The VNP43IA2 BRDF and Albedo Quality product over southeastern Australia from October 29, 2018.View full-size image
The NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Bidirectional Reflectance Distribution Function (BRDF) and Albedo Quality (VNP43IA2) Version 1 product provides BRDF and Albedo quality at 500 meter (m) resolution. The VNP43IA2 product is produced daily using 16 days of VIIRS data and is weighted temporally to the ninth day, which is reflected in the file name. The VNP43IA2 product provides information regarding band quality and days of valid observation within a 16-day period for the VIIRS imagery bands. The VNP43 data products are designed to promote the continuity of NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF/Albedo data product suite.
The VNP43 algorithm uses the RossThick/Li-Sparse-Reciprocal (RTLSR) semi-empirical kernel-driven BRDF model, with the three kernel weights from VNP43IA1 to reconstruct surface anisotropic effects, correcting the directional reflectance to a common view geometry (VNP43IA4), while also computing integrated black-sky albedo (BSA) at local solar noon and white-sky albedo (WSA) (VNP43IA3). Researchers can use the BRDF model parameters with a simple polynomial, to obtain black-sky albedo at any solar illumination angle. Likewise, both the BSA and WSA Science Dataset (SDS) layers can be used with a simple polynomial, to manually estimate instantaneous actual albedo (blue-sky albedo). Additional details regarding the methodology are available in the Algorithm Theoretical Basis Document (ATBD).
The VNP43IA2 data product provides a total of 11 SDS layers including: BRDF/Albedo band quality (inversion information) and days of valid observation within a 16-day period for VIIRS imagery bands I1, I2, and I3, as well as land water type class flag, snow BRDF albedo class flag, local solar noon, albedo uncertainty and the platform name.
|Collection||Suomi NPP VIIRS|
|File Size||~11 MB|
|Temporal Extent||2012-01-17 to Present|
|Geographic Dimensions||1200 km x 1200 km|
|Number of Science Dataset (SDS) Layers||11|
|Columns/Rows||2400 x 2400|
|Pixel Size||500 m|
|SDS Name||Description||Units||Data Type||Fill Value||No Data Value||Valid Range||Scale Factor|
|BRDF_Albedo_Band_Quality_I1||BRDF inversion information||N/A||8-bit unsigned integer||255||N/A||0 to 3||N/A|
|BRDF_Albedo_Band_Quality_I2||BRDF inversion information||N/A||8-bit unsigned integer||255||N/A||0 to 3||N/A|
|BRDF_Albedo_Band_Quality_I3||BRDF inversion information||N/A||8-bit unsigned integer||255||N/A||0 to 3||N/A|
|BRDF_Albedo_LandWaterType||Land/Water type||Class Flag||8-bit unsigned integer||255||N/A||0 to 254||N/A|
|BRDF_Albedo_LocalSolarNoon||Solar zenith angle at local solar noon||Degree||8-bit unsigned integer||255||N/A||0 to 90||N/A|
|BRDF_Albedo_Platform||Platform name||N/A||8-bit unsigned integer||255||N/A||0 to 254||N/A|
|BRDF_Albedo_Uncertainty||Weight of Determination (WoD) of WSA||N/A||16-bit unsigned integer||32767||N/A||0 to 32766||N/A|
|BRDF_Albedo_ValidObs_I1||Days of valid observation within 16-day period for band I1||N/A||16-bit unsigned integer||0||N/A||1 to 65535||N/A|
|BRDF_Albedo_ValidObs_I2||Days of valid observation within 16-day period for band I2||N/A||16-bit unsigned integer||0||N/A||1 to 65535||N/A|
|BRDF_Albedo_ValidObs_I3||Days of valid observation within 16-day period for band I3||N/A||16-bit unsigned integer||0||N/A||1 to 65535||N/A|
|Snow_BRDF_Albedo||Snow flag||Class Flag||8-bit unsigned integer||255||N/A||0 to 1||N/A|
|1||Land (Nothing else but land)|
|2||Ocean and lake shorelines|
|3||Shallow inland water|
|5||Deep inland water|
|6||Moderate or continental ocean|
|0||snow-free albedo retrieved|
|1||snow albedo retrieved|
|0||best quality, full inversion (WoDs, RMSE majority good)|
|1||good quality, full inversion|
|2||Magnitude inversion (numobs ≥ 7)|
|3||Magnitude inversion (numobs ≥ 2 & 7)|
Product Quality information can be found in the ATBD in Table 5. Product accuracy/uncertainty information can be found in Section 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.
In addition to data access and transformation processes, AppEEARS also has the capability to unpack and interpret the quality layers.
The abnormally high activation of the high aerosol flag in the Collection 1 (C1) VNP09 product, has impacted downstream products. The VNP43 BRDF/Albedo/NBAR product is affected by reducing the number of otherwise acceptable observations used as input to characterize surface anisotropy. This effect (most obvious over arid bright surfaces), results in a reduced number of high quality full BRDF model inversions. Therefore, users should be aware that bright arid surfaces (normally associated with high quality BRDF/Albedo/NBAR retrievals) are likely to be somewhat represented by lower quality results in C1. VNP09 has been corrected for Collection 2 (C2). Therefore, users should avoid substantive use of C1 VNP43 over arid regions (and wait for C2 products). In any event, users are always strongly encouraged to download and use the extensive QA data provided in VNP43[I-M]A2, in addition to the briefer mandatory QA provided as part of the VNP43[I-M]A1, 3 and 4 products.
For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.