Canadian Forest Service Publications
Mapping attributes of Canada’s forests at moderate resolution through kNN and MODIS imagery. 2014. Beaudoin, A.; Bernier, P.Y.; Guindon, L.; Villemaire, P.; Guo, X.J.; Stinson, G.; Bergeron, T.; Magnussen, S.; Hall, R.J. Can. J. For. Res. 44:521-532.
Issued by: Laurentian Forestry Centre
Catalog ID: 35489
CFS Availability: PDF (request by e-mail)
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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 (_k_NN) 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).
Plain Language Summary
In Canada, the provinces and territories are responsible for managing their forests and performing inventories based on their specific needs. Because of this, the data collected vary from province to province, which presents an obstacle when studying trans-border forest issues (e.g. insect outbreaks). The National Forest Inventory (NFI) partially addresses this gap by compiling and harmonizing provincial and territorial inventories. However, this covers only 1% of Canada’s landmass, and continuous mapping is needed to analyze many forest issues.
The focus of this research project was to overcome this constraint by developing pan-Canadian forest maps at a resolution of 250 m x 250 m. The data used to describe the forest stands are taken from NFI “photo plots” covering 1% of the territory. Applying a statistical technique (k-nearest-neighbours or kNN) to data from MODIS satellite images, climate data layers and topographic data layers makes it possible to use information from the photo plots to estimate a number of forest attributes for the remaining 99% of forest area.
The 127 attributes mapped this way include the height, age, volume, biomass quantity and species composition of forests, and more. Standardized mapping of forest attributes for all of Canada’s forests is a major technical breakthrough that improves our ability to analyze human and natural activities affecting Canada’s forests.