Displays the levels of escalating enforcement applied by health officers to enforce the Manitoba Food and Food Handling Establishment Regulations when food safety violations are not corrected in the prescribed period of timeThis table displays the frequency in which health officers applied escalating levels of enforcement to food processors who did not correct food safety violations in the prescribed amount of time indicated in the inspection. Food processors are given a period of time to correct food safety violations based on the associated risk to food safety. Escalating enforcement is only applied if the violation is not corrected in the prescribed period of time. This table was created by the Food Safety and Inspection Branch - Agriculture and Resource Development department.Field Names (Field Alias): Field description. Period (Period):The period for which the data was collected. Either quarterly or yearly. Year (Year): The specific year of the previously mentioned data collection period. Date (Date): The dates of the calendar year in which the data was collected during a period. Enforcement_Type (Enforcement Type): The individual levels of escalating enforcement applied by health officers. The values for this field are "Warning letter", "Verbal warning", "Offence notice issued", "Closure orders issued", "Suspensions", "Products seized and destroyed", "Products seized and held". Total (Total): the number of occurrences a level of escalating enforcement was applied in a period.

High-resolution map of leading tree species distribution for Canada’s forested ecosystems (2019). Leading tree species map produced from a 2019 Landsat image composite, geographic and climate data, elevation derivatives, and remote sensing derived phenology following the framework described in Hermosilla et al. (2022). Regional classification models were generated based on Canada’s National Forest Inventory using a 150x150 km tiling system. The leading tree species are defined by representing the most voted tree species from the Random Forests classification models (i.e. the class with the highest class membership probability).The data represents leading tree species of Canada's forested ecosystems in 2019. An image compositing window of August 1 ± 30 days was used to generate the best-available-pixel (BAP) image composites utilized as source data for the classification.The science and methods developed to generate the information outcomes shown here, that track and characterize the history of Canada’s forests, were led by Canadian Forest Service of Natural Resources Canada, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS), partnered with the University of British Columbia, augmented by processing capacity from Digital Research Alliance of Canada.For an overview on the data, image processing, and methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2022) https://doi.org/10.1016/j.rse.2022.113276When using this data, please cite as: Hermosilla, T., Bastyr, A., Coops, N.C., White, J.C., Wulder, M.A., 2022. Mapping the presence and distribution of tree species in Canada’s forested ecosystems. Remote Sensing of Environment 282, 113276.

TA_CROWN_DVLOPMNT_AGRMNTS_SVW contains the spatial representation (polygon) of active and applied for Land Act Development Agreements. Development Agreements allow for use of Crown Land for development with conditions for future purchase of base lands or tenure of property. The view was created to provide a simplified presentation of this single tenure type from the disposition information in the Tantalis operational system. The same content could be derived from the TA_CROWN_TENURES_SVW by filtering to this tenure type only

Significant Benthic Areas are defined in DFO's Ecological Risk Assessment Framework (ERAF) as "significant areas of cold-water corals and sponge dominated communities", where significance is determined "through guidance provided by DFO-lead processes based on current knowledge of such species, communities and ecosystems". Here we provide maps of the location of significant concentrations of corals and sponges on the east coast of Canada produced through quantitative analyses of research vessel trawl survey data, supplemented with other data sources where available. We have conducted those analyses following a bio-regionalization approach in order to facilitate modelling of similar species, given that many of the multispecies surveys do not record coral and sponge catch at species level resolution. The taxa analyzed are sponges (Porifera), large and small gorgonian corals (Alcyonacea), and sea pens (Pennatulacea). We applied kernel density estimation (KDE) to create a modelled biomass surface for each of those taxa, and applied an aerial expansion method to identify significant concentrations, following an approach first applied in 2010 to this region. We compared our results to those obtained previously. KDE uses only geo-referenced biomass data to identify "hot spots". The borders of the areas so identified can be refined using knowledge of null catches and species distribution models that predict species presence-absence and/or biomass, both incorporating environmental data.

TA_CROWN_INCLUSIONS_SVW contains the spatial representation (polygon) of active and applied for Crown Land Inclusions. Inclusions are a mechanism by which an interest holder can extend for inclusion their holdings based on statutory provisions within the Land and Land Title Acts. The view was created to provide a simplified presentation of this single tenure type from the disposition information in the Tantalis operational system. The same content could be derived from the TA_CROWN_TENURES_SVW by filtering to this tenure type only

TA_CROWN_INVENTORY_SVW contains the spatial representation (polygon) of active and applied for Crown Land Inventory Dispositions. Inventories are lands identified for review to determine the availability to market. The view was created to provide a simplified presentation of this single tenure type from the disposition information in the Tantalis operational system. The same content could be derived from the TA_CROWN_TENURES_SVW by filtering to this tenure type only

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.

TA_CROWN_OPERATING_AGRMNTS_SVW contains the spatial representation (polygon) of active and applied for Crown Land Operating Agreements. Operating agreements provide for use of Crown Land for operation/development but do not provide for future purchasing of land. The view was created to provide a simplified presentation of this single tenure type from the disposition information in the Tantalis operational system. The same content could be derived from the TA_CROWN_TENURES_SVW by filtering to this tenure type only

TA_CROWN_LICENSES_SVW contains the spatial representation (polygon) of active and applied for Land Act Licences. Land Act Licences (chapter 245) is not registerable, does not require a survey, possesses fewer rights than a lease and conveys non-exclusive use. The view was created to provide a simplified presentation of this single tenure type from the disposition information in the Tantalis operational system. The same content could be derived from the TA_CROWN_TENURES_SVW by filtering to this tenure type only

The Canadian Wind Turbine Database contains the geographic location and key technology details for wind turbines installed in Canada.Latest update includes: Wild Rose 2, commissioned on Sept. 16, 2025This dataset was jointly compiled by researchers at CanmetENERGY-Ottawa and by the Centre for Applied Business Research in Energy and the Environment at the University of Alberta, under contract from Natural Resources Canada. Additional contributions were made by the Department of Civil & Mineral Engineering at the University of Toronto.Note that total project capacity was sourced from publicly available information, and may not match the sum of individual turbine rated capacity due to de-rating and other factors. The turbine numbering scheme adopted for this database is not intended to match the developer’s asset numbering.This database will be updated in the future. If you are aware of any errors, and would like to provide additional information, or for general inquiries, please use the contact email address listed on this page.