Pan-Arctic Vegetation Cover (PAVC) Gridded v1.0 --- High resolution fractional coverage maps of plant functional types at 20-meter spatial resolution

Zhang, Tianqi; Steckler, Morgan; Breen, Amy; Hoffman, Forrest; Hargrove, William; Salmon, Vertiy; Iversen, Colleen; Wullschleger, Stan; Kumar, Jitendra

doi:10.15485/2513385

Title: Pan-Arctic Vegetation Cover (PAVC) Gridded v1.0 --- High resolution fractional coverage maps of plant functional types at 20-meter spatial resolution

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Abstract

The PAVC-Gridded datasets were created to provide detailed fractional cover information for typical tundra plant functional types (PFTs) across Arctic Alaska, which will be embedded in terrestrial ecosystem models for improving carbon flux estimates. The PFT-level fractional cover also helps characterize the vegetation composition at sub-pixel level for understanding the tundra response to warming climate. This dataset includes 8 Tiff files containing fractional cover for 7 PFTs in the Arctic region of Alaska, USA. There are Tiffs for (1) bryophytes; (2) lichens; (3) non-vascular plants, i.e., the sum of lichens and bryophytes; (4) deciduous shrubs, (5) evergreen shrubs, (6) forbs, (7) graminoids, and a non-PFT class (8) litter. Each pixel in the Tiff file contains the cover (expressed as a fraction of total ground cover) that was predicted by a random-forest regression model. The random-forest models were trained on cover data collected at 978 plots from 2010 to 2021, of which are archived in the Pan-Arctic Vegetation Cover (PAVC) database (https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2483557). The plot cover was linked to 20-meter spatial resolution, satellite-derived predictor variables: Sentinel-2 spectra and Sentinel-1 polarizations averaged over the 2019 growing season, as well as topographical features derived from ArcticDEM. Then, spatio-temporally anomalous plot data that introduced largemore »« less

Authors:

;

Oak Ridge National Laboratory
University of Alaska Fairbanks
USDA Forest Service - SRS

Publication Date:: Sat Mar 01 04:00:00 UTC 2025

Other Number(s):: NGA560

DOE Contract Number:: AC02-05CH11231

Research Org.:: Next-Generation Ecosystem Experiments (NGEE) Arctic

Sponsoring Org.:: U.S. DOE > Office of Science > Biological and Environmental Research (BER)

Subject:: 54 ENVIRONMENTAL SCIENCES; EARTH SCIENCE > BIOSPHERE > VEGETATION; EARTH SCIENCE > BIOSPHERE > VEGETATION > VEGETATION COVER; EARTH SCIENCE > LAND SURFACE > LAND USE/LAND COVER; ESS-DIVE File Level Metadata Reporting Format

OSTI Identifier:: 2513385

DOI:: https://doi.org/10.15485/2513385

Citation Formats


                    Zhang, Tianqi, Steckler, Morgan, Breen, Amy, Hoffman, Forrest, Hargrove, William, Salmon, Vertiy, Iversen, Colleen, Wullschleger, Stan, and Kumar, Jitendra. Pan-Arctic Vegetation Cover (PAVC) Gridded v1.0 --- High resolution fractional coverage maps of plant functional types at 20-meter spatial resolution.  United States: N. p., 2025. 
        Web.  doi:10.15485/2513385.

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                    Zhang, Tianqi, Steckler, Morgan, Breen, Amy, Hoffman, Forrest, Hargrove, William, Salmon, Vertiy, Iversen, Colleen, Wullschleger, Stan, & Kumar, Jitendra. Pan-Arctic Vegetation Cover (PAVC) Gridded v1.0 --- High resolution fractional coverage maps of plant functional types at 20-meter spatial resolution.  United States.  doi:https://doi.org/10.15485/2513385

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                    Zhang, Tianqi, Steckler, Morgan, Breen, Amy, Hoffman, Forrest, Hargrove, William, Salmon, Vertiy, Iversen, Colleen, Wullschleger, Stan, and Kumar, Jitendra. 2025.  
"Pan-Arctic Vegetation Cover (PAVC) Gridded v1.0 --- High resolution fractional coverage maps of plant functional types at 20-meter spatial resolution".  United States.  doi:https://doi.org/10.15485/2513385.  https://www.osti.gov/servlets/purl/2513385. Pub date:Sat Mar 01 04:00:00 UTC 2025

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@article{osti_2513385,

  title        = {Pan-Arctic Vegetation Cover (PAVC) Gridded v1.0 --- High resolution fractional coverage maps of plant functional types at 20-meter spatial resolution},

  author       = {Zhang, Tianqi and Steckler, Morgan and Breen, Amy and Hoffman, Forrest and Hargrove, William and Salmon, Vertiy and Iversen, Colleen and Wullschleger, Stan and Kumar, Jitendra},

  abstractNote = {The PAVC-Gridded datasets were created to provide detailed fractional cover information for typical tundra plant functional types (PFTs) across Arctic Alaska, which will be embedded in terrestrial ecosystem models for improving carbon flux estimates. The PFT-level fractional cover also helps characterize the vegetation composition at sub-pixel level for understanding the tundra response to warming climate. This dataset includes 8 Tiff files containing fractional cover for 7 PFTs in the Arctic region of Alaska, USA. There are Tiffs for (1) bryophytes; (2) lichens; (3) non-vascular plants, i.e., the sum of lichens and bryophytes; (4) deciduous shrubs, (5) evergreen shrubs, (6) forbs, (7) graminoids, and a non-PFT class (8) litter. Each pixel in the Tiff file contains the cover (expressed as a fraction of total ground cover) that was predicted by a random-forest regression model. The random-forest models were trained on cover data collected at 978 plots from 2010 to 2021, of which are archived in the Pan-Arctic Vegetation Cover (PAVC) database (https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2483557). The plot cover was linked to 20-meter spatial resolution, satellite-derived predictor variables: Sentinel-2 spectra and Sentinel-1 polarizations averaged over the 2019 growing season, as well as topographical features derived from ArcticDEM. Then, spatio-temporally anomalous plot data that introduced large variability to the regression outcomes were dropped using the Cook’s distance outlier detection method, and the models were re-created using high-quality plots and their associated satellite derived explanatory variables per each PFT. The correlations between plot-observed and satellite-derived fractional cover for all PFTs were well correlated (R2 = 0.69–0.95 and 0.5 for litter) and had low RMSE bias (0.02–0.11). This research was performed as a part of the NGEE Arctic project. The NGEE Arctic project was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.},

  doi          = {10.15485/2513385},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Sat Mar 01 04:00:00 UTC 2025},

  month        = {Sat Mar 01 04:00:00 UTC 2025}

}

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DOI: https://doi.org/10.15485/2513385

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