VIIRS/NPP VNP13A1: Global Vegetation Indices at 500m

VNP13A1 Version 2 provides three vegetation indices—NDVI, EVI, and EVI2—derived from 16-day composite periods at a 500-meter resolution. The dataset includes 16 variables, such as reflectance bands, sun-sensor geometry, and quality assurance layers, to support continuity with the MODIS mission. It is produced by the NASA/NOAA Suomi NPP satellite to monitor global vegetation dynamics.

Use Cases

• Monitoring crop health and agricultural productivity based on NDVI and EVI time series.
• Tracking seasonal vegetation phenology (e.g., greening and senescence) using 16-day composite data.
• Assessing canopy cover and chlorophyll content by comparing EVI and NDVI sensitivities.
• Validating climate or ecosystem models with global, 500m-resolution surface reflectance data.
• Continuity analysis for long-term Earth observation by comparing VIIRS indices with legacy MODIS products.

Strengths

• Provides a long-term, continuous time series of vegetation indices, with NDVI described as one of the longest continual remotely sensed observations.
• Includes 16 specific variables, such as three vegetation indices, multiple reflectance bands, and quality layers, offering detailed analytical dimensions.
• Designed for continuity with the established MODIS Terra and Aqua Vegetation Indices product suite.
• Has a documented spatial resolution of 500 meters and a temporal compositing period of 16 days.

Limitations

• Lacks coverage for two specific tiles (h33v07 and h18v14) over water due to missing critical inputs.
• Metadata for row count, file size, and specific column names is unavailable across all sources.
• The license is ambiguously listed as 'other-license-specified' without explicit terms.

Provenance

Source

NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) satellite, Visible Infrared Imaging Radiometer Suite (VIIRS) sensor.

Collection Method

Satellite remote sensing, with pixels selected from a 16-day acquisition period.

Freshness

2026-04-09 21:11:26.691775

Geography

Global, using a sinusoidal grid projection.