Annual Vegetative Lifeform Cover for CONUS from Landsat and LiDAR

1984 to 2018 annual estimates of percent ground cover for tree, shrub, herb, and non-vegetation lifeforms across the conterminous United States. NASA produced these data using quantile regression forest models trained on Landsat surface reflectance and 165 airborne LiDAR datasets from G-LiHT and NEON AOP. The results are tiled into 425 units following the CONUS Landsat ARD grid.

Use Cases

• Analyzing trends in forest cover using the annual 'tree' percent cover estimates from 1984-2018.
• Mapping shrubland expansion or contraction with the 'shrub' lifeform class data.
• Assessing grassland ('herb') cover dynamics and its relationship to climate or land use.
• Identifying areas of non-vegetation ('other' class) change over the 35-year time series.
• Validating ecosystem models with spatially explicit lifeform cover and uncertainty layers.

Strengths

• Covers a 35-year time series (1984-2018) for longitudinal ecological analysis.
• Integrates 165 high-resolution LiDAR datasets from NASA G-LiHT and NSF NEON for model training.
• Provides uncertainty estimates alongside percent cover for each of the four lifeform classes.
• Spatial coverage includes eight of the eleven terrestrial biomes in the conterminous U.S. and Alaska.

Limitations

• Platforms conflict on the last update date: Data.gov lists 2026-03-13, while NASA Earthdata lists 2018-12 31.
• Specific column names, row counts, and total dataset size are not provided by any source.
• The license is ambiguously listed as 'other-license-specified' without explicit terms.

Provenance

Source

National Aeronautics and Space Administration (NASA)

Collection Method

Quantile regression forest models applied to Landsat surface reflectance data, trained and validated with airborne LiDAR from G-LiHT and NEON AOP.

Time Range

1984 to 2018

Freshness

2026-03-13

Geography

Conterminous United States (CONUS), with LiDAR training data covering eight terrestrial biomes in CONUS and Alaska.