Forest Biomass Estimates from AVIRIS-NG and UAVSAR in Louisiana Wetlands

NASA's dataset provides geospatial estimates of forest aboveground biomass (AGB) for the Atchafalaya and Terrebonne Basins in Louisiana. The data were generated by applying a machine learning regression model, trained on in-situ plot data from 2015 and 2021, to airborne AVIRIS-NG hyperspectral and UAVSAR radar mosaics. The final product consists of cloud-optimized GeoTIFF maps derived from these combined remote sensing sources.

Use Cases

• Mapping carbon storage in coastal forest ecosystems using derived biomass estimates.
• Validating satellite-based biomass products with high-resolution airborne sensor data.
• Analyzing relationships between vegetation type and biomass density across wetland basins.
• Monitoring changes in forest structure over time by comparing with future or past surveys.

Strengths

• Model incorporates in-situ forest plot data from two field campaigns (Summer 2015 and Fall 2021).
• Derived from fusion of two advanced airborne remote sensing instruments: AVIRIS-NG hyperspectral and UAVSAR polarimetric radar.
• Data is provided in a modern, cloud-optimized GeoTIFF format for efficient access.

Limitations

• Conflicting last updated dates: Data.gov lists 2026-03 13, while NASA Earthdata lists 2021-09-24, creating uncertainty about the most recent version.
• Specific column names, row counts, and file sizes are not provided by any source.
• License is ambiguously listed as 'other-license-specified' without clear terms.

Provenance

Source

National Aeronautics and Space Administration (NASA)

Collection Method

Machine learning regression model applied to AVIRIS-NG surface reflectance and UAVSAR polarimetric decomposition mosaics, trained on coincident in-situ forest plot measurements.

Time Range

2015 to 2021

Freshness

2026-03-13 03:17:59.496914

Geography

Atchafalaya and Terrebonne Basins, Louisiana, United States