VNP22Q2 500 m Greenup Onset image for North America, 2014.
View full-size imageThe Suomi National Polar-Orbiting Partnership (Suomi NPP) NASA Visible Infrared Imaging Radiometer Suite (VIIRS) Land Cover Dynamics data product provides global land surface phenology (GLSP) metrics at yearly intervals. The VNP22Q2 data product is derived from time series of the two-band Enhanced Vegetation Index (EVI2) calculated from VIIRS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR). Vegetation phenology metrics at 500 meter spatial resolution are identified for up to two detected growing cycles per year.
Provided in each VNP22Q2 product are 19 Science Dataset (SDS) layers. The product contains six phenological transition dates: onset of greenness increase, onset of greenness maximum, onset of greenness decrease, onset of greenness minimum, dates of mid-greenup, and senescence phases. The product also includes the growing season length. The greenness related metrics consist of EVI2 onset of greenness increase, EVI2 onset of greenness maximum, EVI2 growing season, rate of greenness increase and rate of greenness decrease. The confidence of phenology detection is provided as greenness agreement growing season, proportion of good quality (PGQ) growing season, PGQ onset greenness increase, PGQ onset greenness maximum, PGQ onset greenness decrease, and PGQ onset greenness minimum. The final layer is quality control specifying the overall quality of the product. A low-resolution browse image showing greenup is also available when viewing each VNP22Q2 granule.
Important information is provided in Sections 5 of the User Guide when comparing VNP22Q2 with the MCD12Q2 data product.
Validation at stage 1 has been achieved for VIIRS land cover dynamic product suite. Visit VIIRS Land Product Quality Assessment Product Maturity for information on product maturity status.
Characteristic | Description |
---|---|
Collection | Suomi NPP VIIRS |
DOI | 10.5067/VIIRS/VNP22Q2.001 |
File Size | ~659.52 MB |
Temporal Resolution | Yearly |
Temporal Extent | 2013-01-01 to Present |
Spatial Extent | Global |
Coordinate System | Sinusoidal |
Datum | N/A |
File Format | HDF-EOS5 |
Geographic Dimensions | Global |
Characteristic | Description |
---|---|
Number of Science Dataset (SDS) Layers | 19 |
Columns/Rows | 2400 x 2400 |
Pixel Size | 500 m |
SDS Name | Description | Units | Data Type | Fill Value | No Data Value | Valid Range | Scale Factor |
---|---|---|---|---|---|---|---|
Date_Mid_Greenup_Phase¹ | Date at a mid-greenup phase | Day | 16-bit unsigned integer | 32767 | N/A | 1 to 32766 | N/A |
Date_Mid_Senescence_Phase¹ | Date at a mid-senescence phase | Day | 16-bit unsigned integer | 32767 | N/A | 1 to 32766 | N/A |
EVI2_Growing_Season_Area | Integrated EVI2 during a growing season | EVI2 | 16-bit unsigned integer | 32767 | N/A | 1 to 32766 | 0.01 |
EVI2_Onset_Greenness_Increase | EVI2 value at greenup onset | EVI2 | 16-bit unsigned integer | 32767 | N/A | 1 to 10000 | 0.0001 |
EVI2_Onset_Greenness_Maximum | EVI2 value at maturity onset | EVI2 | 16-bit unsigned integer | 32767 | N/A | 1 to 10000 | 0.0001 |
GLSP_QC | Global Land Surface Phenology Quality Control | N/A | 8-bit unsigned integer | 255 | N/A | 1 to 100 | N/A |
Greenness_Agreement_Growing_Season | EVI2 agreement between modeled values and raw observations | N/A | 8-bit unsigned integer | 255 | N/A | 1 to 100 | N/A |
Growing_Season_Length | Growing Season Length | Number | 16-bit unsigned integer | 32767 | N/A | 1 to 366 | N/A |
Onset_Greenness_Decrease¹ | Date at which canopy greenness begins to decrease | Day | 16-bit unsigned integer | 32767 | N/A | 1 to 32766 | N/A |
Onset_Greenness_Increase¹ | Date of onset of greenness increase | Day | 16-bit unsigned integer | 32767 | N/A | 1 to 32766 | N/A |
Onset_Greenness_Maximum¹ | Date at which canopy greenness approaches its seasonal maximum | Day | 16-bit unsigned integer | 32766 | N/A | 1 to 32766 | N/A |
Onset_Greenness_Minimum¹ | Date at which canopy greenness reaches a minimum | Day | 16-bit unsigned integer | 32766 | N/A | 1 to 32766 | N/A |
PGQ_Growing_Season | Proportion of good quality of VIIRS observations during a vegetation growing season | N/A | 8-bit unsigned integer | 255 | N/A | 1 to 100 | N/A |
PGQ_Onset_Greenness_Decrease | Proportion of good quality around senescence onset | N/A | 8-bit unsigned integer | 255 | N/A | 1 to 100 | N/A |
PGQ_Onset_Greenness_Increase | Proportion of good quality around greenup onset | N/A | 8-bit unsigned integer | 255 | N/A | 1 to 100 | N/A |
PGQ_Onset_Greenness_Maximum | Proportion of good quality around maturity onset | N/A | 8-bit unsigned integer | 255 | N/A | 1 to 100 | N/A |
PGQ_Onset_Greenness_Minimum | Proportion of good quality around dormancy onset | N/A | 8-bit unsigned integer | 255 | N/A | 1 to 100 | N/A |
Rate_Greenness_Decrease | Rates of change in EVI2 values during a senescence phase | EVI2/Day | 16-bit unsigned integer | 32767 | N/A | 1 to 32766 | 0.0001 |
Rate_Greenness_Increase | Rates of change in EVI2 values during a greenup phase | EVI2/Day | 16-bit unsigned integer | 32767 | N/A | 1 to 32766 | 0.0001 |
¹Please use the following calculation to scale these data: Scaled Data = Unscaled data – (given year-2000)*366
Detailed information on quality for the VNP22 products can be found in Section 2 of the User Guide.
The Quality Control (QC) 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.
In addition to data access and transformation processes, AppEEARS also has the capability to unpack and interpret the quality layers.
For additional information on product quality, refer to the VIIRS Land Product Quality website.
For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.