alaskan Fire Emissions Database (AKFED) was updated and extended for the period 2001-2018. Fire weather variables, temperature, and the drought code complemented remotely sensed tree cover and burn severity as model predictors. Fire ignition location and timing were extracted from the daily burned area maps.
Datasets referenced in this Data Pathfinder are from sensors shown in the table below and is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Observation, Model, or Reanalysis |
---|---|---|---|---|---|
500 m | Alaska, U.S.; Yukon and the Northwest Territories, Canada | 1 Year | 2001-2018 | ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018 | Model |
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
0.5 km (0.64 µm Visible), 1.0 km (Other visible/near-IR), 2 km (Bands (>2 µm)) | Full Disk, CONUS, Mesoscale | Default scan mode: Full Disk every 10 minutes; CONUS every 5 minutes; Mesoscale every 60 seconds (or one every 30 seconds) | 2019-Present | Advanced Baseline Imager (ABI) | GOES-18; GOES-17 | Observation |
15 m, 30 m | Global | Varies | 2000-Present | ASTER | Terra | Observation |
500 m, 1 km, 0.05° | Global | 1-2 Days | 2000-Present | *MODIS | Terra, Aqua | Observation |
375 m, 500 m, 750 m, 1 km, 5.5 km |
Global | 1-2 Days, 8-Day | 2017-Present | *VIIRS | Suomi NPP | Observation |
375m, 750m | Global | 1 Day | 2000-Present | *VIIRS | NOAA-20 | Observation |
15 m, 30 m, 60 m | Global | 16 Days | 1982-Present (various missions) | OLI-2, OLI, ETM+, TM | Landsat 4, 5, 7, 8, 9 | Observation |
30 m | Near-Global (no Antarctic) | 2-3 Days | 2013-Present | OLI, MSI | HLS: Landsat 8, 9 + Sentinel-2A/B) | Observation |
0.5-1 km for visible bands and 1-2 km for near-infrared and infrared bands | Asia-Pacific region, including Japan, Australia, East Asia, Southeast Asia, and the western Pacific Ocean | Full Disk every 10 minutes; Regional every 2.5 minutes | 2022-Present | Advanced Himawari Imager (AHI) | Himawari-9 | Observation |
Satellite imagery acquired by MODIS or by instruments aboard the joint NASA/USGS Landsat series of satellites enable pre- and post-fire comparisons and a change detection approach. One of the most effective ways to discriminate is by generating a normalized burn ratio (NBR). The NBR is an index designed to highlight burnt areas in large fire zones, and combines the use of both near infrared (NIR) and shortwave infrared (SWIR) wavelengths. Healthy vegetation shows a very high reflectance in the NIR, and low reflectance in the SWIR; recently burned areas have low reflectance in the NIR and high reflectance in the SWIR. To calculate NBR using Landsat data, see the NASA Applied Sciences Remote Sensing Training on Introduction to Remote Sensing for Wildfire Applications
The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument is a cooperative effort between NASA and Japan's Ministry of Economy, Trade and Industry (METI).
ASTER Surface Reflectance data can be visualized and interactively explored using NASA Worldview:
Research quality ASTER data products are available through Earthdata Search:
The Enhanced Thematic Mapper (ETM+), the Operational Land Imager (OLI) and OLI-2, and the Thermal Infrared Sensor-2 (TIRS-2) are aboard the joint NASA/USGS Landsat series of satellites.
OLI data can be visualized and interactively explored using NASA Worldview:
Research quality Landsat land surface reflectance data products can be accessed directly using USGS EarthExplorer:
Harmonized Landsat Sentinel-2 (HLS) data provide consistent global observation of Earth’s surface reflectance and top-of-atmosphere (TOA) brightness data from the Landsat OLI and OLI-2 and the ESA (European Space Agency) Multi-Spectral Instrument (MSI) aboard the Sentinel-1A/B satellites every 2-3 days with 30 meter spatial resolution.
HLS Surface Reflectance data can be visualized and interactively explored using NASA Worldview:
Research quality HLS data products can be accessed directly from Earthdata Search:
The Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) tool offers a simple and efficient way to access, transform, and visualize geospatial data from a variety of federal data archives, including USGS Landsat Analysis Ready Data (ARD) surface reflectance products.
Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance products provide an estimate of the surface spectral reflectance as it would be measured at ground level in the absence of atmospheric scattering or absorption.
MODIS Surface Reflectance data can be visualized and interactively explored using NASA Worldview:
Multiple Geographic Information Systems (GIS) MODIS Surface Reflectance data layers with different band combinations are available through Esri’s ArcGIS OnLine (AGOL). NASA GIS data may be used with open-source GIS software such as Quantum GIS or Geographic Resources Analysis Support System (GRASS). Learn more about these tools in the Use the Data section below.
Research quality MODIS data products can be accessed directly from Earthdata Search:
Near real-time (NRT) MODIS Surface Reflectance data are available through NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) within 60 to 125 minutes after a satellite observation:
The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument is aboard the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA-20 satellites.
VIIRS Surface Reflectance data can be visualized and interactively explored using NASA Worldview:
VIIRS/NPP Land Surface Reflectance Data from Earthdata Search, Data are available daily and 8-day at various spatial resolutions.
Near real-time (NRT) VIIRS Surface Reflectance data are available through LANCE within 60 to 125 minutes after a satellite observation:
The MODIS/ASTER Airborne Simulator (MASTER) is a modified Daedalus Wildfire scanning spectrometer which flies on a variety of multi-altitude research aircraft and provides spectral information similar to that which is provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), which is aboard two of NASA Earth Observing System Satellites, TERRA & AQUA. MASTER first flew in 1998 and has ongoing deployments as a Facility Instrument in the NASA Airborne Science Program (ASP). MASTER is a joint project involving the Airborne Sensor Facility (ASF) at the Ames Research Center, the Jet Propulsion Laboratory (JPL), and the Earth Resources Observation and Science Center (EROS). MASTER provides 5 to 50 m spatial resolution along select flight lines in N. America, Europe, and southern Asia.
MASTERs offer multispectral surface radiance data can be accessed directly from Earthdata Search:
The Airborne Visible InfraRed Imaging Spectrometer-Classic (AVIRIS-C) and Next Generation (AVIRIS-NG) are two Facility Instruments (FIs) that are part of NASA’s Airborne Science Program (ASP) and the Jet Propulsion Laboratory’s (JPL) Earth Science Airborne Program. The AVIRIS-C is an imaging spectrometer that delivers calibrated images of the upwelling spectral radiance in 224 contiguous spectral channels with wavelengths from 400 to 2500 nanometers (nm). The AVIRIS-NG is the successor to AVIRIS-Classic and provides high signal-to-noise ratio imaging spectroscopy measurements in 425 contiguous spectral channels with wavelengths in the solar reflected spectral range (380-2510 nm). The AVIRIS-NG started operation in 2014 and is expected to replace the AVIRIS-C instrument. Data from AVIRIS-C and AVIRIS-NG have been applied to a wide range of studies in the fields of terrestrial and coastal aquatic plant physiology, atmospheric and aerosol studies, environmental science, snow hydrology, geology, volcanology, oceanography, soil and land management, agriculture, and limnology.
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
15 km | Global | 2 Days | 2012-Near Present | *AMSR-2 | SHIZUKU (GCOM-W1) | Observation |
0.5° | Global | Daily | 1983-2021 | Varies | GPCP | Observation |
0.1° | Global | 30-minute, daily, monthly | 2000-Present | Varies | GPM IMERG | Observation |
5 km | 50° N to 50° S, 180° W to 180° E | 5-day, 10-day, 15-day | 2000-Present | CHIRPS-GEFS | N/A | Model |
1 km | North America, Hawaii, Puerto Rico | Daily | North America, Hawaii: 1980-Present Puerto Rico: 1950-Present |
Daymet | N/A | Model |
0.01°, 0.1°, 0.125°, 0.25°, 1° | Global | Hourly, 3-hourly, daily, monthly | 2000-2022 | LDAS | N/A | Model |
0.5° x 0.625° | Global | Hourly, daily, monthly | 1980-Present | MERRA-2 | N/A | Model |
0.25º x 0.312° | Global | 15 min, Hourly | Near-real time assimilation (DAS), 10-day forecast at 00z, and 5-day forecast at 12z | GEOS-5 FP | N/A | Model |
various | Global | varies | 1981-Present | GFWED | N/A | Various |
0.25° | Global | Daily | 1950-2100 | NEX-GDDP-CMIP6 | N/A | Model/Downscaled Model Outputs |
The Atmospheric Infrared Sounder (AIRS) is a grating spectrometer aboard NASA's Aqua satellite. In combination with the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), AIRS constitutes an innovative atmospheric sounding group of visible, infrared, and microwave sensors.
The AIRS Precipitation Estimate is an estimate of daily precipitation measured in millimeters using cloud-related parameters of cloud-top pressure, fractional cloud cover, and cloud-layer relative humidity. The precipitation algorithm is a regression between these parameters and observed precipitation data. It is an estimate from AIRS using a TOVS-like algorithm and is intended for merging into the precipitation product of the Global Precipitation Climatology Project (GPCP).
Create and share layered maps with AIRS data using the AIRS Browse Tool.
Research-quality data products can be accessed using Earthdata Search:
The Advanced Microwave Scanning Radiometer 2 (AMSR2) instrument collects data that indicate the rate at which precipitation is falling on the ocean surface in millimeters per hour (mm/hr).
Data can be accessed and interactively explored using NASA Worldview:
Create and share layered maps with AMSR2 data using the AIRS Browse Tool.
Research-quality data products can be accessed using Earthdata Search:
Near real-time (NRT) Surface Precipitation products are generated within 3 hours by the Land, Atmosphere Near real-time Capability for EOS (LANCE). The NRT products are generated in HDF-EOS-5 augmented with netCDF-4/CF metadata and are available via HTTPS from LANCE. If data latency is not a primary concern, please use science quality products. Science quality products are an internally consistent, well-calibrated record of Earth's geophysical properties to support science.
NASA's Precipitation Measurement Missions (PMM) provide a continuous record of precipitation data through the Tropical Rainfall Measuring Mission (TRMM; operational 1997 to 2015) and the Global Precipitation Measurement mission (GPM; launched in 2014). GPM, the TRMM successor mission, provides more accurate measurements, improved detection of light rain and snow, and extended spatial coverage.
Data products from TRMM and GPM are available individually and have been integrated with data from a global constellation of satellites to yield precipitation estimates with improved spatial coverage and temporal resolution. The first integrated product was the TRMM Multi-satellite Precipitation Analysis (TMPA), which has been superseded by the Integrated Multi-satellitE Retrievals for GPM (IMERG). IMERG's multiple runs accommodate different user requirements for accuracy and latency (Early = 4 hours, e.g., for flash flood events; Late = 12 hours, e.g., for crop forecasting; and Final = 3 months, with the incorporation of rain gauge data, for research).
GPM data can be visualized using NASA Worldview:
The Short-term Prediction Research and Transition (SPoRT) project at NASA's Marshall Space Flight Center in Huntsville, AL, is a NASA- and NOAA-funded activity to transition experimental/ quasi-operational satellite observations and research capabilities to the operational weather community to improve short-term weather forecasts on a regional and local scale. SPoRT offers a Near Real-Time Viewer for IMERG data:
Users may access and visualize these data directly through ClimateSERV. Additional datasets include IMERG, Evaporative Stress Index, SMAP Soil Moisture, Rainfall, and NDVI.
Using an online interactive tool called Giovanni, map visualizations of IMERG data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either web video format or animated GIF images:
NASA Earthdata GIS Products:
Near-real time (NRT) data:
Research-quality data products can be accessed using Earthdata Search:
The Global Fire WEather Database (GFWED) integrates different weather factors influencing the likelihood of a vegetation fire starting and spreading. It is based on the Fire Weather Index (FWI) System, the most widely used fire weather system in the world. The FWI System was developed in Canada, and is composed of three moisture codes and three fire behavior indices. The moisture codes capture the moisture content of three generalized fuel classes and the behavior indices reflect the spread rate, fuel consumption and intensity of a fire if it were to start.
Another NASA source for precipitation data is Daymet, which can be accessed through NASA's Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC). Daymet is a collection of gridded estimates of daily weather parameters including minimum and maximum temperature, precipitation, vapor pressure, radiation, snow water equivalent, and day length at 1 km resolution over North America, Puerto Rico, and Hawaii. Daymet data are available from 1980 to present (North America and Hawaii) and from 1950 to present (Puerto Rico) and can be retrieved in a variety of ways, including: Earthdata Search; an API available through ORNL DAAC; ORNL DAAC tools; and through the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS) application. Along with daily data, annual Daymet climatologies also are available.
NASA's Goddard Earth Observing System, Version 5 (GEOS-5) is an atmospheric model used to study the physics of the atmosphere in both the short term, weather, and mid to long term, climate. GEOS-5 has a series of weather maps that can be used to predict parameters such as wind speed up to 240 hours out, which can be used to forecast the movement of a smoke plume over time.
SERVIR (a joint initiative of NASA, USAID, and geospatial organizations in Asia, Africa, and Latin America) and the Climate Hazards Group (CHG) at University of California at Santa Barbara have developed an improved rainfall forecast dataset that merges two highly recognized datasets: Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) and the NCEP’s Global Ensemble Forecasting System (GEFS). GEFS is a weather forecast system that provides daily forecasts out to 16 days at 1º X 1º resolution at 6-hour intervals. The combined CHIRPS-GEFS dataset uses the higher spatial resolution of CHIRPS and the advanced forecasting ability of GEFS to provide up to a 16-day forecast updated every five days at a global spatial resolution of 5 km. CHIRPS-GEFS model data are available for analysis and download through the SERVIR Product Catalog. Users may access and visualize these data directly through ClimateSERV.
The Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set that combines observations and satellite precipitation data.
Using an online interactive tool called Giovanni, map visualizations of GPCP Precipitation data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either web video format or animated GIF images:
The Land Data Assimilation System (LDAS) includes a global collection (GLDAS), a North American collection (NLDAS), National Climate Assessment-Land Data Assimilation System (NCA-LDAS), and a Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS). LDAS uses measurements including air temperature, precipitation, soil texture, and topography. GLDAS modeled data are available from January 1948 to present. NLDAS modeled datasets are available from January 1979 to present. FLDAS modeled datasets are available from January 1982 to present.
Data can be accessed and interactively explored using NASA Worldview:
Using an online interactive tool called Giovanni, data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, or a time series, as well as downloaded in .CSV format:
The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of high-resolution, bias-corrected global downscaled climate projections derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across all four “Tier 1” greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs).
This dataset provides a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions. Uses include: air temperature, precipitation volume, humidity, stellar radiation, and atmospheric wind speed.
NEX-GDDP-CMIP6 data are available through the NASA Center for Climate Simulation (NCCS):
The Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) provides data beginning in 1980. Due to the amount of historical data available, MERRA-2 data can be used to look for trends and patterns as well as anomalies. There are several options available: 1-hourly, 3-hourly, 6-hourly, daily, and monthly. These options provide information on precipitation.
Data can be accessed and interactively explored using NASA Worldview:
Using an online interactive tool called Giovanni, map visualizations of MERRA-2 Precipitation data products can be downloaded as PNG images, or as GeoTIFF or KMZ files; time-series data are available as CSV data files, and animations are in either web video format or animated GIF images:
GIS Product using MERRA-2 reanalysis data:
Research-quality air surface temperature data products can be accessed using Earthdata Search:
The NASA Prediction Of Worldwide Energy Resources (POWER) Data Access Viewer provides MERRA-2 meteorological parameters through a web mapping application with the capability for data subsetting, charting, and visualizing. The data are also available via API as well as via OPeNDAP.
Satellite imagery acquired by MODIS or by instruments aboard the joint NASA/USGS Landsat series of satellites enable pre- and post-fire comparisons and a change detection approach. One of the most effective ways to discriminate is by generating a normalized burn ratio (NBR). The NBR is an index designed to highlight burnt areas in large fire zones, and combines the use of both near infrared (NIR) and shortwave infrared (SWIR) wavelengths. Healthy vegetation shows a very high reflectance in the NIR, and low reflectance in the SWIR; recently burned areas have low reflectance in the NIR and high reflectance in the SWIR. To calculate NBR using Landsat data, see the NASA Applied Sciences Remote Sensing Training on Introduction to Remote Sensing for Wildfire Applications
Detailed topography data and imagery help fire managers and emergency management professionals anticipate areas of risk to themselves and assess the impacts of topography on fire behavior, such as topographic influences on wind direction, landslide potential, or runoff.
Datasets referenced in this Data Pathfinder are from sensors shown in the table below and is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
30 m for U.S., 60 m, 90 m, 1 km for global | Global | One-Time Estimate | 2000 | N/A | SRTM | Observation |
30 m | Global | Multi-Year | 2000-2013 | ASTER | Terra | Observation |
25 m diameter | 51.6° N to 51.6° S | One-Time Estimate | 2019-2022 | Global Ecosystem Dynamics Investigation (GEDI) | International Space Station | Observation and Model |
30 m | All land between 60° N and 56° S latitude. | Multi-Day | 2000 | Inputs from multiple sensors including SRTM, ASTER, ICESat GLAS and PRISM | NASADEM | Model |
One of the most common topography data sources is the Shuttle Radar Topography Mission (SRTM). SRTM provides a DEM of all land between 60° north and 56° south latitude, which encompasses about 80% of Earth's landmass. The spatial resolution is 30 m in the horizontal plane.
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution of 1 arc second (approximately 30 meter horizontal posting at the equator). The ASTER Global Digital Elevation Model (GDEM) coverage spans from 83º north to 83º south latitude, encompassing 99% of Earth's landmass. The spatial resolution is 30 m in the horizontal plane.
DEM data accuracy is typically very sensitive to vegetation cover; however, data from the ASTER instrument tend to perform better over specific landcover types. Applications include identifying crop stress, mapping surface temperatures of soils and geology, and measuring surface heat balance.
The NASADEM data product was released in February 2020 and provides 1 arc-second resolution. NASADEM extends the legacy of the SRTM by improving the DEM height accuracy and data coverage as well as providing additional SRTM radar-related data products.
Imagery can be interactively explored using NASA Worldview:
Research quality topography data products are available from Earthdata Search:
In addition to Earthdata Search, SRTM and ASTER data can be accessed through AppEEARS.
The Global Ecosystem Dynamics Investigation (GEDI) Level 3 Land Surface Metrics dataset provides gridded mean canopy height, standard deviation of canopy height, mean ground elevation, standard deviation of ground elevation, and counts of laser footprints per 1 km x 1 km grid cells within 52° north and south latitude. Data are available from April 2019 through 2022. Level 3 gridded products can be used to create digital elevation models, characterize important carbon and water cycling processes, and more.
Users may download customized subsets (Level 3 and Level 4) of GEDI data using the Spatial Data Access Tool through the at The Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC).
GEDI L3 Gridded Land Surface Metrics data can be visualized and interactively explored using NASA Worldview:
Research quality data can be accessed using Earthdata Search:
Relevant datasets are from sensors shown in the table below. This is not intended to be an exhaustive list of all sensors or missions producing data relevant to wildfires. An asterisk (*) by an entry indicates that near real-time (NRT) data products are available through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE). LANCE data products are available within three hours of a satellite observation. If low-latency is not a primary concern, users are encouraged to use standard science products, which are produced using the best available calibration, ancillary, and ephemeris information. To learn more about the difference between NRT and Standard Science Products, see Near Real-Time versus Standard Products.
Spatial Resolution | Spatial Coverage | Temporal Resolution | Temporal Coverage | Name (Sensor, Model, etc.) | Satellite/ Platform | Observation, Model, or Reanalysis |
---|---|---|---|---|---|---|
250 m, 500 m, 1 km | Global | 1-2 Days | 2000-Present | *MODIS | Terra and Aqua | Observation |
500 m, 1 km, 0.05° | Global | 1-2 Days | 2012-Present | VIIRS | Suomi NPP | Observation |
275 m at all off-nadir angles | Global | Monthly, Seasonal | 2007-Present | MISR | Terra | Observation |
0.5° x 0.625° | Global | Monthly | 1980-Present | MERRA-2 | N/A | Reanalysis |
Vegetation indices can be used to measure the amount of green vegetation over a given area, which is used as an assessment of vegetation health or stress as well as canopy water content. Commonly used vegetation indices are the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and EVI2.
The NDVI takes the difference between near-infrared (NIR) and red reflectance divided by their sum: NDVI = (NIR - VIS)/(NIR + VIS). Resulting values range from -1 to 1. Low values of NDVI correspond to low photosynthetic activity (e.g., unhealthy vegetation) or non-vegetated surfaces, such as areas of rock, sand, exposed soils, or snow. Higher NDVI values generally indicate greener, more lush vegetation, including forests, croplands, and wetlands.
The EVI minimizes canopy-soil variations and improves sensitivity over dense vegetation. The EVI2 minimizes atmospheric effects.
NDVI and EVI Imagery can be interactively explored using NASA Worldview:
Note: The Terra/MODIS NDVI (rolling 8-day) and EVI (rolling 8-day) are only available in Worldview for the last 20 days; older NDVI or EVI imagery are available using use the Level 3, 16-Day, or Monthly Vegetation Index and EVI layers.
NDVI data products can be visualized as a time-averaged map, an animation, seasonally-averaged maps, scatter plots, or a time series using a NASA online interactive data analysis tool called Giovanni:
Multiple Geographic Information Systems (GIS) MODIS Surface Reflectance data layers with different band combinations are available through Esri’s ArcGIS OnLine (AGOL). NASA GIS data may be used with open-source GIS software such as Quantum GIS or Geographic Resources Analysis Support System (GRASS) GIS at no cost:
Near real-time (NRT) MODIS vegetation data can be accessed and downloaded through NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE):
Vegetation products created from data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument can be accessed in several ways.
Vegetation products created from data acquired by the Visible Infrared Imaging Radiometer Suite (VIIRS) can be accessed in several ways. The VNP13 and VJ113 algorithm process produces three vegetation indices: NDVI, EVI, and EVI2. NDVI is one of the longest continual remotely-sensed time series observations, using both the red and near-infrared (NIR) bands. EVI is a slightly different vegetation index that is more sensitive to canopy cover, while NDVI is more sensitive to chlorophyll. EVI2 is a reformation of the standard three-band EVI, using the red band and NIR band. This reformation addresses arising issues when comparing VIIRS EVI to other EVI models that do not include a blue band. EVI2 will eventually become the standard EVI.
Research quality vegetation indices can be accessed directly using Earthdata Search (datasets are available as in HDF format but are, in some cases, customizable to GeoTIFF):
The Global Ecosystem Dynamics Investigation (GEDI) is a joint mission between NASA and the University of Maryland, with the instrument installed on the International Space Station. Data acquired using the instrument’s three lasers are used to construct detailed 3D maps of forest canopy height and the distribution of branches and leaves. GEDI data play an important role in understanding the amounts of biomass and carbon forests store and how much they lose when disturbed by fire.
GEDI data are available through Earthdata Search:
The Multi-angle Imaging SpectroRadiometer (MISR) Level 3 FIRSTLOOK Global Land product in netCDF format features Leaf Area Index (LAI). This data product is a global summary of the Level 2 land/surface parameters of interest averaged over a month and reported on a geographic grid.
Global MISR LAI data are available to browse, visualize, and download through the MISR Level 3 Data Browser.
Research quality data are available through Earthdata Search:
MODIS LAI data can be visualized and interactively explored using NASA Worldview:
MODIS LAI Level 4 data are available starting in 2000 through Earthdata Search:
VIIRS LAI Level 4 data are available starting in 2012 through Earthdata Search:
ABoVE is a NASA Terrestrial Ecology Program field campaign being conducted in Alaska and western Canada for 8 to 10 years, starting in 2015. Research for ABoVE links field-based, process-level studies with geospatial data products derived from airborne and satellite sensors, providing a foundation for improving the analysis, and modeling capabilities needed to understand and predict ecosystem responses to, and societal implications of, climate change in the Arctic and Boreal regions.
This ABoVE: Burned Area, Depth, and Combustion for Alaska and Canada, 2001-2019 dataset provides annual gridded estimates of fire locations and associated burn fraction per pixel for Alaska and Canada at approximately 500 m spatial resolution for the period 2001-2019. Gridded predictions of carbon combustion and burn depth for the same period within the ABoVE extended domain using the burn area maps and field data are also available.
This ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018 datasç ignition locations for boreal fires in Alaska, U.S., and in the Yukon and Northwest Territories, Canada. The data are at 500 m resolution for the 18-year period from 2001-2018. Burned area was retrieved from combining fire perimeter data from the Alaskan and Canadian Large Fire Databases with surface reflectance and active fire data from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6. Per-pixel carbon consumption was estimated based on a statistical relationship between field estimates of pyrogenic consumption and several environmental variables. To derive the carbon consumption estimates, the approach from Alaskan Fire Emissions Database (AKFED) was updated and extended for the period 2001-2018. Fire weather variables, temperature, and the drought code complemented remotely sensed tree cover and burn severity as model predictors. Fire ignition location and timing were extracted from the daily burned area maps.
This Burned and Unburned Field Site Data, Noatak, Seward, and North Slope, AK, 2016-2018 dataset includes field measurements from unburned and burned 10 m x 10 m and 1 m x 1 m plots in the Noatak, Seward, and North Slope regions of the Alaskan tundra during July through August in the years 2016-2018. The data include vegetation coverage, soil moisture, soil temperature, soil thickness, thaw depth, and weather measurements. Measurements were recorded using ocular assessments and standard equipment. Plot photographs are included.