Wildfire Year/dNBR/Mask 1985-2015Wildfire change magnitude 85-15. Spectral change magnitude for wildfires that occurred from 1985 and 2015. The wildfire change magnitude included in this product is expressed via differenced Normalized Burn Ratio (dNBR), computed as the variation between the spectral values before and after the change event. This dataset is composed of three layers: (1) binary wildfire mask, (2) year of greatest wildfire disturbance, and (3) differenced Normalized Burn Ratio (dNBR) transformed for data storage efficiency to the range 0-200. The actual dNBR value is derived as follows: dNBR = value / 100. Higher dNBR values are related to higher burn severity. The information outcomes represent 30 years of wildfires in Canada's forests, derived from a single, consistent spatially-explicit data source in a fully automated manner. Time series of Landsat data with 30-m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by wildfire for the period 1985-2015 for Canada's 650 million hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. (Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution and time series change detection methods applied, as well as information on independent accuracy assessment of the data.Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., 2015. An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. (Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., 2015. Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. (Hermosilla et al. 2015b).Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Catch, effort, location (latitude, longitude), relative abundance indices, and associated biological data from groundfish multi-species bottom trawl surveys in West Coast Haida Gwaii.Introduction The West Coast Haida Gwaii (WCHG) synoptic bottom trawl survey was first conducted annually from 2006 to 2008 and has since been repeated every second year on even numbered years. The survey was not impacted by the COVID-19 pandemic. This survey is one of a set of long-term and coordinated surveys that together cover the continental shelf and upper slope of most of the British Columbia coast. The other surveys are the Queen Charlotte Sound (QCS) survey, the Hecate Strait (HS) survey, the West Coast Vancouver Island (WCVI) survey, and the Strait of Georgia (SOG) survey. The objectives of these surveys are to provide fishery independent abundance indices of all demersal fish species available to bottom trawling and to collect biological samples of selected species. The survey follows a random depth-stratified design and the sampling units are 2 km by 2 km blocks. The synoptic bottom trawl surveys are conducted by Fisheries and Oceans Canada (DFO) in collaboration with the Canadian Groundfish Research and Conservation Society (CGRCS), a non-profit society composed of participants in the British Columbia commercial groundfish trawl fishery. The Queen Charlotte Sound and West Coast Haida Gwaii surveys are conducted under collaborative agreements, with the CGRCS providing chartered commercial fishing vessels and field technicians, while DFO provides in-kind contributions for running the surveys including personnel and equipment. The Hecate Strait, West Coast Vancouver Island, and Strait of Georgia surveys are conducted by DFO and have typically taken place on a Canadian Coast Guard research vessel. Until 2016 this vessel was the CCGS W.E. Ricker. From 2021 onwards, this vessel was the CCGS Sir John Franklin. In years when a coast guard vessel has not been available, the Hecate Strait, West Coast Vancouver Island, and Strait of Georgia surveys have taken place on chartered industry vessels. Data from these surveys are also presented in the groundfish data synopsis report (Anderson et al. 2019).EffortThis table contains information about the survey trips and fishing events (trawl tows/sets) that are part of this survey series. Trip-level information includes the year the survey took place, a unique trip identifier, the vessel that conducted the survey, and the trip start and end dates (the dates the vessel was away from the dock conducting the survey). Set-level information includes the date, time, location, and depth that fishing took place, as well as information that can be used to calculate fishing effort (duration) and swept area. All successful fishing events are included, regardless of what was caught.CatchThis table contains the catch information from successful fishing events. Catches are identified to species or to the lowest taxonomic level possible. Most catches are weighed, but some are too small (“trace” amounts) or too large (e.g. very large Big Skate). The unique trip identifier and set number are included so that catches can be related to the fishing event information (including capture location).BiologyThis table contains the available biological data for catches which were sampled. Data may include any or all of length, sex, weight, age. Different length types are measured depending on the species. Age structures are collected when possible for species where validated aging methods exist and are archived until required for an assessment; therefore, all existing structures have not been aged at this time. The unique trip identifier and set number are included so that samples can be related to the fishing event and catch information.BiomassThis table contains relative biomass indices of species that have been captured in every survey of the time series. The coefficient of variation and bootstrapped 95% confidence intervals are provided for each index. The groundfish data synopsis report (Anderson et al. 2019) provides an explanation of how the relative biomass indices are derived. Note that we do not calculate a biomass index for the 2014 West Coast Haida Gwaii survey, as this survey was incomplete due to operational problems.

Growing degree days (GDDs) are used to estimate the growth and development of plants and insects during the growing season. Growing Degree Day are computed by subtracting a base value temperature from the mean daily temperature and are assigned a value of zero if negative. Base temperatures are a point below which development does not occur for the organism in question. Growing Degree Day products are created for base 0, 5, 10 and 15 degrees Celsius.GDD values are only accumulated during the Growing Season, April 1 through October 31.

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

Boundaries identifying similar behavioural ecotypes and sub-populations of Grizzly bears. This dataset contains versions from multiple years. From 2018 on, NatureServe conservation concern ranking categories (e.g., Very Low, Low, Moderate, High, Extreme Concern) supersede the pre-2018 population status categories (e.g., Viable, Threatened, Extirpated) contained in the field STATUS. NatureServe conservation concern ranking categories reflect population size and trend, genetic and demographic isolation, as well as threats to bears and their habitats. The NatureServe conservation concern ranking fields are named CONSERVATION_CONCERN_RANK and CONSERVATION_CONCERN_DESC. Please view the attached PDF file for a summary of changes to this dataset from 2012 onward. To download only the 2018 units, in the link below, select the "Export" tab, then select the "Provincial Layer Download" button: https://maps.gov.bc.ca/ess/hm/imap4m/?catalogLayers=7744,7745 Grizzly Bear Conservation Ranking results table is available here: https://catalogue.data.gov.bc.ca/dataset/e08876a1-3f9c-46bf-b69a-3d88de1da725 Grizzly Bear population estimates from various years are available here: https://catalogue.data.gov.bc.ca/dataset/2bf91935-9158-4f77-9c2c-4310480e6c29 Grizzly Bear reports are available here: https://www2.gov.bc.ca/gov/content/environment/plants-animals-ecosystems/wildlife/wildlife-conservation/grizzly-bear

Forest Total Aboveground Biomass 2015Total aboveground biomass. Individual tree total aboveground biomass is calculated using species-specific equations. In the measured ground plots, aboveground biomass per hectare is calculated by summing the values of all trees within a plot and dividing by the area of the plot. Aboveground biomass may be separated into various biomass components (e.g. stem, bark, branches, foliage) (units = t/ha). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. The shared products are based upon peer-reviewed science and relate aspects of forest structure including: (i) metrics calculated directly from the lidar point cloud with heights normalized to heights above the ground surface (e.g., canopy cover, height), and (ii) modelled inventory attributes, derived using an area-based approach generated by using co-located ground plot and ALS data (e.g., volume, biomass). Forest structure estimates were generated by combining information from lidar plots (Wulder et al. 2012) with Landsat pixel-based composites (White et al. 2014; Hermosilla et al. 2016) using a nearest neighbour imputation approach with a Random Forests-based distance metric. These products were generated for strategic-level forest monitoring information needs and are not intended to support operational-level forest management. All products have a spatial resolution of 30 m. For a detailed description of the data, methods applied, and accuracy assessment results see Matasci et al. (2018). When using this data, please cite as follows: Matasci, G., Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., Bolton, D.K., Tompalski, P., Bater, C.W., 2018b. Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots. Remote Sensing of Environment 216, 697-714. Matasci et al. 2018)Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

The National Rail Network (NRWN) is a geometric and attributive description of the Canadian rail network.The NRWN product consists of the features classes: Track Segment, Railway Crossing, Railway Station, Marker Post, Junction and Railway Structure. Descriptive attributes include amongst others: Track Classification, Track Name, Track Operator, Track User, Track Owner, Subdivision Name, Junction Type, Crossing Type, Level of Crossing, Warning System, Transport Canada Identifier, Station Name, Station Type, Station User, Structure Type.

Please note that a web service is currently under development and will be launched in winter 2026. Stay on the lookout!## #Avertissement :###### #Le broadcaster cannot guarantee the accuracy, precision, or completeness of the data nor can it be held responsible for the conclusions that arise from their use. This data has no legal value. ####The Geobase of the Quebec Hydrographic Network at High Resolution (GRHQ-HR) offers an up-to-date representation of the hydrographic network with very high precision (scale of 1/2,000). This repository, produced from lidar data, is offered by hydrographic division unit (UDH). The deployment of this geobase is carried out progressively by levels of completeness (NC). Ultimately, it will cover the territory of southern Quebec. During the deployment phase of the repository, [the Quebec Hydrographic Network Geobase (GRHQ)] (https://www.donneesquebec.ca/recherche/fr/dataset/grhq), the GRHQ-HR as well as [potential flow beds] (https://www.donneesquebec.ca/recherche/dataset/lits-d-ecoulements-potentiels-issus-du-lidar) from the lidar will be simultaneously available on Data Quebec for this portion of the territory.The GRHQ-HR includes a 3D linear geometric network, which represents the continuity and direction of flow in all types of aquatic entities (streams, lakes, wetlands, etc.). This network is created by modeling potential flow beds and completed by central flow lines (simplified representation of hydrographic surfaces in central lines). This geobase is part of a strategy to update the cartographic map of Quebec's hydrography. It was carried out in partnership with the Ministry of the Environment, the Fight against Climate Change, Wildlife and Parks (MELCCFP). # #Caractéristiques UDH completion levels##Each level of completeness characterizes the level of work, editing, validation, and descriptive content of the datasets. Thematic and toponymic data will enhance the datasets. ### #NC -1 (primary geometric network) ####* Potential and filamentary flow beds derived from hydrographic, oriented, and topological surfaces.* Priority level defined (allows network analyses).* Presence of certain basic attributes (sustainability, network connection, accumulation of flows, Strahler and Horton orders, distance from upstream, distance from downstream).* Linear reference system (road numbers, vertex M coordinates).* Hydrographic surfaces of the GRHQ on a scale of 1/20,000 (2D).* Presence of some toponyms as an attribute.* Hydrocoherent digital terrain models (GeoTIFF).* Flow accumulation matrices (GeoTIFF).* Flow direction matrices (GeoTIFF).### #NC -2 (enhanced geometric network) ####* NC-1 features.* Update of hydrographic surfaces by photogrammetry.* Correction of errors in the path of potential flow beds and update of downstream filamentaries.* Partial addition of thematic hydrographic data (dams, falls, reefs, islands, wetlands, rapids).* Lidar survey date index.* Topological nesting of matrices.* Update of hydrocoherent numerical terrain models.* Update of flow direction matrices.* Update of flow accumulation matrices.### #NC -3 (thematic bonus) ####* Characteristics of the NC-2.* Hydrographic themes completed (breakwaters, quays).* Addition of toponyms.### #NC -4 (improvement of toponymic content) ####* NC-3 features.* Continuity of toponymic data on geometries.* Addition of named entities.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The purpose of this dataset is to give an accurate representation of the boundaries of lands closed to hunting in Manitoba.The purpose of this dataset is to give an accurate representation of the boundaries of lands closed to hunting in Manitoba. These are defined as lands where hunting and trapping are either prohibited, or special restrictions are in place for certain species and areas are defined within the General Hunting Regulation (351/87), Moose Conservation Closure Regulation (122/2011), Hunting Seasons and Bag Limits Regulation (165/91), and Trapping of Wild Animals Regulation (245/90) of The Wildlife Act (C.C.S.M c. W130). Hunting and trapping prohibitions or restrictions are implemented in certain areas to ensure the conservation of species or enhance public safety. Fields included (Alias (Field Name): Field description) FID (OBJECTID): Sequential unique whole numbers that are automatically generated Id (Id): The number assigned to each restricted area (not currently being used) Name (Name): Name given to the restricted area Restrictions (Restrictions): Description of the restriction applied to the restricted area Director of Surveys Plan (D_of_S): Director of Surveys Plan number which pertains to the boundary of the restricted area Regulation (Regulation): The regulation title defined in The Wildlife Act Shape_Area (Shape_Area): Area of the feature in internal units squared Shape_Length (Shape_Length): Length of the feature in internal units

Manitoba market hog prices and United States (U.S.) iso-wean and feeder pig prices shown weekly and monthly for current and previous years.This table contains weekly and monthly prices paid for market hogs in Manitoba and iso-wean and feeder pigs in United States (U.S.) in current and previous years, as well as average prices for five and 10 previous years.  For hog price report definitions and calculations, click here.  Manitoba market hog prices are collected from major processors in Manitoba, compiled and released weekly by Manitoba Agriculture and Resource Development (ARD). Manitoba market hog prices are weighted by the volume of hogs processed, and averaged monthly. United States (U.S.) iso-wean and feeder pig prices are sourced from the United States Department of Agriculture (USDA) and presented in Canadian dollars (C$) using the Bank of Canada exchange rate. Monthly U.S. iso-wean and feeder pig prices are a simple average of the weekly U.S. total composite weighted average prices. Average five and 10-year prices are calculated as simple averages of weekly or monthly prices. Fields included (Alias (Field name): Field description.) Period (Period): period of time to be presented on charts from the selection of Monthly and Weekly; ; PeriodNo (PeriodNo): serial number of period (1-12 for monthly presentation, 1-52 for weekly presentation); Hog category (Hog category): category of animals from the selection of U.S. feeder pigs, U.S. iso-wean pigs, Manitoba market hogs; Previous year price (Previous): animal price in corresponding period of previous year*; Current year price (Current): animal price in corresponding period of current year*; 5-year average price (Average5): animal price in corresponding period averaged over last 5 years (excluding current year)*; 10-year average price  (Average10): animal price in corresponding period averaged over last 10 years (excluding current year)*. *(C$ per head for U.S. feeder pigs and U.S. iso-wean pigs, C$ per 100 kg for Manitoba market hogs)