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    • MODIS-based GPP, PAR, fC4, and SANIRv estimates from SLOPE for CONUS, 2000-2019

    Metadata Updated: December 7, 2023

    This dataset contains estimated gross primary productivity (GPP), photosynthetically active radiation (PAR), soil adjusted near infrared reflectance of vegetation (SANIRv), the fraction of C4 crops in vegetation (fC4), and their uncertainties for the conterminous United States (CONUS) from 2000 to 2019. The daily estimates are SatelLite Only Photosynthesis Estimation (SLOPE) products at 250-m resolution. There are three distinct features of the GPP estimation algorithm: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR, (2) SLOPE couples gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRv (SANIRv) dataset, and (3) SLOPE couples a temporal pattern recognition approach with a long-term Crop Data Layer (CDL) product to predict dynamic C4 crop fraction. PAR, SANIRv and C4 fraction are used to drive a parsimonious model with only two parameters to estimate GPP, along with a quantitative uncertainty, on a per-pixel and daily basis. The slope GPP product has an R2 = 0.84 and a root-mean-square error (RMSE) of 1.65 gC m-2 d-1.

    Access & Use Information

    Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

    Downloads & Resources

    Dates

    Metadata Created Date December 1, 2022
    Metadata Updated Date December 7, 2023

    Metadata Source

    Harvested from NASA Data.json

    Other Data Resources

    Graphic Preview

    Spatial distribution of (a) GPP (gC m2/d) and (b) GPP uncertainty (gC m2/d) across the CONUS at 250-m resolution for 10 July 2020 (image source: Jiang et al. 2021).

    Additional Metadata

    Resource Type Dataset
    Metadata Created Date December 1, 2022
    Metadata Updated Date December 7, 2023
    Publisher ORNL_DAAC
    Maintainer
    Identifier C2266194621-ORNL_CLOUD
    Data First Published 2021-11-13
    Language en-US
    Data Last Modified 2023-06-12
    Category CMS, geospatial
    Public Access Level public
    Bureau Code 026:00
    Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
    Metadata Catalog ID https://data.nasa.gov/data.json
    Schema Version https://project-open-data.cio.gov/v1.1/schema
    Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
    Citation Jiang, C., and K. Guan. 2020. MODIS-based GPP, PAR, fC4, and SANIRv estimates from SLOPE for CONUS, 2000-2019. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/1786
    Graphic Preview Description Spatial distribution of (a) GPP (gC m2/d) and (b) GPP uncertainty (gC m2/d) across the CONUS at 250-m resolution for 10 July 2020 (image source: Jiang et al. 2021).
    Graphic Preview File https://daac.ornl.gov/CMS/guides/SLOPE_GPP_CONUS_Fig1.png
    Harvest Object Id 26e2e870-c0c0-4817-ad5f-91bf1cae3850
    Harvest Source Id 58f92550-7a01-4f00-b1b2-8dc953bd598f
    Harvest Source Title NASA Data.json
    Homepage URL https://doi.org/10.3334/ORNLDAAC/1786
    Metadata Type geospatial
    Old Spatial -155.57 19.99 -52.22 50.01
    Program Code 026:001
    Source Datajson Identifier True
    Source Hash da9b1d3f57535fd5ab68ef08f1c05329ddd613fc55a6162685296c495a616ec1
    Source Schema Version 1.1
    Spatial
    Temporal 2000-01-01T00:00:00Z/2020-01-01T23:59:59Z

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