The Canada Nature Fund for Aquatic Species at Risk (CNFASAR) is a contribution program that focuses on providing funding for recovery and threat mitigation activities in nine priority places and to address two marine threats to aquatic species at risk. The Priority Places and Marine Threats layer supports CNFASAR by delineating the location of the places and threats.The Canada Nature Fund for Aquatic Species at Risk (CNFASAR) supports applicants in the design and delivery of stewardship projects. These projects support the recovery and protection of aquatic species at risk. DFO has identified 2 priority marine threats and 9 priority places as the focus for projects funded by CNFASAR, these areas are included in this dataset.

Feature point layer showing locations of community kitchens available for rent in ManitobaThis feature point layer shows locations of community kitchens available for rent in Manitoba. Each kitchen has a Food Service Establishment permit issued by Manitoba Health, and is a suitable facility to produce value-added food products for sale. For more information, visit Manitoba Agriculture. This layer is used in the Manitoba Commercial Community Kitchens map and the Commercial Community Kitchens in Manitoba application. Fields included [Alias (Field Name): Field description] UID (UID): Unique identifier for the kitchen Operating (Operating): Indicates whether or not the kitchen is currently in operation Facility Name (Facility_Name): Name of the kitchen Region (Region): Economic region in which the kitchen is located Address (Address): Physical address of the kitchen City or Town (City_or_Town): City or town in which the kitchen is located Phone (Phone): Phone number for the kitchen Website (Website): Website link for the kitchen Equipment (Equipment): List of available equipment in the kitchen Contact (Contact): Contact person for the kitchen Contact Email (Contact_Email): Email address of contact person for the kitchen Contact Phone (Contact_Phone): Phone number of contact person for the kitchen Secondary Contact (Secondary_Contact): Secondary contact person for the kitchen Secondary Contact Email (Secondary_Contact_Email): Email address of secondary contact person for the kitchen Secondary Contact Phone (Secondary_Contact_Phone): Phone number of secondary contact person for the kitchen Latitude (Latitude): Latitudinal coordinates of the representative centre of the feature in decimal degrees Longitude (Longitude): Longitudinal coordinates of the representative centre of the feature in decimal degrees

Data provided shows grants and contributions provided to Canadian firms by National Research Council (NRC) and its Industrial Research Assistance Program (IRAP) between April 1, 2018 and March 31, 2019.

Forest Percentage Above 2m 2015Percentage of first returns above 2 m (%). Represents canopy cover. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). 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

Canada's National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 106 km2 of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data. We used the k nearest neighbours (kNN) method with 26 geospatial data layers including MODIS spectral data and climatic and topographic variables to produce maps of 127 forest attributes at a 250 × 250 m resolution. The stand-level attributes include land cover, structure, and tree species relative abundance. In this article, we report only on total live aboveground tree biomass, with all other attributes covered in the supplementary data (http://nrcresearchpress.com/doi/suppl/10.1139/cjfr-2013-0401). In general, deviations in predicted pixel-level values from those in a PP validation set are greater in mountainous regions and in areas with either low biomass or sparse PP sampling. Predicted pixel-level values are overestimated at small observed values and underestimated at large ones. Accuracy measures are improved through the spatial aggregation of pixels to 1 km2 and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org)Collection:- **[Canada's National Forest Inventory (NFI) 2006](https://open.canada.ca/data/en/dataset/e2fadaeb-3106-4111-9d1c-f9791d83fbf4)**

A National Forest Fire Behaviour Prediction (FBP) Fuel Type (FT) layer, representing fuel types as described in the Canadian Forest Fire Danger Rating System (CFFDRS) Canada-wide. This data is developed through the Spatialized Canadian National Forest Inventory (SCANFI) dataset, specifically the updated SCANFI version 2.0. The Fuel Type layer is produced at variable resolution to best meet the needs of users: 30m (default) and 100m (ideal for fire growth modelling).The purpose of this dataset is to characterize Canadian forests into Fuel Types for use in various applications, including wildland fire management, research, fuel management, and more. This layer is primarily developed to support national scale applications and uses but can be utilized for localized landbases and adapted as required.This data represents the most up-to-date national product and is updated annually prior to the start of the fire season to incorporate burned area and additional data from the previous year. This data will be updated annually and published online by April 30th of each year.Note: In this product Slash fuel types (S-1, S-2, and S-3) are not represented. Conifer Plantation (C-6) is not represented. Raster Grid Value 13 represents vegetated fuels without an effective match to an existing FBP Fuel Type under this ruleset. Grid Value 11 (corresponding to D-1 Leafless Aspen) is assumed to represent true Deciduous fuels as described in the FBP system.

A Rest Area is a developed roadside area for the use of the traveling public which must contain a washroom, and often has litter receptacles, picnic tables and other facilities. It is a Point feature

Canada's National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 106 km2 of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data. We used the k nearest neighbours (kNN) method with 26 geospatial data layers including MODIS spectral data and climatic and topographic variables to produce maps of 127 forest attributes at a 250 × 250 m resolution. The stand-level attributes include land cover, structure, and tree species relative abundance. In this article, we report only on total live aboveground tree biomass, with all other attributes covered in the supplementary data (http://nrcresearchpress.com/doi/suppl/10.1139/cjfr-2013-0401). In general, deviations in predicted pixel-level values from those in a PP validation set are greater in mountainous regions and in areas with either low biomass or sparse PP sampling. Predicted pixel-level values are overestimated at small observed values and underestimated at large ones. Accuracy measures are improved through the spatial aggregation of pixels to 1 km2 and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org)Collection:- **[Canada's National Forest Inventory (NFI) 2006](https://open.canada.ca/data/en/dataset/e2fadaeb-3106-4111-9d1c-f9791d83fbf4)**

Data provided shows grants and contributions provided to Canadian firms by National Research Council (NRC) and its Industrial Research Assistance Program (IRAP) between April 1, 2024 and March 31, 2025.

Forest 95th Percentile Elevation(Ht) 201595th percentile of first returns height (m). Products relating the structure of Canada's forested ecosystems have been generated and made openly accessible. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). 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