SLOPE: Daily GPP Estimates for CONUS at 250m, 2000-2019

Daily 250-meter resolution estimates of gross primary productivity (GPP), photosynthetically active radiation (PAR), soil-adjusted near infrared reflectance of vegetation (SANIRv), and C4 crop fraction cover the conterminous United States from 2000 to 2019. The SLOPE algorithm couples machine learning with MODIS satellite data from Terra and Aqua, achieving a reported R2 of 0.84 and an RMSE of 1.65 gC m-2 d-1 for GPP. It provides per-pixel daily values along with quantitative uncertainty estimates.

Use Cases

• Modeling terrestrial carbon fluxes based on daily GPP estimates.
• Analyzing crop type influence on regional photosynthesis using dynamic C4 fraction maps.
• Validating other ecosystem models against the SLOPE product's reported R2 and RMSE.
• Studying vegetation productivity trends over two decades across CONUS.
• Estimating photosynthetically active radiation (PAR) at the land surface from satellite data.

Strengths

• Covers a 20-year time range (2000-2019).
• Provides daily estimates at a fine 250-meter spatial resolution.
• Algorithm validation shows an R2 of 0.84 and RMSE of 1.65 gC m-2 d-1.
• Includes quantitative uncertainty estimates for each variable.

Limitations

• Column names and exact data structure are not specified in the provided metadata.
• Conflicting last-updated dates exist between sources (2026 vs. 2020).
• Spatial coverage is limited to the conterminous United States (CONUS).

Provenance

Source

National Aeronautics and Space Administration

Collection Method

SatelLite Only Photosynthesis Estimation (SLOPE) algorithm using MODIS atmosphere and land products from Terra and Aqua satellites, coupled with machine learning and the Crop Data Layer.

Time Range

2000 to 2019

Freshness

2026-04-10 00:57:12.325871

Geography

Conterminous United States (CONUS)