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Full catalog/Global_SIF_OCO2_MODIS_1863
Global_SIF_OCO2_MODIS_1863·v2·dataset

How actively plants photosynthesize, gap-free (OCO-2 + MODIS)

High Resolution Global Contiguous SIF Estimates from OCO-2 SIF and MODIS, Version 2
biosphere NASA ORNL_CLOUD Level 3 netCDF-4 classic
In plain English

What it measures. Gap-free global maps of solar-induced chlorophyll fluorescence, a faint glow plants give off when they photosynthesize, which serves as a stand-in for how actively plants are turning sunlight into food. Cells are about 5 km across, every 16 days from 2014 to 2020.

How it's made. Created by training a neural network on actual fluorescence readings from the OCO-2 satellite together with MODIS surface reflectance, then using it to fill in the areas OCO-2 didn't directly observe.

How & where you'd use it. Supports drought monitoring, crop planning and yield estimates, and gives scientists a consistent benchmark for comparing satellite plant-activity measurements with ground observations.

What's measured

BIOSPHERE › VEGETATION › SOLAR INDUCED FLUORESCENCEBIOSPHERE › VEGETATION › CHLOROPHYLLBIOSPHERE › ECOLOGICAL DYNAMICS › ECOSYSTEM FUNCTIONS › PRIMARY PRODUCTIONBIOSPHERE › VEGETATION › LEAF CHARACTERISTICS

Coverage & cadence

  • Time span2014-09-01 → 2020-07-31
  • Measured byTerra (MODIS) · Aqua (MODIS) · MODELS (Computer) · OCO-2 (SPECTROMETERS)
  • Processing levelLevel 3
  • Spatial extent-180, -90, 180, 90
  • FormatsnetCDF-4 classic
  • StatusCOMPLETE

What you can do with it

  • Map vegetation, forests and biomass
  • Monitor ecosystem productivity and carbon
  • Support habitat and biodiversity studies
Official description

This dataset provides spatially-contiguous global mean daily solar-induced chlorophyll fluorescence (SIF) estimates at 0.05 degree (approximately 5 km at the equator) spatial and 16-day temporal resolution from September 2014 through July 2020. This product was derived from Orbiting Carbon Observatory-2 (OCO-2) SIF observations and produced by training an artificial neural network (ANN) on the native OCO-2 SIF observations and MODIS BRDF-corrected seven-band surface reflectance along OCO-2's orbits. The trained ANN model was then applied to predict mean daily SIF (mW/m2/nm/sr) in OCO-2's gap regions based on MODIS reflectance and landcover. This framework was stratified by biomes and 16-day time steps. This dataset's high resolution and global contiguous coverage will greatly enhance the synergy between satellite SIF and photosynthesis measured on the ground at consistent spatial scales. Potential applications of this dataset include advancing dynamic drought monitoring and mitigation, informing agricultural planning and yield estimation, and providing a benchmark for upcoming satellite missions with SIF capabilities at higher spatial resolutions.

Get the data

global_sif_oco2_modis_1863_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="Global_SIF_OCO2_MODIS_1863",
    version="2",
    bounding_box=(-122.5, 37.2, -121.8, 37.9),  # your area (W,S,E,N)
    temporal=("2024-01-01", "2024-12-31"),       # your dates
)
files = earthaccess.open(results)   # stream straight from ORNL_CLOUD
Browsing CMR needs no login. Downloading or streaming bytes needs a free Earthdata Login + the earthaccess package.