VNP13A2 v002

VIIRS/NPP Vegetation Indices 16-Day L3 Global 1 km SIN Grid


PI: Eric Vermote

Description

The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Vegetation Indices (VNP13A2) Version 2 data product provides vegetation indices by a process of selecting the best available pixel over a 16-day acquisition period at 1 kilometer (km) resolution. The VNP13 data products are designed after the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua Vegetation Indices product suite to promote the continuity of the Earth Observation System (EOS) mission.

The VNP13 algorithm process produces three vegetation indices: The Normalized Difference Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), and the Enhanced Vegetation Index-2 (EVI2). NDVI is one of the longest continual remotely sensed time series observations, using both the red and near-infrared (NIR) bands. EVI is a slightly different vegetation index that is more sensitive to canopy cover, while NDVI is more sensitive to chlorophyll. EVI2 is a reformation of the standard 3-band EVI, using the red band and NIR band. This reformation addresses arising issues when comparing VIIRS EVI to other EVI models that do not include a blue band. EVI2 will eventually become the standard EVI.

Along with the three Vegetation Indices layers, this product also includes layers for NIR reflectance; three shortwave infrared (SWIR) reflectance; red, blue, and green reflectance; composite day of year; pixel reliability; relative azimuth, view, and sun angles, and a quality layer. Two low resolution browse images are also available for each VNP13A2 product: EVI and NDVI.

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Characteristics

Improvements/Changes from Previous Versions

  • Improved calibration algorithm and coefficients for entire Suomi NPP mission.
  • Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.
  • Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo.
  • Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data.
  • Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.
  • Modified QA VI Usefulness bits to ignore BRDF flag.
  • Implemented VI specific land/water mask.

More details can be found in this VIIRS Land V2 Changes document.

Product Maturity

Validation at stage 1 has been achieved for the VIIRS Vegetation Index (VI) product suite. Visit VIIRS Land Product Quality Assessment Product Maturity for information on product maturity status.

Collection and Granule

Collection

Characteristic Description
CollectionSuomi NPP VIIRS
DOI10.5067/VIIRS/VNP13A2.002
File Size~13.5 MB
Temporal ResolutionMonthly
Temporal Extent2012-01-19 to Present
Spatial ExtentGlobal
Coordinate SystemSinusoidal
DatumN/A
File FormatHDF-EOS5
Geographic Dimensions1200 km x 1200 km

Granule

Characteristic Description
Number of Science Dataset (SDS) Layers16
Columns/Rows1200 x 1200
Pixel Size1000 m

Layers / Variables

SDS Name Description Units Data Type Fill Value No Data Value Valid Range Scale Factor
1 km 16 days EVI 1 km 16 days EVI EVI 16-bit signed integer -15000, -13000 N/A -10000 to 10000 10000
1 km 16 days EVI2 1 km 16 days EVI2 EVI2 16-bit signed integer -15000, -13000 N/A -10000 to 10000 10000
1 km 16 days NDVI 1 km 16 days NDVI NDVI 16-bit signed integer -15000, -13000 N/A -10000 to 10000 10000
1 km 16 days NIR reflectance 1 km 16 days NIR reflectance (846–885 nm) N/A 16-bit signed integer -1000 N/A 0 to 10000 10000
1 km 16 days SWIR1 reflectance 1 km 16 days SWIR1 reflectance (1230–1250 nm) N/A 16-bit signed integer -1000 N/A 0 to 10000 10000
1 km 16 days SWIR2 reflectance 1 km 16 days SWIR2 reflectance (1580–1640 nm) N/A 16-bit signed integer -1000 N/A 0 to 10000 10000
1 km 16 days SWIR3 reflectance 1 km 16 days SWIR3 reflectance (2225–2275 nm) N/A 16-bit signed integer -1000 N/A 0 to 10000 10000
1 km 16 days VI Quality 1 km 16 days VI Quality Bit Field 16-bit unsigned integer 65535 N/A 0 to 65534 N/A
1 km 16 days blue reflectance 1 km 16 days blue reflectance (478–498 nm) N/A 16-bit signed integer -1000 N/A 0 to 10000 10000
1 km 16 days composite day of the year 1 km 16 days composite day of the year Julian day 16-bit signed integer -1 N/A 1 to 366 N/A
1 km 16 days green reflectance 1 km 16 days green reflectance (545–565 nm) N/A 16-bit signed integer -1000 N/A 0 to 10000 10000
1 km 16 days pixel reliability 1 km 16 days pixel reliability Rank 8-bit signed integer -4, -1 N/A 0 to 11 N/A
1 km 16 days red reflectance 1 km 16 days red reflectance (600–680 nm) N/A 16-bit signed integer -1000 N/A 0 to 10000 10000
1 km 16 days relative azimuth angle 1 km 16 days relative azimuth angle Degree 16-bit signed integer -20000 N/A -18000 to 18000 100
1 km 16 days sun zenith angle 1 km 16 days sun zenith angle Degree 16-bit signed integer -20000 N/A 0 to 18000 100
1 km 16 days view zenith angle 1 km 16 days view zenith angle Degree 16-bit signed integer -20000 N/A 0 to 18000 100

All scale factors are to be divided.

Fill Values for the Vegetation Index Layers

Fill Value Description
-15000 over ocean/water
-13000 over land

Fill Values for the Pixel Reliability Layer

Fill Value Description
-4 over ocean/water
-1 over land

Rankings for the Pixel Reliability Layer

Rank Description
0 Excellent
1 Good
2 Acceptable
3 Marginal
4 Pass
5 Questionable
6 Poor
7 Cloud Shadow
8 Snow/Ice
9 Cloud
10 Estimated
11 LTAVG

Product Quality

Product Quality information can be found in the combined User Guide and Algorithm Theoretical Basis Document (ATBD). For the “500 m 16 days pixel reliability” SDS Layer, a rank quality table for each pixel can be found in Table 5. For the “500 m 16 days VI Quality” SDS Layer, for use with all VI’s, a bit field Quality Assurance table can be found in Table 13, with additional information available in Table 14. Accuracy Precision and Uncertainty information is available in Section 12.1.4.

The Quality Assessment (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 quality layer.

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 additional information on product quality, refer to the VIIRS Land Product Quality website.

Known Issues

For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website and the User Guide and ATBD.


About the image

NDVI from the VNP13A2 product over Brazil during July 2023.

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Documentation

User Guide and Algorithm Theoretical Basis Document (ATBD)
File Specification

Using the Data

Access Data

Citation

DOI: 10.5067/VIIRS/VNP13A2.002