Weather Elements on Grid (WEonG) based on the High Resolution Deterministic Prediction System (HRDPS) is a post-processing system designed to compute the weather elements required by different forecast programs (public, marine, aviation, air quality, etc.). This system amalgamates numerical and post-processed data using various diagnostic approaches. Hourly concepts are produced from different algorithms using outputs from the pan-Canadian High Resolution Deterministic Prediction System (HRDPS-NAT).

List of locations of B.C. public and B.C. private degree granting and non-B.C. degree granting post-secondary institutions.

The National Parks and National Park Reserves of Canada Legislative Boundaries web service includes the following lands: 1) National Parks of Canada as defined in Schedule 1 of the Canada National Parks Act, 2) National Park Reserves of Canada as defined in Schedule 2 of the Canada National Parks Act, 3) Rouge National Urban Park as defined in the Rouge National Urban Park Act and 4) Saguenay–St. Lawrence Marine Park as defined in the Saguenay-St. Lawrence Marine Park Act.The Data available for download is the former National Framework Canada Lands Administrative Boundaries Level 1 product. There are some attribute differences between the data available for download and the web service; however both contain the same underlying data. Please refer to the Supporting Documents for additional information on the National Framework Canada Lands Administrative Boundaries Level 1 dataset. Work is under way to align these two data products. As well, the Comprehensive Claims Settlement Areas have been removed from this dataset, but can be obtained from the Post-1975 Treaties (Modern Treaties) dataset produced by Indigenous and Northern Affairs Canada.

The Modern treaties (formerly known as the Post-1975 treaties) dataset contains geographic boundaries as well as basic attribute data representing signed agreements that were negotiated between Indigenous groups, the Government of Canada, and provincial and territorial governments after 1975. These boundaries represent the areas of Canada where Indigenous land rights and title have not been addressed by treaty or through other legal means. These boundaries represent the final result of a negotiated First Nation’s claimed area. These boundaries are usually not surveyed but help to delineate the geographic extent of the rights of Indigenous beneficiaries defined within the agreement. The Modern treaties dataset includes: 1) Overall Treaty Area (OTA) which is the broad area to which the agreement applies, often composed of the sum of the specific geographies defined within the treaty. 2) Treaty Settlement Lands that is wholly Indigenous-owned and forms part of the “land and cash” settlements that are integral to the treaty. This category belongs to the Department of Natural Resources Canada and can be found on the Open data website as ‘‘Aboriginal Lands’’ classified as ‘‘Land Claim’’. 3) Treaty-Specified Rights Areas which category pertains to areas (lands or waters) where specific rights, activities or responsibilities apply pursuant to the treaty. 4) Other Treaty-related Geography is the catch-all category for any remaining geographies that do not fit within the aforementioned categories but do form part of the OTA, such as lands or marine areas designated for conservation or for specific projects.For more information about Modern treaties, visit https://www.rcaanc-cirnac.gc.ca/eng/1100100028574/1529354437231#chp4. The Modern treaties dataset is one of multiple datasets representing treaties and agreements between the Crown and Indigenous peoples. The Crown-Indigenous treaties and agreements geospatial datasets represent the geographic boundaries of the solemn agreements between the Crown and Indigenous peoples that set out promises, obligations and benefits for parties. The following datasets are also available: 1) The Historic treaties (formerly known as the Pre-1975 treaties) dataset, which represents most signed treaties that were negotiated between Indigenous peoples and the Crown between 1725 and 1929.2) The Indigenous agreements dataset, which represents established protocols in place for consultation processes, self-government agreements, and other signed agreements between Indigenous groups and the Crown which do not fall into the aforementioned categories.The Modern treaties dataset is Crown-Indigenous Relations and Northern Affairs Canada (CIRNAC) and Indigenous Services Canada (ISC)’s primary source for Modern treaties geographic boundaries on maps.This dataset can also be viewed in the Aboriginal and Treaty Rights Information System (ATRIS). This web-based system provides access to information to inform governments, industry and other interested parties in determining their consultation obligations and in carrying out their consultation research.For more information, visit https://www.rcaanc-cirnac.gc.ca/eng/1100100014686/1609421785838.

This layer is the current fire year burn severity classification for large fires (greater than 100 ha). Burn severity mapping is conducted using best available pre- and post-fire satellite multispectral imagery acquired by the MultiSpectral Instrument (MSI) aboard the Sentinel-2 satellite or the Operational Land Imager (OLI) sensor aboard the Landsat-8 and 9 satellites. Every attempt is made to use cloud, smoke, shadow and snow-free imagery that was acquired prior to September 30th. However, in late fire seasons imagery acquired after September 30th may be used. This layer is considered an interim product for the 1-year-later burn severity dataset (WHSE_FOREST_VEGETATION.VEG_BURN_SEVERITY_SP). Mapping conducted during the following growing season benefits from greater post-fire image availability and is expected to be more representative of tree mortality. #### Methodology: • Select suitable pre- and post-fire imagery or create a cloud/snow/smoke-free composite from multiple images scenes • Calculate normalized burn severity ratio (NBR) for pre- and post-fire images • Calculate difference NBR (dNBR) where dNBR = pre NBR – post NBR • Apply a scaling equation (dNBR_scaled = dNBR*1000 + 275)/5) • Apply BARC thresholds (76, 110, 187) to create a 4-class image (unburned, low severity, medium severity, and high severity) • Mask out water bodies using a satellite-derived water layer • Apply region-based filters to reduce noise • Confirm burn severity analysis results through visual quality control • Produce a vector dataset and apply Euclidian distance smoothing

Land authorizations representing the road right of way for road activities. The spatial data includes polygon data for approved and post-construction road rights of way collected on or after October 30, 2006. This dataset is updated nightly.

Land authorizations for areas on which well or facility activities can occur. This dataset contains spatial data collected on or after October 30, 2006. The spatial data includes approved and post-construction land areas associated with well or facility activities. This dataset is updated nightly.

Post-disturbance forest recovery data for Canada's forested ecosystems, representing a total area of ~650 million ha, captures the return of forests following wildfire and harvest that occurred between 1986 and 2012. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). These spatially-explicit outputs represent the rate of spectral recovery: the rate at which a pixel returns to 80% of its pre-disturbance value (White et al. 2017) within the observation period (1985-2017) using the Y2R or Years-to-Recovery metric derived from Landsat times series data. Baseline rates of spectral recovery (Y2R) were defined for each of Canada's 12 forested ecozones. These baselines were then used to identify spatial clusters of recovering pixels on the landscape where Y2R were either significantly faster or slower than their ecozonal baseline. Finally, areas that were disturbed by wildfire and harvest (1986-2012), but which had not recovered by the end of the observation period (2017) are also provided. Note that these areas are still recovering, but they had not yet recovered according to our metric of spectral recovery, by the end of the time series in 2017. For an overview of the methods, the validation of the Y2R metric, and interpretation of the derived trends, see White et al. (2022) and White et al. (2017).White, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., 2022. Mapping, validating, and interpreting spatio-temporal trends in post-disturbance forest recovery. Remote Sensing of Environment, 271, 112904. https://doi.org/10.1016/j.rse.2022.112904 ( White et al. 2022)White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C., Hobart, G.W. 2017. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment, 194, pp. 303-321. DOI: https://doi.org/10.1016/j.rse.2017.03.035 .( White et al. 2017)

This project was completed by the Shellfish Section in the Newfoundland and Labrador Science Branch of Fisheries and Oceans Canada (DFO), in collaboration with industry partners. The Coastal Environmental Baseline program supported the Placentia Bay portion of project work for an ongoing industry-DFO collaborative post-season trap survey for Snow Crab that was initiated in 2003 and has occurred each year. This survey is conducted by Snow Crab harvesters accompanied by at-sea observers and takes place in NAFO Divisions 2J3KLNOP4R. Historically the survey focused on commercial fishing grounds but began transitioning to a partly random stratified design in 2017. Since 2018, approximately 50% of survey stations are randomly allocated while 50% remain fixed. At each station, six (for inshore stations) or ten (for offshore stations) commercial traps are set in a fleet. To gather data on non-commercial sized Snow Crab, including females, many fleets also include one small-mesh trap. The coverage of small-mesh traps has been expanding in recent years with the aim of one small-mesh trap for every station in the coming years. Biological sampling is undertaken on at least one commercial trap and the small-mesh trap at each station. The data from this survey is incorporated into the annual stock assessment for Snow Crab in the Newfoundland and Labrador region. This record contains trap locations for Placentia Bay, and information on the types of data collected. More detailed information can be found in Pantin et al. (2022).https://publications.gc.ca/collections/collection_2023/mpo-dfo/fs70-5/Fs70-5-2022-076-eng.pdf

This dataset provides the location of Yukon's education facilities ranging from elementary to post-seondary education. The data also includes contact information and general programming information about each facility.Distributed from GeoYukon by the Government of Yukon. Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:%20geomatics.help@yukon.ca)