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Wildfire Data Pathfinder

According to the Fourth National Climate Assessment, climate change has made its appearance, touting the world with extreme weather conditions, including increased heat waves, rising sea levels, and increasing devastation from wildfires, to name just a few. A combination of ground- and satellite-based data provides a unique view of the globe to better understand the impacts of climate change. These measurements help scientists, researchers, and decision makers prepare for risk and response to events but also in forecasting events and assessing the post-event impacts. NASA, in collaboration with other organizations, has a series of instruments that provide this information for understanding a number of phenomena, including wildfires.

NASA is particularly interested in wildfires because they are looking at the Earth system and how changes to that system can have environmental, societal, and economic impacts. What is causing the changes and what can we do to mitigate impacts?

Applications of Earth Observations Data of Fire

Scientists, researchers, land managers, decision makers, etc. are using wildfire data in numerous ways (to see some of the data in action, check out our Data User Profiles or our Wildfire news). Wildfire data can be used to forecast events. By acquiring data on precipitation, soil moisture, drought severity, topography, land surface temperatures, and vegetation density and extent, land and/or wildlife managers can perform pre-fire mapping to indicate potential areas of risk. Near-real time wildfire data, looking at total area burning, fire radiative power, etc., can be used to assess risk in a given area and develop a more efficient strategy for response. Wildfire data can be used in post-fire mapping, incorporating total burned area, burn severity, and vegetation regrowth. Whatever your mission, NASA has data to meet those needs.

Choose from below the fire application of interest.


Benefits and Limitations of Data

Benefits and Limitations of Data
In determining whether or not to use remotely sensed data for wildfire assessment, it’s important to understand both the benefits but also the limitations of the data.

Benefits of using Wildfire Data

  • Satellite data provides a more regional to global spatial coverage; some of the information is available in near-real time allowing for more efficient disaster response.
  • With satellite data, comparisons can be made using pre- and post-fire imagery, providing information on smoke and ash transport, burn severity, vegetation loss, and so much more.
  • Incorporating satellite data with in-situ data in modeling programs makes for a more robust forecasting system.

Challenges of Using Wildfire Data

  • While the data provides a more global view, for small fires or field level events the spatial resolution is coarse, introducing a higher level of error.
  • Many of these satellites only pass over the same spot every 1-2 days and some every 16+ days.
  • Passive satellites (those that use energy being emitted from Earth for measurements) are not able to penetrate cloud or vegetation cover. This challenge can lead to errors within the size and radiative power of small fires.

Risk and Response - Near Real Time

Risk and Response - Near Real Time

Near Real-Time Data
Aerosols/smoke plumes and transport

Near Real-Time Data

Modisvsviirs

NASA’s Land, Atmosphere Near real-time Capability for EOS (LANCE) provides data to the public within 3 hours of satellite overpass, which allows for almost near-real time (NRT) monitoring and decision making. Specifically for fires, both MODIS (Moderate Resolution Imaging Spectroradiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) provide a quick look at hotspots, fire and thermal anomalies, and the smoke plume movement. There are some differences between the data sets that must be considered in planning. Each MODIS active fire location represents the center of a 1km pixel that is flagged by the algorithm as containing one or more fires within the pixel, whereas VIIRS has an improved spatial resolution of 375 m, which provides a greater response over fires of relatively small areas.The 375 m data also has improved nighttime performance. It is important to note that the NRT products are not quality checked and a predicted geolocation is used.

There are two primary ways of exploring NRT fire data, or Fire Information for Resource Management System (FIRMS) - through an interactive map or by direct download of the data if you know the region in which you are interested. The interactive map provides daily global MODIS and VIIRS fire locations, as well as, burned area. These active fire data are also made available for download once you know your region of interest. The data are downloadable as shapefiles, KML, text, etc.

Select by region of interest? Active Fire Data
or
Explore data on an interactive map? FIRMS Fire Map


For a tutorial on using FIRMS data, see the Earthdata webinar, Discover NASA’s FIRMS.

Aerosols/smoke plumes and transport

CampfireAerosols as a result of the smoke and ash from the fire as well as the plume and its movement through time can also be measured using NASA satellite data. The Worldview tool provides the capability to interactively browse over 800 global, full-resolution satellite imagery layers and then download the underlying data. Many of the imagery layers are updated within three hours of observation, essentially showing the entire Earth as it looks "right now". Using MODIS or VIIRS data, one can follow the smoke plume and its movement through time. Also, one can assess the aerosol optical depth (which can be converted to particulate matter with specific algorithms), carbon monoxide, sulfur dioxide, etc. at the fire location, where and when available. If you would like to then download the data for further analysis, the data download option allows you to access the specific data products in the original format (see the data access tools section).

Types of aerosol data provided in NRT:

  • Aerosol Index (AI) — Aerosols absorb and scatter incoming sunlight, which reduces visibility and increases the optical depth. Satellite-derived AI products are useful for identifying and tracking the long-range transport of smoke from wildfires or biomass burning events. Currently there are two satellite products measuring AI, the Aura Ozone Monitoring Instrument (OMI) and Suomi-NPP’s Ozone Mapping and Profiler Suite (OMPS). AI indicates the presence of ultraviolet (UV)-absorbing particles in the air (aerosols); the higher the AI, the higher the concentration in the atmosphere. For both satellites, the spatial resolution is 2 km and the temporal resolution is daily.
  • Aerosol Optical Depth (AOD) — indicates the level at which particles in the air (aerosols) prevent light from traveling through the atmosphere. From an observer on the ground, an AOD of less than 0.1 is “clean” - characteristic of clear blue sky, bright sun and maximum visibility. As AOD increases to 0.5, 1.0, and greater than 3.0, aerosols become so dense that the sun is obscured.
    • AOD MODIS Data — Aqua and Terra's Moderate Resolution Imaging Spectroradiometer Combined Value-Added Aerosol Optical Depth layer is a value-added layer based on MODIS Level 2 aerosol products. The layer can give a quick, synoptic view of the level of aerosol in the atmosphere.
    • Deep Blue AOD from MODIS — Deep Blue AOD layer is useful for studying aerosol optical depth over land surfaces. This layer is created from the Deep Blue (DB) algorithm.
  • Trace Gases from Fires — in addition, the particulate matter, numerous trace gases are found in the atmosphere during and after a fire event. These trace gases, like Carbon Monoxide and Sulfur Dioxide, are harmful pollutants that can impact public health. These two trace gases are available from a variety of different satellites. For CO, the Atmospheric Infrared Sounder onboard the AQUA satellite provides the best global coverage at 2km resolution and twice daily measurements (day and night). AIRS also provides measurements of SO2. Two other instruments, OMI and OMPS (descriptions above) provide information on SO2 at the lower troposphere, middle troposphere, and upper troposphere/stratosphere layers.
    • AIRS CO Total Column (Day/Night) — indicates the amount of CO in the total vertical column profile of the atmosphere (from Earth’s surface to top-of-atmosphere) and is measured in parts per billion by volume (ppbv).
    • AIRS SO2 — indicates Sulfur Dioxide column amounts in the atmosphere, measured in Dobson Units (DU).
    • OMI/OMPS SO2 — indicates the column density of sulfur dioxide at that layer of the atmosphere and is measured in Dobson Units (DU). OMI data are available from 2005-present and OMPS from 2012-present.

Fire Forecasting

Fire Forecasting
Many factors contribute to a fire, its intensity and its severity. As such, its important to monitor contributing factors in order to predict the formation of a fire and how it will move through the environment. NASA has several data sets for making these predictions.
  • Vegetation Density and Extent — the Normalized Difference Vegetation Index (NDVI) provides a means to assess the vegetation health in a given area. Very low values of NDVI (0.1 and below) correspond to barren areas of rock, sand, or snow. Moderate values represent shrub and grassland (0.2 to 0.3), while high values indicate temperate and tropical rainforests (0.6 to 0.8). Aqua and Terra's Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data can be accessed via the following ways:
    • Science quality, or higher-level “standard” data products can be accessed via the Earthdata Search client; data sets are available as HDF files which can be opened using Panoply or customizable to GeoTIFF.
      NDVI

    • Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, time series, etc. through an online interactive tool, Giovanni. For more information on choosing a type of plot, see Giovanni’s User manual.
      • MODIS NDVI from Giovanni — Select a map plot, date range and region and then plot the data. Data can be downloaded as GeoTIFF.
  • Precipitation — NASA’s Precipitation Measurement Missions provide a continuous long-term record (over 20 years) of precipitation data through the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM). With the follow-on GPM mission, measurements increased in accuracy, improved detection of light rain and snow, and extended the spatial coverage. These products are available individually or have been integrated, TRMM into the TRMM Multi-satellite Precipitation Algorithm (TMPA) and GPM into the Integrated Multi-satellitE Retrievals for GPM (IMERG), with a global constellation of satellites to yield improved spatial/temporal precipitation estimates with a temporal resolution of 30 minutes. IMERG’s multiple runs accommodate different user requirements for latency and accuracy (Early= 4 hours for flash flood events, Late = 12 hours for crop forecasting, and Final = 3 months for research with the incorporation of rain gauge data). In addition, for NRT data, among IMERG and LDAS, the Atmospheric Infrared Sounder (AIRS) instrument provides an estimate of daily precipitation measured in millimeters (mm) using cloud-related parameters of cloud-top pressure, fractional cloud cover, and cloud-layer relative humidity.
    • Science quality, or higher-level “standard” data products can be accessed via the Earthdata Search client; data sets are available as HDF files which can be opened using Panoply or customizable to GeoTIFF.
      • TMPA - Earthdata — rainfall estimate at 3 hours, 1 day or NRT and accumulated rainfall at 3 hours and 1 day. Data are in HDF format and can be opened using panoply. Data are available from 1997.
      • IMERG - Earthdata — Early, Late and Final precipitation data on the half hour or 1 day timeframe. Data are in NetCDF or HDF format and can be opened using Panoply. Data are available from 2014.
    • Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, time series, etc. through an online interactive tool, Giovanni. For more information on choosing a type of plot, see Giovanni’s User manual.
      • TMPA - Giovanni - select a map plot, date range and region, and determine your variable and then plot the data. Data can be downloaded as GeoTIFF.
      • IMERG - Giovanni — select a map plot (you can a time-averaged map, an animation, or seasonal maps), date range and region, and determine your variable and then plot the data. Data can be downloaded as GeoTIFF. Data are only available from 2014-2018.
    • WhichdataNRT Data (unsure about which of the NRT to choose, see diagram at right):
  • Land Surface Temperature — is useful for monitoring changes in weather and climate patterns and used in wildfire risk assessment.
  • Soil Moisture — there are numerous means of accessing informaiton on soil moisture. As mentioned in the benefits and challenges, current ground measurements of soil moisture are sparse and have limited coverage, and so satellite data can help fill in those blanks. However, satellites obviously are not able to get at the detail, or resolution, needed. The preferred measurement should be chosen based upon your needs. NASA's Soil Moisture Active Passive (SMAP) satellite measures the moisture in the top 5cm of the soil globally every 3 days, at a resolution of 10-40km. NASA, in collaboration with other agencies, also have developed models of soil moisutyre content, incorporating satellite information with ground-based data when available. These models are part of the Land Data Assimilation System (LDAS), of which there is a global collection (GLDAS) and a US national collection (NLDAS).
    • SMAP Data from Earthdata — data are in HDF format. They can be downloaded as HDF and opened using panoply or customizable to GeoTIFF.
    • NLDAS (US) Data from Giovanni — select a map plot, date range and region, and determine your variable and then plot the data. Data can be downloaded as GeoTIFF.
    • GLDAS (Global) Data from Giovanni — select a map plot, date range, and determine your variable and then plot the data. Data can be downloaded as GeoTIFF.
  • Topography — the elevation of an area is important prior to a fire event so that fire managers and emergency management professionals can anticipate where areas of risk might be. The Shuttle Radar Topography Mission (SRTM) provides a digital elevation model of all land between 60 degrees north and 56 degrees south, about 80% of all Earth’s landmass.
    • SRTM data from Earthdata — these data were acquired in 2000 and are in HGT format, which can be opened in most Geographic Information Systems (GIS), such as ArcGIS or QGIS. Data are also customizable to GeoTIFF.

Post-Fire Impacts

Post-Fire Impacts
Wildfires have enormous impacts on the surrounding area, including burned area, changes in runoff, landslide potential, etc. In some areas, this is measured through observation-based estimates of post-fire effects. However, remote areas or rugged terrain often impede measurements. Remotely-sensed data provides a means to extend our knowledge in these areas.
  • Vegetation Density and Extent — the Nomalized Difference Vegetation Index (NDVI) provides a means to assess the vegetation health in a given area. Very low values of NDVI (0.1 and below) correspond to barren areas of rock, sand, or snow. Moderate values represent shrub and grassland (0.2 to 0.3), while high values indicate temperate and tropical rainforests (0.6 to 0.8). Aqua and Terra's Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data can be accessed via the following ways:
    • Science quality, or higher-level “standard” data products can be accessed via the Earthdata Search client; data sets are available as HDF files which can be opened using Panoply or customizable to GeoTIFF.
    • Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, time series, etc. through an online interactive tool, Giovanni. For more information on choosing a type of plot, see Giovanni’s User manual.
      • MODIS NDVI from Giovanni — select a map plot, date range and region and then plot the data. Data can be downloaded as GeoTIFF.
  • Precipitation — NASA’s Precipitation Measurement Missions provide a continuous long-term record (over 20 years) of precipitation data through the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM). With the follow-on GPM mission, measurements increased in accuracy, improved detection of light rain and snow, and extended the spatial coverage. These products are available individually or have been integrated, TRMM into the TRMM Multi-satellite Precipitation Algorithm (TMPA) and GPM into the Integrated Multi-satellitE Retrievals for GPM (IMERG), with a global constellation of satellites to yield improved spatial/temporal precipitation estimates with a temporal resolution of 30 minutes. IMERG’s multiple runs accommodate different user requirements for latency and accuracy (Early= 4 hours for flash flood events, Late = 12 hours for crop forecasting, and Final = 3 months for research with the incorporation of rain gauge data). In addition, for NRT data, among IMERG and LDAS, the Atmospheric Infrared Sounder (AIRS) instrument provides an estimate of daily precipitation measured in millimeters (mm) using cloud-related parameters of cloud-top pressure, fractional cloud cover, and cloud-layer relative humidity.
    • Science quality, or higher-level “standard” data products can be accessed via the Earthdata Search client; data sets are available as HDF files which can be opened using Panoply or customizable to GeoTIFF.
      • TMPA - Earthdata — rainfall estimate at 3 hours, 1 day or NRT and accumulated rainfall at 3 hours and 1 day. Data are in HDF format and can be opened using panoply. Data are available from 1997.
      • IMERG - Earthdata — Early, Late and Final precipitation data on the half hour or 1 day timeframe. Data are in NetCDF or HDF format and can be opened using Panoply. Data are available from 2014.
    • Data products can be visualized as a time-averaged map, an animation, seasonal maps, scatter plots, time series, etc. through an online interactive tool, Giovanni. For more information on choosing a type of plot, see Giovanni’s User manual.
      • TMPA - Giovanni - select a map plot, date range and region, and determine your variable and then plot the data. Data can be downloaded as GeoTIFF.
      • IMERG - Giovanni — select a map plot (you can a time-averaged map, an animation, or seasonal maps), date range and region, and determine your variable and then plot the data. Data can be downloaded as GeoTIFF. Data are only available from 2014-2018.
    • NRT Data (unsure about which of the NRT to choose, see diagram at right):
  • Topography — the elevation of an area is important after a fire event occurs so that fire managers and emergency management officials can assess potential areas of increased runoff and landslide potential. The Shuttle Radar Topography Mission (SRTM) provides a digital elevation model of all land between 60 degrees north and 56 degrees south, about 80% of all Earth’s landmass.
    • SRTM data from Earthdata — these data were acquired in 2000 and are in HGT format, which can be opened in most Geographic Information Systems (GIS), such as ArcGIS or QGIS. Data are also customizable to GeoTIFF.

Other Fire-Related Resources

Other Fire-Related Resources
The Global Wildfire Information System is a joint initiative of the Group on Earth Observations and the Copernicus Programs. The Global Wildfire Information System (GWIS) aims at bringing together existing information sources, including NASA’s MODIS and VIIRS data, to provide a comprehensive view and evaluation of fire regimes and fire effects at a global level.
  • GWIS Current Situation Viewer - provides a fire danger forecast as well as a rapid damage assessment, which includes active fires, burnt area, and fire emissions (sulfur dioxide, nitrogen oxides, particulate matter, and so on). The viewer also allows for some basic statistical analysis.

Tools for Data Access

Tools for Data Access
GearHDF and NetCDF files can be viewed in Panoply or customization can be done once the data of interest are selected, either by selecting the gear (see figure to the right) or if downloading multiple files, choose customize product and then select GeoTiff as your output file format. Note that you can change your projection as well as choose only those bands of interest.
Customize


For a Panoply Orientation - https://www.youtube.com/watch?v=WNs5ZdZMhQY&list=PLO2yB4LGNlWoyJ02Z3kNlYNWqD1KfbtVT&index=26&t=0s

For a tutorial on creating plots in Panoply: https://www.youtube.com/watch?v=dTvxE5zcY08&list=PLO2yB4LGNlWoyJ02Z3kNlYNWqD1KfbtVT&index=27&t=0s

Giovanni how-tos: https://www.youtube.com/channel/UCQloC07ADoKnfyJA7eGFhzw

Worldview provides access to visualization of many data sets in NRT, that is 3-hours after acquisition. All of the visualizations for a particular area of interest are accessible via the add layer button. They are categorized by the hazard or disaster, i.e. fires (see below).
Wvhazards
WVDATAWithin Worldview, visualizations of different measurements or dates can be compared using the "Start Comparison" button. A snapshot of the visualization can be downloaded as a PNG, JPG, GeoTIFF or KMZ file. If the original data is needed, the Data tab provides access to the downloadable data sets.

For a tutorial of Worldview, see the Earthdata webinar, Explore the Earth Every Day.

Page Last Updated: May 15, 2019 at 2:14 PM EDT