This dataset uses RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) satellite images to identify open water regions within ice-covered rivers during winter, with the aim to assess hydrokinetic resources near remote communities reliant on diesel fuel for electricity generation. The data is processed with the HyRASS, a machine learning-based SAR image processing and classification algorithm.Disclaimer:This dataset was designed to identify open water regions within ice-covered rivers for assessing hydrokinetic resources near remote communities reliant on diesel fuel for electricity generation and is subject to the following limitations: • This dataset was derived from RADARSAT Constellation Mission (RCM) Synthetic Aperture Radar (SAR) satellite images. While these images are generally reliable, they are subject to inherent limitations, including resolution constraints, potential distortion, and occasional inaccuracies in real-time conditions capture. • The HyRASS algorithm is designed to pinpoint open water areas using satellite images, with a particular emphasis on RCM quad polarization (QP) imagery. This specialization means that its effectiveness depends on the accessibility of this specific type of imagery. Consequently, the data it produces might not cover a broad spectrum of time periods. For more reliable results, it's essential to classify areas more regularly, ensuring that detected open water regions are consistent over time.This dataset is intended for preliminary assessment and should not be the sole basis for making critical decisions or investments related to hydrokinetic energy projects. Further validation and in-depth analysis are strongly recommended, and users should conduct their own due diligence and additional research to verify the data accuracy and relevance for specific applications. By accessing and using this dataset, users acknowledge and accept these disclaimers. The providers of this dataset explicitly absolve themselves of any responsibility or liability for any consequences arising from the use, reliance upon, or interpretation of this dataset. Users are advised that their use of the dataset is at their own risk, and they assume full responsibility for any actions or decisions made based on the information contained therein. This disclaimer is in accordance with applicable laws and regulations, and by accessing or utilizing the dataset, users agree to release the providers of this dataset from any legal claims, damages, or liabilities that may arise from such use.

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 national map of Canadian Fire Behaviour Prediction (FBP) Fuel Types (FT) developed from public data sources. The resolution of the raster grid is 30m, classified from the Spatialized Canadian National Forest Inventory (SCANFI) dataset, ecozones of Canada, and the National Burned Area Composite (NBAC). The purpose of the dataset is to characterize Canadian forests into fuel types for use in Fire Behaviour Prediction calculations as well as for situational awareness of national fire potential.

Zero Emission Vehicle Infrastructure Program (ZEVIP) and Electric Vehicle and Alternative Fuel Infrastructure Deployment Initiative (EVAFIDI) qualitative, quantitative, and geographic data set derived from the program database. This data defines the project number, the number of chargers, the name of the promoter, the type of connector, the address, the city, the province, the postal code, the geographical coordinates, the status, the opening date, and the type of contribution agreement for each project funded by the program.The Canada Infrastructure Bank’s (CIB) Charging and Hydrogen Refuelling Infrastructure Initiative (CHRI) aims to reduce transportation sector greenhouse gas emissions by accelerating the private sector’s rollout of large-scale ZEV chargers and hydrogen refuelling stations, helping to spur the market for private investment.Through this initiative, the CIB has dedicated a minimum of $500 million to support the federal government’s goals as part of Canada’s 2030 Emissions Reduction Plan. Technology funding current to April 1 2025.

This data set shows utility points that provide services for: * power * water * communications * heating fuel They include: * fibre optic stations * hydro stations * lock pumping stations This product requires the use of geographic information system (GIS) software.

The purpose of the Licence Area feature is to record areas where a licencee holds a timber resources licence, a woodlot licence or a fuel wood licence.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

This data set shows utility lines that provide services for: * power * water * communications * heating fuel They include: * communication lines/submerged communication lines * hydro lines/submerged hydro lines * natural gas pipelines/submerged natural gas pipelines * water pipelines/submerged water pipelines * unknown pipelines * unknown transmission lines This product requires the use of geographic information system (GIS) software.

Fire management zones help guide how wildfires are prioritized and managed and show where wildfires may be used to achieve ecological objectives. Zones are based on relatively constant factors, such as the level of human use or development and the presence of reliable fuel breaks.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)

Offshore Oil and Gias exporation Potential

The Remote Communities Energy Database (RCED) is a tool that aims to collect and show pertinent information about the generation and use of electricity and other energy sources for all remote communities of Canada. This data is collected from a variety sources, including Statistics Canada, Provincial and Territorial Governments, utilities, public reports and communities.The term “remote community” refers to any community not currently connected to the North American electrical grid nor to the piped natural gas network; and which is a permanent or long-term (five years or more) settlement with at least 10 dwellings.Disclaimer: Natural Resources Canada (NRCan) accepts no responsibility or liability for any errors, inaccuracies and/or omissions in the Remote Communities Energy Database (RCED). The content of the RCED is a compilation of data obtained from many sources and the data is subject to change without notice. Neither does NRCan warrant or guarantee that the information is accurate, complete or current at all times. In no event will NRCan or the Government of Canada and its employees be liable or responsible for any damages resulting from any such errors, inaccuracies or omissions nor will they be liable or responsible for any lost profits, loss of revenue or earnings, claims by third parties or for any economic, indirect, special, incidental, consequential or exemplary damage including but not limited to any demands or causes of action in contract, tort or otherwise including any liability for negligence.