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PAVC: The foundation for a Pan-Arctic Vegetation Cover database.

Morgan R Steckler1, Jitendra Kumar2, Amy L Breen3

  • 1Oak Ridge National Laboratory Computational Science and Engineering Division, Oak Ridge, TN, USA. stecklermr@ornl.gov.

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|July 21, 2025
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Summary

This study harmonized Arctic field data to create a consistent database for vegetation cover mapping. The Pan-Arctic Vegetation Cover (PAVC) database supports remote sensing applications and Earth System Models.

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Area of Science:

  • Ecology
  • Remote Sensing
  • Geospatial Science

Background:

  • Accurate Arctic vegetation cover data is crucial for mapping vegetation structure and composition.
  • Existing field data collection methods vary, hindering unification for remote sensing applications.
  • High-resolution vegetation maps are vital for Earth System Models and monitoring ecological change.

Purpose of the Study:

  • To synthesize and harmonize diverse field-based fractional cover data from the Arctic.
  • To establish a high-quality, consistent repository schema for remote sensing-based vegetation mapping.
  • To develop a reproducible workflow for integrating various fractional cover data types.

Main Methods:

  • Synthesized and harmonized field-based fractional cover data from multiple sources.
  • Developed a reproducible workflow for combining visual estimate and point-intercept data.
  • Created the Pan-Arctic Vegetation Cover (PAVC) database.

Main Results:

  • The Pan-Arctic Vegetation Cover (PAVC) database contains synthesized fractional cover data.
  • Data is available at both species and plant functional type levels.
  • Includes absolute foliar cover for various vegetation types, litter, water, and bare ground.

Conclusions:

  • The PAVC database provides a consistent resource for remote sensing-based vegetation mapping.
  • This harmonized data facilitates improved Earth System Models and vegetation monitoring.
  • The reproducible workflow enables future data integration and database expansion.