Abstract
Field-measured Arctic vegetation cover data is essential for creating accurate, high-quality vegetation structure and composition maps. Extrapolating field data into high-resolution cover maps provides detailed, function-specific information for use in Earth System Models, vegetation classifications, and monitoring vegetation change over time and space. However, field campaigns that collect plant cover vary substantially in scope, method, and purpose, which makes them difficult to unify across data stores, and they are often not designed to meet remote sensing needs. In this work, we synthesized and harmonized field-based fractional cover data from various data stores to create a high-quality, consistent repository schema for remote sensing-based vegetation cover mapping applications. We developed a reproducible workflow for synthesizing visual estimate and point-intercept fractional cover data. The resultant Pan-Arctic Vegetation Cover (PAVC) database contains synthesized fractional cover at both the species and plant functional type levels. The latter includes absolute foliar cover for deciduous shrubs and trees, evergreen shrubs and trees, forbs, graminoids, lichen, bryophytes, and “other” vegetation, as well as absolute cover for litter and top cover for water and bare ground.
| Original language | English |
|---|---|
| Article number | 1271 |
| Journal | Scientific Data |
| Volume | 12 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2025 |
Funding
This research was partially supported by the NGEE Arctic project which is sponsored by the Biological and Environmental Research program in the Department of Energy’s Office of Science. We thank the Mary’s Igloo, Council, and Sitnasuak Native Corporations for their guidance and for permitting us to quantify vegetation cover on their lands. Partial support was provided by the United States Army Corps of Engineers (USACE) Engineering Research and Development Center (ERDC) Geospatial Research Laboratory (GRL) and was accomplished under Cooperative Agreement Federal Award Identification Number (FAIN) W9132V-22-2-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of USACE ERDC GRL or the U.S. Government. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (“ http://energy.gov/downloads/doe-public-access-plan ”). This material is based in part upon work supported by the National Ecological Observatory Network (NEON), a program sponsored by the U.S. National Science Foundation (NSF) and operated under cooperative agreement by Battelle. This research was partially supported by the NGEE Arctic project which is sponsored by the Biological and Environmental Research program in the Department of Energy’s Office of Science. We thank the Mary’s Igloo, Council, and Sitnasuak Native Corporations for their guidance and for permitting us to quantify vegetation cover on their lands. Partial support was provided by the United States Army Corps of Engineers (USACE) Engineering Research and Development Center (ERDC) Geospatial Research Laboratory (GRL) and was accomplished under Cooperative Agreement Federal Award Identification Number (FAIN) W9132V-22-2-0001. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of USACE ERDC GRL or the U.S. Government. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (“http://energy.gov/downloads/doe-public-access-plan ”). This material is based in part upon work supported by the National Ecological Observatory Network (NEON), a program sponsored by the U.S. National Science Foundation (NSF) and operated under cooperative agreement by Battelle. The PAVC database is archived on the Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) Repository at https://doi.org/10.15485/2483557 . The final synthesized database and metadata were formatted according to Environmental System Science Data Infrastructure for a Virtual Ecosystem (ESS-DIVE) File-Level Meta-Data (FLMD) v1 standards. ESS-DIVE is a data repository for Earth and environmental sciences data supported by the Department of Energy Biological and Environmental Research program. There are four datasets within the database: “species_pft_checklist,” “synthesized_species_fcover,” “synthesized_pft_fcover,” and “survey_unit_information,” all of which are stored in UTF-8-Sig encoded Comma Separated Value (CSV) format (Fig. ). For each data file, there is an associated FLMD CSV that provides information about the data file itself, as well as a data dictionary (DD) CSV, which explains the data file’s header information. This format ensures easy readability by people, scripting languages, and table-viewing software.