Terra MODIS gross primary productivity (GPP) data from the MOD17A2HGF product over Northern Argentina from January 1 - 8, 2003.View full-size image
The MOD17A2HGF Version 6 Gross Primary Productivity (GPP) product is a cumulative 8-day composite of values with 500 meter (m) pixel size based on the radiation use efficiency concept that can be potentially used as inputs to data models to calculate terrestrial energy, carbon, water cycle processes, and biogeochemistry of vegetation. The data product includes information about GPP and Net Photosynthesis (PSN). The PSN band values are the GPP less the Maintenance Respiration (MR). The data product also contains a PSN Quality Control (QC) layer. The quality layer contains quality information for both the GPP and the PSN.
The MOD17A2HGF will be generated at the end of each year when the entire yearly 8-day MOD15A2H is available. Hence, the gap-filled MOD17A2HGF is the improved MOD17, which has cleaned the poor-quality inputs from 8-day Leaf Area Index and Fraction of Photosynthetically Active Radiation (FPAR/LAI) based on the Quality Control (QC) label for every pixel. If any LAI/FPAR pixel did not meet the quality screening criteria, its value is determined through linear interpolation. However, users cannot get MOD17A2HGF in near-real time because it will be generated only at the end of a given year.
Validation at stage 3 has been achieved for the MODIS Gross and Net Primary Productivity data products. Further details regarding MODIS land product validation for the MOD17 data products are available from the MODIS Land Team Validation site.
|File Size||3.938 MB|
|Temporal Extent||2000-01-01 to Present|
|Geographic Dimensions||1200 km x 1200 km|
|Number of Science Dataset (SDS) Layers||3|
|Columns/Rows||2400 x 2400|
|Pixel Size||500 m|
|SDS Name||Description||Units||Data Type||Fill Value||No Data Value||Valid Range||Scale Factor|
|Gpp_500m||Gross Primary Productivity||kgC/m²/8day||16-bit signed integer||32761 to 32767||N/A||0 to 30000||0.0001|
|PsnNet_500m||Net Photosynthesis||kgC/m²/8day||16-bit signed integer||32761 to 32767||N/A||-30000 to 30000||0.0001|
|Psn_QC_500m||Quality control Indicators||Bit Field||8-bit unsigned integer||255||N/A||0 to 254||N/A|
|32761||Land cover assigned as "unclassified" or not able to determine|
|32762||Land cover assigned as urban/built-up|
|32763||Land cover assigned as "permanent" wetlands/inundated marshland|
|32764||Land cover assigned as perennial snow, ice|
|32765||Land cover assigned as barren, sparse veg (rock, tundra, desert)|
|32766||Land cover assigned as perennial salt or inland fresh water|
For the year-end gap-filled MOD17A2HGF, users may ignore the QC data layer because cloud-contaminated LAI/FPAR gaps have been temporally filled prior to calculation.
Mappings for the Psn_QC_500m layer and an explanation of how to interpret this information are provided under Section 4.1 in the User Guide.
The quality 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 this layer.
Additional information on the Collection 5.5 improved 1 km MOD17 product by the Numerical Terradynamic Simulation Group (NTSC) at the University of Montana and a comparison with the MOD17HGF products are provided in MOD17HGF_vs_NTSG.pdf.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.
Operational and uncertainty issues are provided under Section 2 in the User Guide. Please refer to the MODIS Land Quality Assessment website for complete information about MOD17A2HGF known issues..