• Fire severity - MODIS

    Cover of Fire Severity product

    Fire severity describes the immediate impact of fire on vegetation. The MODIS Fire severity product provides two classes – non-severe and severe. Non-severe fires only impacted the understorey while severe fires have impacted the tree canopy as well.

    • KEYWORDS:
      MODIS, fire, burnt area, severity
    • DATA LICENCE
      & ACCESS RIGHTS:
      CC-BY 4.0
    • SPATIAL COVERAGE
      & RESOLUTION:
      0.0025 deg (250 m) resolution, North Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      1 month composite; 2002 to ongoing
    • PRODUCTION STATUS:
      Updated quarterly
  • Annual fire scars - Landsat, Qld

    Statewide annual composite of fire scars (burnt area) derived from all available Landsat images in each year. This product may assist the development of appropriate fire management practices and benefit a range of conservation and resource management objectives.

    • KEYWORDS:
      Landsat, fire, burnt area
    • DATA LICENCE
      & ACCESS RIGHTS:
      CC-BY 3.0
    • SPATIAL COVERAGE
      & RESOLUTION:
      30 m resolution; Queensland
    • TEMPORAL COVERAGE & RESOLUTION:
      1 year; 1987 to 2015
    • PRODUCTION STATUS:
      Updated yearly
  • Grassland curing - MODIS

    Grassland curing is the dead fraction of grassland, expressed as a percentage, strictly by dried weight. Data is provided for five alternative algorithms: four developed by the Bushfire CRC Project A1.4 on grassland curing (methods A, B, C, D), and one developed by the Victorian Country Fire Authority (MapVictoria).

    • KEYWORDS:
      MODIS, Bushfire CRC
    • DATA LICENCE
      & ACCESS RIGHTS:
      BoM data licence
    • SPATIAL COVERAGE
      & RESOLUTION:
      500 m resolution; Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      8 day; 2000 to ongoing
    • PRODUCTION STATUS:
      Updated weekly
  • Active-fire based burned area - MODIS, MCD64A1(v5.1) mosaic

    Estimates the approximate date of burning and creates a map of the spatial extent of recent fires. The algorithm identifies rapid changes in the daily surface reflectance dynamics.

    • KEYWORDS:
      MODIS, LPDAAC, fire, burned area
    • DATA LICENCE
      & ACCESS RIGHTS:
      CC-BY 3.0
    • SPATIAL COVERAGE
      & RESOLUTION:
      500 m resolution; Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      1 month composite; 2000 to ongoing
    • PRODUCTION STATUS:
      Updated as available from University of Maryland
  • Thermal anomalies (fire hotspots) - MODIS, MOD15A2(c5) mosaic

    Locations of fire based on absolute detection of a fire (when the fire strength is sufficient to detect), and on detection relative to its background (to account for variability of the surface temperature and reflection by sunlight).

    • KEYWORDS:
      MODIS, LPDAAC, fire, hotspots
    • DATA LICENCE
      & ACCESS RIGHTS:
      CC-BY 3.0
    • SPATIAL COVERAGE
      & RESOLUTION:
      1000m resolution; Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      8 day composite, 2000 to ongoing
    • PRODUCTION STATUS:
      Updated as available from USGS
  • Fire frequency - AVHRR

    Fire Frequency provides the average number of fires affecting an area in a given time period. It is derived from the whole time series of AVHRR burnt area maps.

    • KEYWORDS:
      AVHRR, fire, burned area
    • DATA LICENCE
      & ACCESS RIGHTS:
      CC-BY 3.0
    • SPATIAL COVERAGE
      & RESOLUTION:
      0.01 deg (1 km) resolution; Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      15 year composite; 1997 to 2011
    • PRODUCTION STATUS:
      Updated every few years
  • Sub-pixel fire patchiness (fraction pixel burnt) - MODIS

    An estimate of the fraction of a pixel that has been burnt. Derived from spectral unmixing of daily MODIS observations.

    • KEYWORDS:
      MODIS, fire, burned area
    • DATA LICENCE
      & ACCESS RIGHTS:
      Contact auscover at maitec.com.au for data access
    • SPATIAL COVERAGE
      & RESOLUTION:
      0.0025 deg (250 m) resolution; Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      1 month composite; 2002 to ongoing
    • PRODUCTION STATUS:
      Updated monthly
  • Active-fire based burned area - MODIS, MCD64A1(v5.1) mosaic

    Estimates the approximate date of burning and creates a map of the spatial extent of recent fires. The combined use of active-fire and reflectance data enables the algorithm to adapt regionally over a wide range of pre- and post-burn conditions and across multiple ecosystems.

    • KEYWORDS:
      MODIS, fire, burned area
    • DATA LICENCE
      & ACCESS RIGHTS:
      CC-BY 3.0
    • SPATIAL COVERAGE
      & RESOLUTION:
      500 m resolution; Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      1 month composite; 2000 to ongoing
    • PRODUCTION STATUS:
      Updated as available from University of Maryland
  • Near real-time burnt area - MODIS

    Locations of areas affected by fire in near real-time, usually available within 2h of the satellite overpass.

    • KEYWORDS:
      MODIS, fire, burned area
    • DATA LICENCE
      & ACCESS RIGHTS:
      Contact auscover at maitec.com.au for data access
    • SPATIAL COVERAGE
      & RESOLUTION:
      0.0025 deg (250 m) resolution; Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      1 day as per satellite overpass; last 60 day from present
    • PRODUCTION STATUS:
      Updated Daily
  • Burnt area and approximate day of burn - MODIS

    Locations of areas affected by fire including the approximate day of burning. The MODIS time series is investigated for sudden changes in reflectance, persistent over multiple days.

    • KEYWORDS:
      MODIS, fire, burned area
    • DATA LICENCE
      & ACCESS RIGHTS:
      CC-BY 3.0
    • SPATIAL COVERAGE
      & RESOLUTION:
      0.0025 deg (250 m) resolution; Australia
    • TEMPORAL COVERAGE & RESOLUTION:
      1 month composite; 2000 to ongoing
    • PRODUCTION STATUS:
      Updated monthly

Download our ‘Good Practice Guidelines’

TERN AusCover supports a nationally consistent approach to the calibration, validation, and delivery of earth observation data products. To ensure that earth observation data is useful to a wide range of users, the collection and delivery of this data needs to be accurate, precise, and use reproducible methods. To support the earth observation community in achieving a high quality and consistent approach nationwide, we’ve developed our ‘Good Practice Guidelines’ that provide advice on calibrating and validating earth observation data.
The Guidelines are provided as a free and accessible tool to anyone working in earth observation. They are also intended to be a dynamic resource that will be updated over time as new knowledge and best-practice processes emerge. Please contact us if you have feedback or questions.
The Guidelines draw upon the knowledge and experience of our national expert network, and also internationally agreed protocols and standards. We are grateful to the external and international reviewers who refined the Guidelines prior to their release.

Download the Guidelines here

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