by Marie-Claude Boileau | 14 November 2022
Published in Forestry Chronicle, vol. 95(2), 101-112.
Canada’s forests have frequently been characterized using binary classifications such as intact/non-intact or managed/unmanaged. A more nuanced classification approach is needed to better understand the geography of forest management in Canada. The best way to represent Canada’s complex diversity of forest management regimes with a simple classification is to categorize according to ownership, protection status and tenure. We gathered federal, provincial and territorial geospatial datasets and used a binary decision tree approach in GIS to classify land into nine classes: (i) Protected, (ii) Restricted, (iii) Federal Reserve, (iv) Indian Reserve, (v) Treaty/Settlement, (vi) Private, (vii) Long-Term Tenure, (viii) Short-Term Tenure, and (ix) Other. These classes are broad; management intensity may vary considerably within classes. Not all forests in Long-Term Tenure or Short-Term Tenure areas are available for timber supply. Government regulations establish considerable reserve areas within forest management units where harvesting is not permitted. The resulting map dataset is current to 2017 and will need to be updated as land designations change.
by Marie-Claude Boileau | 14 November 2022
Published in Canadian Journal of Remote Sensing., vol 39. p. 217-231. https://doi.org/10.5589/m13-030
The aim of this study was to develop an imputing method to map forest stand attributes (height and volume) using panchromatic aerial photographs with a spatial resolution of 30 cm and Landsat images. The method was tested on several black spruce-dominated sites in Québec, Canada. The method involved four procedures: (i) measuring the shadow fraction from panchromatic aerial photographs; (ii) generating regression models between the shadow fraction and forest attributes; (iii) locally mapping the forest attributes as a grid layer (30 m × 30 m); and (iv) expanding the forest attributes from the local maps to a large study area using an imputation approach. Regression models between the shadow fraction and stand attributes were calibrated with ground sample plots and a series of 73 aerial photographs.
The portion of each aerial photograph that was used was restricted to its centre (between 6.2° and 11.3°) to improve goodness-of-fit. Small local maps of stand attributes were thus produced from the shadow fraction and used as the training dataset for an imputing approach, a k nearest-neighbours algorithm, with the aim of mapping forest attributes over a large area.
by Marie-Claude Boileau | 14 November 2022
Published in Forest Ecology and Management, vol. 266, p. 66-74.
This study demonstrates a method for mapping forest stand polygons based on four forest attributes (volume, basal area, height, and crown closure) using shadow fraction values that were estimated from high spatial resolution QuickBird panchromatic images. The method was tested over three test sites in northeastern Canada that were largely dominated by black spruce (Picea mariana (Mill.) BSP). The method involved four sets of procedures: (i) estimating shadow fraction from the panchromatic band of QuickBird images; (ii) generating site-specific and global regression models linking shadow fraction with each of the four forest attributes; (iii) mapping the forest attributes as a grid layer (30 × 30 m) for each test site using the global regression models; and (iv) generating stand polygons from the raster layers. Between 2002 and 2004, 108 ground sample plots were acquired to develop local regression models.
Stand volume maps were produced using both the shadow fraction method and conventional forest stand maps (derived from aerial photo-interpretation) for a test site. Volume patterns were similar, and total volume for the test site differed by only 5.6% between the two maps. Lastly, the raster images derived from the shadow fraction method were used to produce a stand map following guidelines similar to those used by provincial inventory. In all cases, our results suggest that the shadow fraction method is a reliable and convenient way to map forest stand polygons and related attributes of black spruce stands in northeastern Canada.
by Marie-Claude Boileau | 14 November 2022
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.
by Marie-Claude Boileau | 14 November 2022
Published in Botany 96: 411-423 https://doi.org/10.1139/cjb-2018-0016
The long-standing hypothesis that sugar maple (Acer saccharum Marshall) communities are maintained at equilibrium by present climate and small-scale disturbances is questioned because empirical evidence is accumulating about the ability of the species to withstand several stand-scale disturbances. The fire history of a sugar maple site at the northeastern range limit of the species (Gaspe Peninsula, eastern Canada) was documented to test the hypothesis that this forest type is resilient to fire disturbance. The fire history was reconstructed using radiocarbon-dated soil macro-charcoals. Two main fire periods were recorded during the Holocene. The oldest period occurred between 9055 and 8265 cal. years BP, and was characterized by the presence of conifers, including spruce. After 6900 years of fire-free activities, the second period covered the last 1335 years, and was characterized by the presence of sugar maple in the charcoal assemblage. The dominance of sugar maple after more than 1000 years of recurrent fires underlines the species resilience to frequent site disturbances. The soil of the forest stand was heavily disturbed by earthworms. However, the dense seedling and sapling bank of sugar maple suggests that earthworms do not adversely affect the regeneration and survival of the species.
