Overview map of the Yukon

A WMS compliant Internet resource for thematic planning data hosted by Yukon Land Use Planning Council as part of the Yukon Planning Atlas project.

Location of Major Infrastructure, Resource, Oil and Gas Projects in Nunavut, Northwest Territories and Yukon. Data and maps for illustrative purposes only. Users understand that, although all efforts have been made to accurately and exhaustively compile, locate and classify projects, the authors do not guarantee the accuracy and/or the comprehensiveness of the data and assume no responsibility for errors or omissions. CanNor does not assume responsibility for errors or omissions. In support of this initiative, proponents and partners are encouraged to contact CanNor should they identify any errors or omissions.

Location of Major Infrastructure, Resource, Oil and Gas Projects in Nunavut, Northwest Territories and Yukon. Data and maps for illustrative purposes only.

Emplacement des grandes infrastructures, de ressources, projets pétroliers et gaziers au Nunavut, Territoires du Nord-Ouest et du Yukon. Les données et les cartes sont pour des fins d'illustration seulement.

The dataset consists of maps detailing the boundaries of the designatable units for conservation considerations as defined by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) for species of Pacific Salmon in British Columbia and the Yukon. Designatable units represent geographical areas that support groups of individuals with a unique genetic heritage makes them discrete and evolutionarily significant units of the taxonomic species, where “significant” means that the unit is important to the evolutionary legacy of the species as a whole and if lost is unlikely to be replaced through natural dispersion.

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.

Water wells dynamically extracted from various provincial and territorial databases (Yukon, British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Quebec, Nova Scotia, Newfoundland and Labrador. Also, Hydrostratigraphic units from 30 key aquifers in Canada. Puits dynamiquement extraits de bases de données provinciales et territoriales (Yukon, Colombie-Britannique,Alberta, Saskatchewan, Manitoba, Ontario, Québec, Nouvelle-Écosse et Terre-Neuve-et-Labrador). Aussi, Unités stratigraphiques de 30 aquifères clés du Canada

The Canadian long term satellite data record (LTDR) derived from 1-km resolution Advanced Very High Resolution Radiometer (AVHRR) data was produced by the Canada Center for Remote Sensing (CCRS). Processing included: geolocation, calibration, and compositing using Earth Observation Data Manager (Latifovic et al. 2005), cloud screening (Khlopenkov and Trishchenko, 2006), BRDF correction (Latifovic et. al., 2003), atmosphere and other corrections as described in Cihlar et. al. (2004). For temporal analysis of vegetation cross-sensor correction of Latifovic et al. (2012) is advised. Data collected by the AVHRR instrument on board the National Oceanic and Atmospheric Administration (NOAA) 9,11,14,16,17,18 and 19 satellites were used to generate Canada-wide 1-km 10-day AVHRR composites. Data are available starting in 1985. It is important to note that there are three types of AVHRR sensors: (i) AVHRR-1 flown onboard TIROS-N, NOAA-6, NOAA-8, and NOAA-10; (ii) AVHRR-2 flown onboard NOAA-7, NOAA-9, NOAA-11, NOAA-12, and NOAA-14; and (iii) AVHRR-3 currently operational onboard NOAA-15, NOAA-16, NOAA-17, NOAA-18 and NOAA-19. The AVHRR-1 has four channels, AVHRR-2 has five channels and the AVHRR-3 has six channels, although only five channels of AVHRR-3 can be operational at any one time. As such, channels 3A (1.6 m) and 3B (3.7 m) work interchangeably. The processing procedure was designed to minimize artefacts in AVHRR composite images. There are thirty six 10-day image composites per year. The following three processing levels are provided: P1) top of atmosphere reflectance and brightness temperature, P2) reflectance at surface and surface temperature and P3) reflectance at surface normalized to a common viewing geometry (BRDF normalization). The processing level P1 and P2 are provided for all 36 composites while level P3 is provided for 21 composites from April – October.