Wildfires Data Pathfinder - Find Data

Along with their destructive power, naturally-occurring wildfires are a vital component of forest growth, ecological succession, and soil nutrient enhancement. NASA provides datasets and tools for assessing and managing wildfires before, during, and after an event.

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. 

Common Measurements at a Glance

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

Model Data

GEDI

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.

Common Measurements at a Glance

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

Earth Observation Data by Sensor

ECOSTRESS

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.


Model Data

ECOSTRESS

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

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. 

Common Measurements at a Glance

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

Earth Observation Data by Sensor

ECOSTRESS

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:

MODIS

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:

TM, ETM+, and OLI/TIRS

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:


Model Data

ECOSTRESS

MODIS

Research quality MODIS Level 4 ET products are available in yearly and 8-day temporal resolutions with 500 m pixel size:

LDAS

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:

  • GLDAS ET
    • Data are available with a temporal resolution of 3-hourly, daily, and monthly

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.

Common Measurements at a Glance

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

Earth Observation Data by Sensor

MODIS

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.

ASTER

Research quality LST data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) are available in HDF-EOS format through Earthdata Search:

  • ASTER Surface Kinetic Temperature
    • ASTER surface temperature products are processed on-demand and must be requested with additional parameters (note that there is a limit of 2,000 granules per order)

MODIS/ASTER

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:

ECOSTRESS

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.

VIIRS

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:

OLI and OLI-2

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:

  • Landsat 8 OLI: April 2013 to present
  • Landsat 9 OLI-2: February 2022 to present

Model Data

MODIS/VIIRS

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.

LDAS

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:

  • Water resources applications
  • Drought and wetness monitoring
  • Numerical weather prediction studies
  • Interpretation of satellite and ground-based observations

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.

NEX-GDDP-CMIP6

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):


Reanalysis Data

MERRA-2

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. 

Common Measurements at a Glance

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

Earth Observation Data by Sensor

MISR

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:


Model Data

MODIS

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:

VIIRS

Visible Infrared Imaging Radiometer Suite (VIIRS) LAI Level 4 data are available starting in 2012 through Earthdata Search:


Reanalysis Data

MERRA-2

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. 

Common Measurements at a Glance

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

Earth Observation Data by Sensor

AIRS

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:

AMSR2

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:

GPM IMERG

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:

  • GPM IMERG Early
  • GPM IMERG Late
  • IMERG-Tropics

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:

  • IMERG Final
    • Data are available from 2000-present
  • GPM
    • Includes all IMERG runs: Early, Late, and Final
  • TMPA

NASA Earthdata GIS Products:

Near-real time (NRT) data:

  • IMERG Early Run Half-Hourly 
    • The Early Run product at NASA's Global Precipitation Measurement website is generated every half hour with a 6-hour latency from the time of data acquisition

Research-quality data products can be accessed using Earthdata Search:

  • TMPA
    • Rainfall estimates at 3 hours, 1 day, or NRT and accumulated rainfall at 3 hours and 1 day; data are available from 1997
  • IMERG
    • Early, Late, and Final precipitation data on the half-hour or 1-day timeframe; data are available from 2000

Model Data

Global Fire WEather Database (GFWED)

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.

Daymet

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.

GEOS-5

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.

  • GEOS-5 Weather Maps
    • Within the viewer, select the parameter or field of interest, the area of interest, and indicate the forecast time and the forecast lead hour. Selecting "Animate" shows the forecast for the given parameter over the time period indicated. Note that it may take time to load the images to animate. For wind speed near the surface, select 850 as your level (850 hPa is approximately 5,000 ft/1,500 m above sea level)

CHIRPS-GEFS

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

GPCP

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:

LDAS

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:

NEX-GDDP-CMIP6

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):


Reanalysis Data

MERRA-2

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.

Common Measurements at a Glance

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

Earth Observation Data by Sensor

SMAP

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:

  • SMAP
    • includes root zone and surface soil moisture values

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:

AMSR-2

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:

  • AMSR-2 NRT data are available through LANCE (global data from 2018 to present)

Research-quality data products can be accessed using Earthdata Search:


Model Data

SPoRT-LiS

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:

  • Enhanced Alaska (9 km)
  • Enhanced Continental U.S. (CONUS) (9 km)
  • Enhanced East Africa (9 km)
  • Level 2 CONUS
  • Level 2 East Africa

LDAS

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:

GRACE-DA-DM

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:

GMAO SMAP

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:


Reanalysis Data

MERRA-2

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.

Common Measurements at a Glance

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
Image
An ASTER GDEM image of Mt. Raung and the surrounding area.
An ASTER GDEM image of Mt. Raung, a volcano in Indonesia, and the surrounding area. Credit: LP DAAC.

Earth Observation Data by Sensor

SRTM

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.

ASTER

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:

  • SRTM
    • These data were acquired in 2000 and are in raw format (with the ".hgt" file extension), and can be opened in most Geographic Information Systems (GIS), such as ArcGIS or QGIS; data are also customizable to GeoTIFF
  • ASTER Digital Elevation Model V003
  • NASADEM

In addition to Earthdata Search, SRTM and ASTER data can be accessed through the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS).

GEDI

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.

Common Measurements at a Glance

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

Earth Observations by Sensor

Image
Screenshot of Normalized Difference Vegatation Index of King Fire area of burn.
False-color image showing changes in NDVI before (September 19, 2013; left image) and after (November 17, 2014; right image) California's King Fire in September and October, 2014. Green areas indicate healthy vegetation; red areas indicate sparse/burned vegetation. Credit: NASA's ORNL DAAC.

MODIS

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:

  • MODIS NDVI
    • Select a map plot, date range, and region and plot the data; data can be downloaded as GeoTIFF

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: 

VIIRS

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):


    Reanalysis Data

    MERRA-2

    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.

    Common Measurements at a Glance

    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

    Earth Observations by Sensor

    GEDI

    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:

    ATLAS

    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. 

    Common Measurements at a Glance

    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

    Earth Observation Data by Sensor

    Vegetation Type

    MODIS

    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:


    Vegetation Cover

    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:


    Phenology (Seasonal Cycle of Vegetation Growth)

    MODIS

    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:

    VIIRS

    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:


    Solar Induced Fluorescence

    OCO-2/OCO-3

    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:


    Model Data

    SIF

    OCO-2 and MODIS

    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.

    Common Measurements at a Glance

    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

    Earth Observation Data by Sensor

    AMSR2

    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.

    DDMI

    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:


    Reanalysis Data:

    MERRA-2

    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.


    Model Data:

    GEOS-5

    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.

    • GEOS-5 Weather Maps
      • Within the viewer, select the parameter or field of interest, the area of interest, and indicate the forecast time and the forecast lead hour. Selecting "Animate" shows the forecast for the given parameter over the time period indicated. Note that it may take time to load the images to animate. For wind speed near the surface, select 850 as your level (850 hPa is approximately 5,000 ft/1,500 m above sea level)

    Global Fire WEather Database (GFWED)

    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.

    NEX-GDDP-CMIP6

    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.

    Common Measurements at a Glance

    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

    Earth Observation Data by Sensor

    OMI

    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:

    OMI AI

    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 

    OMPS

    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:

    TROPOMI

    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:


    Reanalysis Data

    MERRA-2

    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:


      Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

      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.

      Common Measurements at a Glance

      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

      Earth Observation Data by Sensor

      MODIS

      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:

      • MODIS AOD Level 2 data
      • MODIS/Aqua AOD (3 km resolution, merged algorithm)
      • MODIS/Terra AOD (3 km resolution, merged algorithm)
      • MODIS Terra/Aqua-MAIAC Retrieval AOD (1 km resolution)
        • Multi-angle Implementation of Atmospheric Correction (MAIAC) Land AOD utilizes a new advanced algorithm that uses time series analysis and a combination of pixel- and image-based processing to improve the accuracy of cloud detection, aerosol retrievals, and atmospheric correction

      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:

      VIIRS

      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:

      • VIIRS Level 2 Deep Blue Aerosol Product
        • The product uses the Deep Blue algorithm over land and the SOAR algorithm over water to determine atmospheric aerosol loading. The product is designed to facilitate continuity in the aerosol record. Deep Blue uses measurements from multiple Earth observing satellites to determine the concentration of atmospheric aerosols along with the properties of these aerosols

      Research quality data products can be accessed using Earthdata Search:

      OMI

      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:

      • OMI AOD
        • Within Giovanni, you can plot daily data at individual wavelengths
        • Benefits of using Giovanni to view these products:
          • The two AOD products provided through Giovanni use two different algorithms. The multi-wavelength layer and the UV absorbing layer displays the degree to which airborne particles (aerosols) prevent the transmission of light through the process of absorption (attenuation), and the UV extinction layer indicates the level at which particles in the air (aerosols) prevent light (extinction of light) from traveling through the atmosphere. Toggling between these can provide more distinction on the types of aerosols present
          • OMI Multi-wavelength (OMAERO)
            • Based on the multi-wavelength algorithm and uses up to 20 wavelength bands between 331 nm and 500 nm. This algorithm uses reflectances for a wide variety of microphysical aerosol models representative of desert dust, biomass burning, volcanic, and weakly absorbing aerosol types
          • OMI UV (OMAERUV)
            • Uses the near-UV algorithm, which is capable of retrieving aerosol properties over a wider variety of land surfaces than is possible using measurements only in the visible or near-IR because the reflectance of all terrestrial surfaces (not covered with snow) is small in the UV

      EPIC

      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:


      Reanalysis Data

      MERRA-2

      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:

      • Animate and download weather maps for a variety of meteorological parameters, including MERRA-2 AOT map 
        • At the link above, you can visualize a variety of AOT parameters:  
          • Black Carbon
          • Dust
          • Fine
          • Organic Carbon
          • Sea Salt
          • Sulfate
          • Total

      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:


      Ground-Based Observations

      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.


        Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

        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.

        Common Measurements at a Glance

        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

        Earth Observation Data by Sensor

        ASTER

        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:

        MODIS

        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:

        • Corrected Reflectance True Color (Bands 1-4-3)
        • Corrected Reflectance (Bands 3-6-7)
        • Corrected Reflectance (Bands 7-2-1)

        MODIS Corrected Reflectance imagery is available in NASA Worldview:

        NRT MODIS Correct Reflectance products are available through Earthdata Search:

        VIIRS

        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:

        • Corrected Reflectance True Color (Bands I1-M4-M3)
        • Corrected Reflectance (Bands M3-I3-M11)
        • Corrected Reflectance (Bands M11-I2-I1)

        VIIRS NRT Corrected Reflectance imagery is available in NASA Worldview:

        NRT VIIRS Correct Reflectance products are available through Earthdata Search

        ETM+, OLI, OLI-2, and TIRS-2

        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:

        • Landsat 7 ETM+
        • Landsat 8 OLI
        • Landsat 9 OLI-2

        HLS

        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.

        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. 

        GOES

        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.

        Himawari

        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. 


          Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

          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.

            Common Measurements at a Glance

            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
            Image
            Animation of U.S. lightning with colored dots indicating lighting strikes.
            Animation of LIS-detected lightning strikes over the Central U.S. from June 7 to 17, 2021. Colors indicate number of detected lightning strikes. Click on image to start animation. Credit: NASA Worldview.

            Earth Observation Data

            LIS

            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:


              Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

              Satellite-based sensors can detect the signal of fire hotspots, also called thermal anomalies, because the signal measured by the sensor in space in the thermal infrared bands appears to be an anomaly compared to the signal emanated from the background land. These thermal anomalies may originate from fire, hot smoke, agriculture, or other sources. Thermal anomaly data can indicate the locations of fires as well as their frequency and intensity.

              Common Measurements at a Glance

              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

              Earth Observation Data by Sensor

              Image
              image
              Example of MODIS thermal anomaly detection showing ground conditions (top boxes) and resulting MODIS detection (lower boxes). Credit: NASA FIRMS.

              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

              MODIS data can be interactively visualized and explored in NASA Worldview:

              MODIS Active Fire and Thermal Anomalies from Earthdata Search

              VIIRS

              Image
              This screen capture from FIRMS shows Landsat active fire imagery of the Double Creek Fire in Oregon on September 10, 2022.

              Fire Information for Resource Management System (FIRMS)

              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:

              1. Through the FIRMS interactive map. The FIRMS interactive map provides NRT data along with the full archive of global MODIS and VIIRS fire locations. It also enables users to view the MODIS Terra/Aqua Global Burned Area data product (with an approximate four-month lag between the date of burn and the availability of the burned area data product in FIRMS).
              2.  Direct download of the NRT data. Active fire data are available for download for any area of interest in NRT and from the full archive. 

              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 Applied Sciences Wildfire Products

              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.


                Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                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.

                Common Measurements at a Glance

                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

                Carbon Monoxide (CO) Data

                Earth Observation Data by Sensor

                AIRS

                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:

                • AIRS CO data
                  AIRS Level 2 data are nominally 45 km/pixel at the equator, but the data in Worldview have been resampled into a 32 km/pixel visualization. The data are in units of parts per billion by volume at the 500 hPa pressure level, which is approximately 5,500 meters (18,000 feet) above sea level

                Create and share layered maps with AIRS data using the AIRS Browse Tool.

                Research quality data products can be accessed using Earthdata Search:

                • AIRS CO data
                  AIRS measures abundances of trace gases in the atmosphere, including CO. Data are available daily (AIRS3STD), over eight days (AIRS3ST8), or monthly (AIRS3STM). The instrument measures the amount of CO in the total vertical column profile of the atmosphere (from Earth’s surface to top-of-atmosphere)

                MLS

                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:

                • MLS CO data: Visualization of the amount of Carbon Monoxide (215 hPa, Day and Night) (measured in ppbv) 

                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:

                MOPITT

                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:

                • MOPITT CO data (Monthly) (Note: At time of publication, these data are only available through May 2022)

                Research quality data products can be accessed using Earthdata Search:

                • MOPITT CO data
                  MOPITT measures the amount of CO present in the total vertical column of the lower atmosphere (troposphere) and is measured in mole per square centimeter (mol/cm2); data are available daily or monthly, and are acquired using the thermal and near-infrared channels

                TROPOMI

                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:


                Model Data

                GEOS FP

                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-CF

                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. 

                Sulfur Dioxide (SO2) Data

                Earth Observation Data by Sensor:

                AIRS

                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:

                OMI

                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:

                • OMI SO2 data
                  OMI provides daily total column data at a resolution of 13x24 km; data are in HDF5 format

                OMPS

                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:

                TROPOMI

                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:

                MLS

                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:


                Analysis Data

                GEOS FP

                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.


                Model Data

                GEOS-CF

                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.


                Reanalysis Data

                MERRA-2

                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:

                For information on NASA's data collections related to air quality, visit the Air Quality Data Pathfinder.


                  Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                  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.

                  Common Measurements at a Glance

                  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

                  Earth Observation Data by Sensor

                  GEDI

                  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:


                  Model Data

                  GEDI

                  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:


                    Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                    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.

                    Common Measurements at a Glance

                    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

                    Earth Observation Data by Sensor

                    MODIS

                    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.

                    • Burned Area Data from FIRMS
                    • MODIS/Aqua Burn Scar Corrected Reflectance (GIS Web Map)
                      This daily visualization represents a "false color" band combination (7-2-1) of data continuously collected by the MODIS instrument on the Aqua satellite and is useful for distinguishing burn scars from naturally low vegetation or bare soil.
                    • MODIS/Terra Burn Scar Corrected Reflectance (GIS Web Map)
                      This daily visualization represents a "false color" band combination (7-2-1) of data continuously collected by the MODIS instrument on the Terra satellite and is useful for distinguishing burn scars from naturally low vegetation or bare soil.
                    • Burned Area Data from Earthdata Search
                      The Terra and Aqua combined Burned Area data product (MCD64A1) is a monthly, global, gridded 500 m product containing per-pixel burned-area and quality information.
                    • MODIS Corrected Reflectance Bands 7-2-1 in Worldview
                      This MODIS band combination is most useful for distinguishing burn scars from naturally low vegetation. When bare soil becomes exposed, the brightness in Band 1 may increase, but that may be offset by the presence of black carbon residue; the near infrared (Band 2) will become darker, and Band 7 becomes more reflective. When assigned to red in the image, Band 7 will show burn scars as deep or bright red, depending on the type of vegetation burned, the amount of residue, or the completeness of the burn.
                    • MODIS Land Surface Reflectance from Earthdata Search
                      The MODIS Land Surface Reflectance product is available from both the Terra (MOD09) and Aqua (MYD09) satellites. The sensor resolution is 500 m, imagery resolution is 500 m, and the temporal resolution is daily.green. Using specific band combinations (such as 7-2-1 for wildfires) enables environmental boundaries to be more easily identified.

                    Model Data

                    Fire Intensity and Burn Severity Metrics for Circumpolar Boreal Forests, 2001-2013

                    This Fire Intensity and Burn Severity Metrics for Circumpolar Boreal Forests, 2001-2013

                    ABoVE: Burned Area, Depth, and Combustion for Alaska and Canada, 2001-2019

                    • 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.

                    ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018

                    • This ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018 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.

                    ABoVE: Post-Fire and Unburned Field Site Data, Anaktuvuk River Fire Area, 2008-2017

                    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.

                    Global Fire Atlas with Characteristics of Individual Fires, 2003-2016

                    • The Global Fire Atlas is a global dataset that tracks the day-to-day dynamics of individual fires to determine the timing and location of ignitions, fire size, duration, daily expansion, fire line length, speed, and direction of spread. These individual fire characteristics were derived based on the Global Fire Atlas algorithm and estimated day of burn information at 500-m resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 MCD64A1 burned area product. The algorithm identified 13.3 million individual fires (>=21 ha or 0.21 km2; the size of one MODIS pixel) over the 2003-2016 study period.

                    Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                    Common Measurements at a Glance

                    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

                    Model Data

                    GFED

                    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.

                    QFED

                    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.

                    ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018

                    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.


                      Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                      Common Measurements at a Glance

                      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

                      Model Data:

                      ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018

                      • This 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.

                      Global Fire Atlas with Characteristics of Individual Fires, 2003-2016

                      • The Global Fire Atlas is a global dataset that tracks the day-to-day dynamics of individual fires to determine the timing and location of ignitions, fire size, duration, daily expansion, fire line length, speed, and direction of spread. These individual fire characteristics were derived based on the Global Fire Atlas algorithm and estimated day of burn information at 500-m resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 MCD64A1 burned area product. The algorithm identified 13.3 million individual fires (>=21 ha or 0.21 km2; the size of one MODIS pixel) over the 2003-2016 study period.

                        Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                        Common Measurements at a Glance

                        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

                        Earth Observation Data by Sensor

                        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

                        Space-based Platforms:

                        ASTER

                        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:

                        ETM, OLI, OLI-2, and TIRS-2

                        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:

                        • Landsat 7 ETM+
                        • Landsat 8 OLI
                        • Landsat 9 OLI-2

                        HLS

                        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. 

                        MODIS

                        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:

                        VIIRS

                        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:

                        • VIIRS NRT Data in LANCE for 357 m, 750 m
                        • VIIRS NRD Data in Lance for 1 km and 500 m

                        Air-based Platforms:

                        MASTER

                        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:

                        AVIRIS

                        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.


                          Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                          Common Measurements at a Glance

                          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

                          Earth Observation Data by Sensor

                          AIRS

                          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:

                          AMSR2

                          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.

                          GPM

                          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.

                          IMERG

                          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:

                          • GPM IMERG Early
                          • GPM IMERG Late
                          • IMERG - Tropics

                          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:

                          • IMERG Final: Data are available from 2000-present
                          • GPM: includes all IMERG runs, Early, Late, and Final
                          • TMPA

                          NASA Earthdata GIS Products:

                          Near-real time (NRT) data:

                          • IMERG Early Run Half-Hourly 
                            • The "early run" product at NASA's Global Precipitation Measurement website is generated every half hour with a 6-hour latency from the time of data acquisition

                          Research-quality data products can be accessed using Earthdata Search:

                          • TMPA
                            Rainfall estimates at 3 hours, 1 day, or NRT and accumulated rainfall at 3 hours and 1 day. Data are available from 1997
                          • IMERG
                            Early, Late, and Final precipitation data on the half-hour or 1-day timeframe. Data are available from 2000

                          Model Data

                          Global Fire WEather Database (GFWED)

                          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.

                          Daymet

                          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.

                          GEOS-5

                          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.

                          • GEOS-5 Weather Maps
                            Within the viewer, select the parameter or field of interest, the area of interest, and indicate the forecast time and the forecast lead hour. Selecting "Animate" shows the forecast for the given parameter over the time period indicated. Note that it may take time to load the images to animate. For wind speed near the surface, select 850 as your level (850 hPa is approximately 5,000 ft/1,500 m above sea level).

                          CHIRPS-GEFS

                          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

                          GPCP

                          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:

                          LDAS

                          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:

                          NEX-GDDP-CMIP6

                          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):


                          Reanalysis Data

                          MERRA-2

                          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.


                            Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                             

                            Earth Observation Data by Sensor

                            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.

                            Common Measurements at a Glance

                            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

                             

                            Earth Observation Data by Sensor

                            SRTM

                            Image
                            An ASTER GDEM image of Mt. Raung and the surrounding area.
                            An ASTER GDEM image of Mt. Raung and the surrounding area. Credit: LP DAAC.

                            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.

                            ASTER

                            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.

                            GEDI

                            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:


                              Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

                              Common Measurements at a Glance

                              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

                              Earth Observations by Sensor

                              Image
                              Screenshot of Normalized Difference Vegatation Index of King Fire area of burn.
                              False-color image showing changes in NDVI before (September 19, 2013; left image) and after (November 17, 2014; right image) California's King Fire in September and October, 2014. Green areas indicate healthy vegetation; red areas indicate sparse/burned vegetation. Credit: NASA's ORNL DAAC.

                              MODIS

                              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:

                              • MODIS NDVI
                                • Select a map plot, date range, and region and plot the data; data can be downloaded as GeoTIFF

                              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. 

                              VIIRS

                              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):

                                GEDI

                                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:

                                MISR

                                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:


                                Model Data

                                MODIS

                                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

                                VIIRS LAI Level 4 data are available starting in 2012 through Earthdata Search:


                                Data From the Arctic-Boreal Vulnerability Experiment (ABoVE)

                                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.

                                ABoVE: Burned Area, Depth, and Combustion for Alaska and Canada, 2001-2019

                                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.

                                ABoVE: Ignitions, Burned Area, and Emissions of Fires in AK, YT, and NWT, 2001-2018

                                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.

                                Burned and Unburned Field Site Data, Noatak, Seward, and North Slope, AK, 2016-2018

                                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.


                                  Visit NASA's Disaster Mapping Portal for the latest near real-time and disaster specific products in Geographic Information Systems (GIS) format.

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