MYD11C2 v006

• Removed cloud-contaminated LSTs from Level 2 and Level 3 LST products.
• Updated the coefficient look-up table (LUT) for the split-window algorithm with comprehensive regression analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) simulation data in bands 31 and 32 over wide ranges of surface and atmospheric conditions, especially extending the upper boundary for (LST – Ts-air) in arid and semi-arid regions. Increased the overlap between various sub-ranges to reduce the sensitivity of the algorithm to uncertainties in the input data (i.e., column water vapor and air surface temperature from MYD07).
• Made minor adjustments in the classification-based surface emissivity values, especially for bare soil and rocks land cover types.
• Tuned the day/night algorithm by adjusting weights to improve performance in desert regions where the incorporated split-window algorithm may not work well.
• Generated new gridded LST&E products with a 6 km spatial resolution for 8-day (MYD11B2) and monthly (MYD11B3) intervals in response to user community requests.

Validation at stage 2 has been achieved for all MODIS Land Surface Temperature and Emissivity products. Further details regarding MODIS land product validation for the MYD11 data products are available from the MODIS Land Team Validation site.

The Quality Ccontrol (QC) 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 QC layers are provided in the User Guide in Table 15.

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.

For complete information about the MYD11C2 known issues please refer to the MODIS Land Quality Assessment website.