MOD17A2H v006

MODIS/Terra Gross Primary Productivity 8-Day L4 Global 500 m SIN Grid


PI: Steve Running

The MOD17A2H Version 6 data product was decommissioned on July 31, 2023. Users are encouraged to use the MOD17A2H Version 6.1 data product.

Description

The MOD17A2H 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.

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Characteristics

Improvements/Changes from Previous Versions

  • The product uses updated Biome Property look-up tables (BPLUT) and an updated version of the daily Global Modeling and Assimilation Office (GMAO) meteorological data.
  • The products are now generated at the native resolution of 500 m using the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index(LAI)/Fraction of Photosynthetically Active Radiation (FPAR) (MOD15A2H) 8-day composite at 500 m resolution.

Product Maturity

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.

Collection and Granule

Collection

Characteristic Description
CollectionTerra MODIS
DOI10.5067/MODIS/MOD17A2H.006
File Size~3.938 MB
Temporal ResolutionMulti-Day
Temporal Extent2000-02-18 to 2023-02-17
Spatial ExtentGlobal
Coordinate SystemSinusoidal
DatumN/A
File FormatHDF-EOS
Geographic Dimensions1200 km x 1200 km

Granule

Characteristic Description
Number of Science Dataset (SDS) Layers3
Columns/Rows2400 x 2400
Pixel Size500 m

Layers / Variables

SDS Name Description Units Data Type Fill Value No Data Value Valid Range Scale Factor
Gpp_500m Gross Primary Productivity kg C/m² 16-bit signed integer 32761 to 32767 N/A 0 to 30000 0.0001
PsnNet_500m Net Photosynthesis kg C/m² 16-bit signed integer 32761 to 32767 N/A -30000 to 30000 0.0001
Psn_QC_500m Quality control indicators N/A 8-bit unsigned integer 255 N/A 0 to 254 N/A

Non-Terrestrial Fill Value Classes

Value Description
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
32767 Fill Value

Product Quality

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.

The bit flags for the Psn_QC_500m Quality layer are provided in the MOD17A2H File Specification.

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.

Known Issues

For complete information about the MOD17A2H known issues refer to the MODIS Land Quality Assessment website.


About the image

Terra MODIS gross primary productivity (GPP) data from the MOD17A2H product over central South America on August 29 - September 5, 2018.

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Documentation

User Guide
Algorithm Theoretical Basis Document (ATBD)
File Specification

Using the Data

Access Data

Citation

DOI: 10.5067/MODIS/MOD17A2H.006

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