Combined MODIS burn date data from the MCD64A1 product over Australia, June 2018.View full-size image
The Terra and Aqua combined MCD64A1 Version 6 Burned Area data product is a monthly, global gridded 500 meter (m) product containing per-pixel burned-area and quality information. The MCD64A1 burned-area mapping approach employs 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) Surface Reflectance imagery coupled with 1 kilometer (km) MODIS active fire observations. The algorithm uses a burn sensitive Vegetation Index (VI) to create dynamic thresholds that are applied to the composite data. The VI is derived from MODIS shortwave infrared atmospherically corrected surface reflectance bands 5 and 7 with a measure of temporal texture. The algorithm identifies the date of burn for the 500 m grid cells within each individual MODIS tile. The date is encoded in a single data layer as the ordinal day of the calendar year on which the burn occurred with values assigned to unburned land pixels and additional special values reserved for missing data and water grid cells.
The data layers provided in the MCD64A1 product include Burn Date, Burn Data Uncertainty, Quality Assurance, along with First Day and Last Day of reliable change detection of the year.
|File Size||~2.08 MB|
|Temporal Extent||2000-11-01 to Present|
|Geographic Dimensions||1200 km x 1200 km|
|Number of Science Dataset (SDS) Layers||5|
|Columns/Rows||2400 x 2400|
|Pixel Size||500 m|
|SDS Name||Description||Units||Data Type||Fill Value||No Data Value||Valid Range||Scale Factor|
|Burn Date||Burn day of year||Day||16-bit signed integer||-2 to 0||N/A||1 to 366||N/A|
|Burn Date Uncertainty||Estimated uncertainty in burn day||Day||8-bit unsigned integer||0||N/A||0 to 100||N/A|
|QA||Quality Assurance Indicators||Bit Field||8-bit unsigned integer||N/A||N/A||0 to 255||N/A|
|First Day||First day of the year of reliable change detection||Day||16-bit signed integer||-2, -1||N/A||1 to 366||N/A|
|Last Day||Last day of the year of reliable change detection||Day||16-bit signed integer||-2, -1||N/A||1 to 366||N/A|
For more information on the Quality layer and to view the bitmap, refer to page 9, Section 3.1.2, of the Burned Area User Guide.
Quality assurance information should be considered when determining the usability of data for a particular science application. The ArcGIS MODIS-VIIRS Python Toolbox contains tools capable of decoding quality data layers while producing thematic quality raster files for each quality attribute.
In addition to data access and transformation processes, AppEEARS also has the capability to unpack and interpret the quality layers.
The QA layer is stored in an efficient bit-encoded manner. The unpack_sds_bits executable from the LDOPE Tools is available to the user community to help parse and interpret the QA layer.