NWT Relief Basemap

Manitoba's forest boundaries datasets in 2021. This data is used within Manitoba's Five Year Report on the Status of Forestry, 2016 - 2021 story map. Manitoba's forest boundaries datasets in 2021. This data is used within Manitoba's Five Year Report on the Status of Forestry, 2016 - 2021 story map.  The forest boundaries included represent forest sections, forest management units, provincial forests and forest management license areas.

This dataset corresponds to daily snow cover percentage at 1km resolution grid over land areas of Canada from 2006-2010. The data are subsampled by 4km to reduce data volumes and considering the geolocation uncertainty of the input satellite imagery. The daily maps are generated by assimilation of daily cloud screened NOAA AVHRR satellite imagery and Canadian Meteorological Centre (CMC) snow depth analysis snow depth and density fields within an off-line version of the CMC daily snow depth model. The snow depth model is modified to include snowpack reflectance model and a surface radiative transfer scheme that relates vegetation and snowpack reflectance to top-of-canopy bi-directional reflectance. A logistic vegetation phenology model is used to parameterize temporal dynamics of canopy leaf area index. A per-pixel particle filter with a 30 day moving window is applied to assimilation observations corresponding to 1km resolution visible band directional reflectance and normalized difference vegetation index and 24km CMC daily snow depth and monthly snow density fields. The assimilation is forced using daily air temperature and precipitation fields. Validation of the datasets has been performed by comparison to MODIS snow cover maps and in-situ snow depth stations across Canada. Validation suggests similar accuracy to MODIS snow cover products over relatively flat terrain. Validation over mountainous regions is ongoing.

Polygons denoting concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations and the area occupied by successive catch weight thresholds was used to identify aggregations. These analyses were performed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures. These polygons identify sponge grounds from the broader distribution of sponges in the Southern Gulf region as sampled by Western II A gear in the Gulf biogeographic zone. A 3 kg minimum threshold for the sponge catch was identified as the weight that separated the sponge ground habitat from the broader distribution of sponges with these research vessel tow data and gear type.

Manitoba's forest boundaries datasets in 2021. This data is used within Manitoba's Five Year Report on the Status of Forestry, 2016 - 2021 story map. Manitoba's forest boundaries datasets in 2021. This data is used within Manitoba's Five Year Report on the Status of Forestry, 2016 - 2021 story map.  The forest boundaries included represent forest sections, forest management units, provincial forests and forest management license areas.

Manitoba's forest boundaries datasets in 2021. This data is used within Manitoba's Five Year Report on the Status of Forestry, 2016 - 2021 story map. Manitoba's forest boundaries datasets in 2021. This data is used within Manitoba's Five Year Report on the Status of Forestry, 2016 - 2021 story map.  The forest boundaries included represent forest sections, forest management units, provincial forests and forest management license areas.

Canadas Managed Forests 2017 Albers Equal Area Canada's Managed Forests 2017 Albers Equal Area

Concentrations of sea pens, small and large gorgonian corals and sponges on the east coast of Canada have been identified through spatial analysis of research vessel survey by-catch data following an approach used by the Northwest Atlantic Fisheries Organization (NAFO) in the Regulatory Area (NRA) on Flemish Cap and southeast Grand Banks. Kernel density analysis was used to identify high concentrations. These analyses were performed for each of the five biogeographic zones of eastern Canada. The largest sea pen fields were found in the Laurentian Channel as it cuts through the Gulf of St. Lawrence, while large gorgonian coral forests were found in the Eastern Arctic and on the northern Labrador continental slope. Large ball-shaped Geodia spp. sponges were located along the continental slopes north of the Grand Banks, while on the Scotian Shelf a unique population of the large barrel-shaped sponge Vazella pourtalesi was identified. The latitude and longitude marking the positions of all tows which form these and other dense aggregations are provided along with the positions of all tows which captured black coral, a non-aggregating taxon which is long-lived and vulnerable to fishing pressures.

IBL - Imagery, basemaps, and land cover (imageryBaseMapsEarthCover) Basemaps. For example, resources describing land cover, topographic maps, and classified and unclassified images

This data set comprises all of the current feature classes in the Alberta Provincial Electoral Divisions profiles. This data is derived from the 2021 Census of Canada.