Journal
CANADIAN JOURNAL OF REMOTE SENSING
Volume 46, Issue 5, Pages 567-584Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/07038992.2020.1811083
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Funding
- Canadian Space Agency (CSA) Government Related Initiatives Program (GRIP)
- Canadian Forest Service (CFS) of Natural Resources Canada
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We developed a methodology for extending estimates of the presence-absence of trees and several tree species contained in the Canadian National Forest Inventory using nationally consistent Landsat data products. For a prototype boreal forest region of Newfoundland and Labrador, Canada, we modeled and assessed changes in the presence-absence of trees and tree species distributions over a 25-year period. Random Forest models of presence-absence of trees had an overall classification accuracy of 0.87 +/- 0.019. For five tree species, overall classification accuracies were: 0.74 +/- 0.017 for balsam fir; 0.75 +/- 0.028 for black spruce; 0.64 +/- 0.085 for trembling aspen; 0.64 +/- 0.035 for tamarack; and 0.77 +/- 0.041 for white birch. While the proportion of treed area increased by 8.5% over the 25-year period, the area occupied by black spruce declined by 13.5%. The area of balsam fir and white birch increased by 9.9% and 28.2%, respectively, while trembling aspen and tamarack changed by less than 5%. The map products developed and trends observed offer baseline information in support of long-term monitoring of treed area and tree species distributions. The demonstrated methods encourage development of spatially-explicit map products to complement spatially or temporally limited forest inventory datasets.
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