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Full catalog/Landsat8_Sentinel2_Phenocam_2248
Landsat8_Sentinel2_Phenocam_2248·v1·dataset

When plants leaf out and turn, from satellites and cameras

Phenology derived from Satellite Data and PhenoCam across CONUS and Alaska, 2019-2020
biosphere NASA ORNL_CLOUD Level 3 multiple
In plain English

What it measures. The timing of seasonal plant changes, when vegetation greens up, reaches full leaf, starts to fade, and goes dormant, mapped at fine 30-meter detail across 78 sample regions in the U.S. and Alaska for 2019-2020, along with a gap-free greenness time series.

How it's made. Created by blending Landsat 8 and Sentinel-2 satellite imagery with ground-level PhenoCam camera photos, then fitting a model to detect the key transition dates.

How & where you'd use it. Serves as a high-accuracy reference for studying growing seasons and how vegetation responds to climate, and for validating other phenology products.

What's measured

BIOSPHERE › VEGETATION › PLANT PHENOLOGYCLIMATE INDICATORS › BIOSPHERIC INDICATORS › PHENOLOGICAL CHANGES › PLANT PHENOLOGICAL CHANGES

Coverage & cadence

  • Time span2019-01-01 → 2020-12-31
  • Measured bySentinel-2A (Sentinel-2 MSI) · LANDSAT-8 (OLI)
  • Processing levelLevel 3
  • Spatial extent-145.854, 27.1314, -68.6772, 63.9265
  • Formatsmultiple
  • 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 a reference of land surface phenology (LSP) at 30-m pixels for 78 regions of 10 x 10 km2 across a wide range of ecological and climatic regions in North America during 2019 and 2020. The data were derived by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near- surface PhenoCam time series (hereafter called HP-LSP). The HP-LSP dataset consists of two parts: (1) the 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series and (2) four key phenological transition dates that are greenup onset, maturity onset, senescence onset, and dormancy onset (accuracy less than or equal to five days). The PhenoCam network offers near-surface observations via the RGB (Red, Green, and Blue) imagery every 30 minutes. Each RGB imagery enables us to calculate as many as 100 Green Chromatic Coordinate (GCC) for generating a collection of localized vegetation dynamics. The HLS EVI2 time series with frequent gaps was fused with the most comparable PhenoCam GCC temporal shape selected from the GCC collection using the Spatiotemporal Shape Matching Model (SSMM) to create the synthetic gap-free HLS-PhenoCam EVI2 time series, which was used to establish the physically-based hybrid piecewise logistic model (HPLM) for detecting phenological transition dates (phenometrics).

Get the data

landsat8_sentinel2_phenocam_2248_access.py
import earthaccess
earthaccess.login(strategy="netrc")          # free Earthdata Login

results = earthaccess.search_data(
    short_name="Landsat8_Sentinel2_Phenocam_2248",
    version="1",
    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.