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

Overview

DOIhttps://doi.org/10.3334/ORNLDAAC/1786
Version1
Project
Published2021-12-03
Updated2021-11-13
Usage117 downloads

Description

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.

Science Keywords

  • LAND SURFACE
  • SURFACE RADIATIVE PROPERTIES
  • REFLECTANCE
  • BIOSPHERE
  • VEGETATION
  • PHOTOSYNTHETICALLY ACTIVE RADIATION
  • BIOSPHERE
  • VEGETATION
  • PLANT CHARACTERISTICS
  • SPECTRAL/ENGINEERING
  • INFRARED WAVELENGTHS
  • REFLECTED INFRARED
  • LAND SURFACE
  • SOILS
  • SOIL PRODUCTIVITY
  • GROSS PRIMARY PRODUCTION (GPP)

Data Use and Citation

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Crosscite Citation Formatter
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

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Companion Files

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Dataset has 2 companion files.

  • read_check.zip
  • SLOPE_GPP_CONUS.pdf