Mapping attributes of Canada's forests at moderate resolution through kNN and MODIS imagery

被引:244
作者
Beaudoin, A. [1 ]
Bernier, P. Y. [1 ]
Guindon, L. [1 ]
Villemaire, P. [1 ]
Guo, X. J. [1 ]
Stinson, G. [2 ]
Bergeron, T. [1 ]
Magnussen, S. [2 ]
Hall, R. J. [3 ]
机构
[1] Nat Resources Canada, Canadian Forest Serv, Laurentian Forestry Ctr, Quebec City, PQ G1V 4C7, Canada
[2] Nat Resources Canada, Canadian Forest Serv, Pacific Forestry Ctr, Victoria, BC V8Z 1M5, Canada
[3] Nat Resources Canada, Canadian Forest Serv, No Forestry Ctr, Edmonton, AB T6H 3S5, Canada
关键词
nonparametric method; remote sensing; boreal forest; stand attribute; biomass; composition; national baseline inventory; NEAREST-NEIGHBOR IMPUTATION; SPATIAL-RESOLUTION; INVENTORY; AREA; VARIABLES; LEVEL; PLOTS;
D O I
10.1139/cjfr-2013-0401
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
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 x 10(6) km(2) 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 x 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 km(2) and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org).
引用
收藏
页码:521 / 532
页数:12
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