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Dataset of timberland variables used to assess forest conditions in two Southeastern United States׳ fuelsheds()

The data presented in this article are related to the research article entitled “How is wood-based pellet production affecting forest conditions in the southeastern United States?” (Dale et al., 2017) [1]. This article describes how United States Forest Service (USFS) Forest Inventory and Analysis (...

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Detalles Bibliográficos
Autores principales: Parish, Esther S., Dale, Virginia H., Tobin, Emma, Kline, Keith L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470533/
https://www.ncbi.nlm.nih.gov/pubmed/28649587
http://dx.doi.org/10.1016/j.dib.2017.05.048
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author Parish, Esther S.
Dale, Virginia H.
Tobin, Emma
Kline, Keith L.
author_facet Parish, Esther S.
Dale, Virginia H.
Tobin, Emma
Kline, Keith L.
author_sort Parish, Esther S.
collection PubMed
description The data presented in this article are related to the research article entitled “How is wood-based pellet production affecting forest conditions in the southeastern United States?” (Dale et al., 2017) [1]. This article describes how United States Forest Service (USFS) Forest Inventory and Analysis (FIA) data from multiple state inventories were aggregated and used to extract ten annual timberland variables for trend analysis in two case study bioenergy fuelshed areas. This dataset is made publically available to enable critical or extended analyses of changes in forest conditions, either for the fuelshed areas supplying the ports of Savannah, Georgia and Chesapeake, Virginia, or for other southeastern US forested areas contributing biomass to the export wood pellet industry.
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spelling pubmed-54705332017-06-23 Dataset of timberland variables used to assess forest conditions in two Southeastern United States׳ fuelsheds() Parish, Esther S. Dale, Virginia H. Tobin, Emma Kline, Keith L. Data Brief Data Article The data presented in this article are related to the research article entitled “How is wood-based pellet production affecting forest conditions in the southeastern United States?” (Dale et al., 2017) [1]. This article describes how United States Forest Service (USFS) Forest Inventory and Analysis (FIA) data from multiple state inventories were aggregated and used to extract ten annual timberland variables for trend analysis in two case study bioenergy fuelshed areas. This dataset is made publically available to enable critical or extended analyses of changes in forest conditions, either for the fuelshed areas supplying the ports of Savannah, Georgia and Chesapeake, Virginia, or for other southeastern US forested areas contributing biomass to the export wood pellet industry. Elsevier 2017-05-27 /pmc/articles/PMC5470533/ /pubmed/28649587 http://dx.doi.org/10.1016/j.dib.2017.05.048 Text en © 2017 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Data Article
Parish, Esther S.
Dale, Virginia H.
Tobin, Emma
Kline, Keith L.
Dataset of timberland variables used to assess forest conditions in two Southeastern United States׳ fuelsheds()
title Dataset of timberland variables used to assess forest conditions in two Southeastern United States׳ fuelsheds()
title_full Dataset of timberland variables used to assess forest conditions in two Southeastern United States׳ fuelsheds()
title_fullStr Dataset of timberland variables used to assess forest conditions in two Southeastern United States׳ fuelsheds()
title_full_unstemmed Dataset of timberland variables used to assess forest conditions in two Southeastern United States׳ fuelsheds()
title_short Dataset of timberland variables used to assess forest conditions in two Southeastern United States׳ fuelsheds()
title_sort dataset of timberland variables used to assess forest conditions in two southeastern united states׳ fuelsheds()
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5470533/
https://www.ncbi.nlm.nih.gov/pubmed/28649587
http://dx.doi.org/10.1016/j.dib.2017.05.048
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