BarrettePareMankaEtAl2018

Référence

Barrette, J., Pare, D., Manka, F., Guindon, L., Bernier, P., Titus, B. (2018) Forecasting the spatial distribution of logging residues across the canadian managed forest. Canadian Journal of Forest Research, 48(12):1470-1481. (Scopus )

Résumé

There is a growing interest in using logging residues as feedstock in the bioeconomy. Quantifying the amount of this resource over large areas has been difficult due to the lack of availability of and consistency in forest inventory data across jurisdictions and the lack of a clear definition of what constitutes logging residues. The goal of this study was to develop an approach to spatially estimate the amounts of logging residues that would potentially be available in the near future for public lands across the Canadian managed forest using remote sensing maps and to compare these estimates with field assessments. Remote sensing estimates of branch and foliage biomass, although only a fraction of total postharvest residual biomass, were generally comparable with estimates from field assessments of recoverable residues after harvesting at the forest management unit (FMU) scale or at the 100 km2 scale. However, they tended to not capture the strong variability between sites and to underestimate observed field values in regions that have very high biomass density. On average, the national logging residue density is estimated to be 26 ± 16 oven-dry tonnes (ODT)·ha−1, and annual national availability is estimated to be 21 M ODT·year−1. Maps produced are available at doi:10.23687/dd94871a-9a20-47f5-825b-768518140f35 and doi:10.23687/5072c495-240c-42a3-ad55-c942ab37c32a. © Her Majesty the Queen in right of Canada 2018.

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@ARTICLE { BarrettePareMankaEtAl2018,
    AUTHOR = { Barrette, J. and Pare, D. and Manka, F. and Guindon, L. and Bernier, P. and Titus, B. },
    TITLE = { Forecasting the spatial distribution of logging residues across the canadian managed forest },
    JOURNAL = { Canadian Journal of Forest Research },
    YEAR = { 2018 },
    VOLUME = { 48 },
    NUMBER = { 12 },
    PAGES = { 1470-1481 },
    NOTE = { cited By 0 },
    ABSTRACT = { There is a growing interest in using logging residues as feedstock in the bioeconomy. Quantifying the amount of this resource over large areas has been difficult due to the lack of availability of and consistency in forest inventory data across jurisdictions and the lack of a clear definition of what constitutes logging residues. The goal of this study was to develop an approach to spatially estimate the amounts of logging residues that would potentially be available in the near future for public lands across the Canadian managed forest using remote sensing maps and to compare these estimates with field assessments. Remote sensing estimates of branch and foliage biomass, although only a fraction of total postharvest residual biomass, were generally comparable with estimates from field assessments of recoverable residues after harvesting at the forest management unit (FMU) scale or at the 100 km2 scale. However, they tended to not capture the strong variability between sites and to underestimate observed field values in regions that have very high biomass density. On average, the national logging residue density is estimated to be 26 ± 16 oven-dry tonnes (ODT)·ha−1, and annual national availability is estimated to be 21 M ODT·year−1. Maps produced are available at doi:10.23687/dd94871a-9a20-47f5-825b-768518140f35 and doi:10.23687/5072c495-240c-42a3-ad55-c942ab37c32a. © Her Majesty the Queen in right of Canada 2018. },
    AFFILIATION = { Natural Resources Canada, Canadian Forest Service, 1055 du P.E.P.S, P.O. Box 10380, Stn. Sainte-Foy, Québec, QC G1V 4C7, Canada; Natural Resources Canada, Pacific Forestry Centre, 506 Burnside Road West, Victoria, BC V8Z 1M5, Canada },
    AUTHOR_KEYWORDS = { Bioenergy; Field assessment; Inventory; Logging residues; Remote sensing },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1139/cjfr-2018-0080 },
    SOURCE = { Scopus },
    URL = { https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057870852&doi=10.1139%2fcjfr-2018-0080&partnerID=40&md5=bad63479f9a6d02c6bc891c4e98dbd2e },
}

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