Global VIIRS BRDF and Albedo Quality Data at 1 km Resolution

Global daily land surface data provides Bidirectional Reflectance Distribution Function (BRDF) and Albedo quality metrics at a 1 km resolution. NASA produces this product using 16-day rolling windows of observations from the VIIRS/NPP satellite, applying the RossThick/Li-Sparse-Reciprocal kernel-driven model. The dataset contains 23 Science Dataset layers for moderate resolution bands, including quality flags, observation days, and land cover classifications.

Use Cases

• Modeling surface anisotropic effects using the three kernel weights from the RTLSR BRDF model.
• Correcting directional reflectance to a common view geometry for consistent cross-sensor comparisons.
• Estimating black-sky albedo at local solar noon or any solar illumination angle using provided model parameters.
• Classifying land and water types or snow conditions using the integrated land water type and snow BRDF albedo class flags.
• Analyzing temporal trends in surface albedo using the daily produced data with a 16-day observation window.

Strengths

• Provides 23 distinct Science Dataset layers for detailed analysis of multiple VIIRS spectral bands.
• Uses a documented, semi-empirical BRDF model (RTLSR) with methodology detailed in an Algorithm Theoretical Basis Document.
• Offers daily production with a 16-day data window, balancing recency with observational stability.

Limitations

• Specific row counts, file sizes, and column names are not provided across any platform.
• License information is inconsistently reported as 'other-license-specified' on Data.gov but is null on NASA Earthdata.

Provenance

Source

National Aeronautics and Space Administration (NASA)

Collection Method

Produced daily from 16-day rolling windows of VIIRS/NPP satellite observations using the VNP43 algorithm.

Time Range

Daily production; temporal coverage is not explicitly specified but implied to be ongoing.

Freshness

2026-03-12 20:06:32.239547

Geography

Global coverage on a 1 km Sinusoidal (SIN) grid.