Terra MODIS surface reflectance band 1-2-1 data from the MOD09Q1 product over the western United States, Nov ember 24 - December 1, 2020.View full-size image
The MOD09Q1 Version 6.1 product provides an estimate of the surface spectral reflectance of Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Bands 1 and 2, corrected for atmospheric conditions such as gasses, aerosols, and Rayleigh scattering. Provided along with the 250 meter (m) surface reflectance bands are two quality layers. For each pixel, a value is selected from all the acquisitions within the 8-day composite period. The criteria for the pixel choice include cloud and solar zenith. When several acquisitions meet the criteria the pixel with the minimum channel 3 (blue) value is used.
|File Size||56 MB|
|Temporal Extent||2000-02-18 to Present|
|Geographic Dimensions||1200 km x 1200 km|
|Number of Science Dataset (SDS) Layers||4|
|Columns/Rows||4800 x 4800|
|Pixel Size||250 m|
|SDS Name||Description||Units||Data Type||Fill Value||No Data Value||Valid Range||Scale Factor|
|sur_refl_b01||Surface Reflectance Band 1||N/A||16-bit signed integer||-28672||N/A||-100 to 16000||0.0001|
|sur_refl_b02||Surface Reflectance Band 2||N/A||16-bit signed integer||-28672||N/A||-100 to 16000||0.0001|
|sur_refl_state_250m||Surface Reflectance 250m State flags||Bit Field||16-bit unsigned integer||65535||N/A||0 to 57343||N/A|
|sur_refl_qc_250m||Surface Reflectance 250m Band Quality Control flags||Bit Field||16-bit unsigned integer||65535||N/A||0 to 32767||N/A|
The sur_refl_state_250m and sur_refl_qc_250m layers are 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 QC layers.
The QA bit flags for the sur_refl_state_250m and sur_refl_qc_250m layers are provided in the User Guide in Tables 13 and 9 respectively.
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.
For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.