BeaudoinBernierGuindonEtAl2014

Référence

Beaudoin, A., Bernier, P.Y., Guindon, L., Villemaire, P., Guo, X.J., Stinson, G., Bergeron, T., Magnussen, S. and Hall, R.J. (2014) Mapping attributes of Canada's forests at moderate resolution through kNN and MODIS imagery. Canadian Journal of Forest Research, 44(5):521-532. (URL )

Résumé

Canada's National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 106 km2 of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data. We used the k nearest neighbours (kNN) method with 26 geospatial data layers including MODIS spectral data and climatic and topographic variables to produce maps of 127 forest attributes at a 250 × 250 m resolution. The stand-level attributes include land cover, structure, and tree species relative abundance. In this article, we report only on total live aboveground tree biomass, with all other attributes covered in the supplementary data (http://nrcresearchpress.com/doi/suppl/10.1139/cjfr-2013-0401). In general, deviations in predicted pixel-level values from those in a PP validation set are greater in mountainous regions and in areas with either low biomass or sparse PP sampling. Predicted pixel-level values are overestimated at small observed values and underestimated at large ones. Accuracy measures are improved through the spatial aggregation of pixels to 1 km2 and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org).

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@ARTICLE { BeaudoinBernierGuindonEtAl2014,
    AUTHOR = { Beaudoin, A. and Bernier, P.Y. and Guindon, L. and Villemaire, P. and Guo, X.J. and Stinson, G. and Bergeron, T. and Magnussen, S. and Hall, R.J. },
    TITLE = { Mapping attributes of Canada's forests at moderate resolution through kNN and MODIS imagery },
    JOURNAL = { Canadian Journal of Forest Research },
    YEAR = { 2014 },
    VOLUME = { 44 },
    PAGES = { 521-532 },
    NUMBER = { 5 },
    NOTE = { cited By (since 1996)1 },
    ABSTRACT = { Canada's National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 106 km2 of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data. We used the k nearest neighbours (kNN) method with 26 geospatial data layers including MODIS spectral data and climatic and topographic variables to produce maps of 127 forest attributes at a 250 × 250 m resolution. The stand-level attributes include land cover, structure, and tree species relative abundance. In this article, we report only on total live aboveground tree biomass, with all other attributes covered in the supplementary data (http://nrcresearchpress.com/doi/suppl/10.1139/cjfr-2013-0401). In general, deviations in predicted pixel-level values from those in a PP validation set are greater in mountainous regions and in areas with either low biomass or sparse PP sampling. Predicted pixel-level values are overestimated at small observed values and underestimated at large ones. Accuracy measures are improved through the spatial aggregation of pixels to 1 km2 and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org). },
    AUTHOR_KEYWORDS = { Biomass; Boreal forest; Composition; National baseline inventory; Nonparametric method; Remote sensing; Stand attribute },
    CODEN = { CJFRA },
    DOCUMENT_TYPE = { Article },
    DOI = { 10.1139/cjfr-2013-0401 },
    ISSN = { 12086037 },
    KEYWORDS = { Biomass; Chemical analysis; Pixels; Radiometers; Remote sensing, Aboveground tree biomass; Boreal forests; K nearest neighbours (k-NN); Moderate resolution; Mountainous regions; National baseline inventory; National forest inventories; Nonparametric methods, Forestry, aboveground biomass; accuracy assessment; boreal forest; data set; forest cover; forest inventory; forest management; map; MODIS; pixel; sampling; satellite imagery; stand structure; vegetation mapping, Biomass; Chemical Analysis; Chemical Composition; Forestry; Inventories; Radiometry; Remote Sensing, Canada },
    SOURCE = { Scopus },
    URL = { http://www.nrcresearchpress.com/doi/abs/10.1139/cjfr-2013-0401#.UvzgW_t4CQU },
}

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