Summary
Published in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8(11), 5199-5211.
Boreal forests have a significant impact on the Earth's climate and on global warming. In this context, a large-scale mapping method was developed to characterize forest attributes, surficial deposits and forest disturbance history in the absence of support datasets. The method, which was based on remote sensing data, image processing techniques and image interpretation, was applied over a very large area (680 000 km2) of Québec (Canada) that was dominated by black spruce (Picea mariana [Miller] BSP). The method involved five steps: 1) mapping the vegetation based on unsupervised classification, imputation and segmentation methods; 2) mapping the history of fires that occurred over the mapping area based on archive Landsat images; 3) determining the dominant species characterizing forest stands; 4) mapping surficial deposits; and 5) assessing accuracy of map attributes based on video datasets. Kappa values ranged from 72.5% to 96.3%. The results demonstrated that our method is a convenient and inexpensive way of mapping forest ecosystems over large areas of the northern boreal forest.
File
Sector(s):
Forests
Categorie(s):
Scientific Article
Theme(s):
Cartography and Data, Imaging and LiDAR
Departmental author(s):
Author(s)
LEBOEUF, Antoine and Richard A. FOURNIER
Year of publication :
2015
Format :
Keywords :
Boreal forest, fire history, forest attributes, Landsat, RapidEye, surficial deposits
