The Alberta Wildland Fuels Inventory Program (AWFIP): data description and reference tables

The Alberta Wildland Fuels Inventory Program (AWFIP): data description and reference tables

Key message This document describes a dataset obtained from a field sampling program conducted in Alberta, Canada. Field data were used to describe the structure and composition of forest stands, including several fuel loads (e.g., surface, understory, canopy fuels). The dataset can be downloaded fr...

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Bibliographic Details
Published in:Annals of forest science. Vol. 79; no. 1; pp. 1 - 16
Main Authors: Phelps, Nathan, Cameron, Hilary, Forbes, Air M., Schiks, Tom, Schroeder, Dave, Beverly, Jennifer L.
Format: Journal Article
Language:English
Published: Paris Springer Paris 2022
Springer Nature B.V
BMC
Subjects:
Biomedical and Life Sciences
Canopies
Composition
Data Paper
Datasets
Environment
Field inventory
Fire behavior
Forest structure
Forestry
Forestry Management
Fuel load
Fuel measurement
Fuels
Life Sciences
Metadata
Remote sensing
Sampling
Tree Biology
Understory
Vegetation management
Wood Science & Technology
Fire behavior
Forest structure
Fuel load
Field inventory
Fuel measurement
Fuel treatment
Vegetation management
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Description
Summary:Key message This document describes a dataset obtained from a field sampling program conducted in Alberta, Canada. Field data were used to describe the structure and composition of forest stands, including several fuel loads (e.g., surface, understory, canopy fuels). The dataset can be downloaded from https://doi.org/10.17605/OSF.IO/FZ8E4 and metadata is available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/527efb49-43b4-43eb-88b2-70535ff99fc5 We present a quality-checked and curated dataset obtained from a field sampling program conducted in the province of Alberta, Canada. Field data were used to describe the structure and composition of forest stands documented in 476 sampling events. Each sampling event record consists of 42 different variables, including several fuel loads (e.g., surface, understory, canopy fuels). The dataset has been created for operational and research applications including but not limited to fuel classification, estimation of fuel attributes from remote sensing technologies, fuel treatment planning, fire behavior prediction, and use in high resolution fire growth models.
ISSN:1286-4560
1297-966X
DOI:10.1186/s13595-022-01144-w