The "Starter Kits" of the Canadian Geospatial Data Infrastructure (CGDI) are curated bundles of geospatial data delivered as a service. These kits are the result of a user needs assessment commissioned by Natural Resources Canada (NRCan), with a primary focus on addressing the specific requirements of Indigenous Peoples. Within these kits, you'll discover a selection of data provided as a service from a collection of over 71,000 datasets falling under the "Nature and Environment" category sourced from CGDI's Federal and Provincial/Territorial partners. These Starter Kits have been thoughtfully crafted into four thematic or geographic areas of Canada:a) British Columbia,b) Northwest Territories,c) Climate Change across Canada,d) And Water Resources across Canada.Each of these kits represents diverse areas and data categories, offering new users a compact, comprehensive, and user-friendly gateway to explore a wide array of information provided by the CGDI.

This layer contains polygon features that represent geological units in New Brunswick. The associated Bedrock Geology Relate Table contains details about each map unit, including: a brief legend description, Group name, Formation name, and rock age. This layer is the result of nearly 50 years of bedrock mapping and it continues to change as new interpretations are made and more data is collected through field work and analysis.

The Canada Centre for Mapping and Earth Observation (CCMEO) has created a 30m resolution radar mosaic of Canada's landmass from the RADARSAT Constellation Mission (RCM). This product highlights different types of radar interaction with the surface, which can assist the interpretation and study of land cover on a national scale. The national mosaic is made up of 3222 RCM images acquired between August 2023 and February 2024. (Credit: RADARSAT Constellation Mission imagery © Government of Canada [2024]. RADARSAT is an official mark of the CSA.)

The maps show a multiyear ground deformation rate caused by small-scale deformation processes in Canada, measured in meters per year. Horizontal-east and vertical deformation components were computed from data acquired on ascending and descending orbits. This horizontal-east **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

“Biomass Inventory Mapping and Analysis – Business Data” provides a number of datasets related to the yield and production of residues from the agricultural and forestry industry, agricultural crops, and municipal solid wastes across Canada. The datasets contain agricultural residue production information (i.e., straw or stover) for barley, wheat, flax, oats and corn, and crop production information for barley, wheat, flax, oats, corn, canola and soybean. They also include information about amounts of straw required for cattle bedding and feeding, the type of tillage used in an area, and the amount of residue needed for soil conservation purposes. Datasets in the series provide the yield, production and other information for the median year and 1-in-10 year and 1-in-20 year lows. The forestry inventory dataset provides information about the location and quantity of residues from the forestry industry, as well as urban wood waste and potential sites and productivity of plantations of fast-growing trees that are grown as feedstock. Forestry residues include material left at the roadside after harvesting and excess and waste materials from mills. The municipal solid waste inventory dataset provides information about the approximate location and quantity of different types of municipal solid wastes, such as organics (including food and yard), paper and total. A transportation network dataset and datasets that are used to calculate cost to harvest and transport biomass are also included in this series.

The maps show a multiyear ground deformation rate caused by small-scale deformation processes in Canada, measured in meters per year. Horizontal-east and vertical deformation components were computed from data acquired on ascending and descending orbits. This horizontal-east **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

The maps show a multiyear ground deformation rate caused by small-scale deformation processes in Canada, measured in meters per year. Horizontal-east and vertical deformation components were computed from data acquired on ascending and descending orbits. This horizontal-east **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

The maps show a multiyear ground deformation rate caused by small-scale deformation processes in Canada, measured in meters per year. Horizontal-east and vertical deformation components were computed from data acquired on ascending and descending orbits. This horizontal-east **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

The maps show a multiyear ground deformation rate caused by small-scale deformation processes in Canada, measured in meters per year. Horizontal-east and vertical deformation components were computed from data acquired on ascending and descending orbits. This horizontal-east **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

Between 2017 and 2024, underwater imaging sampling campaigns were conducted by Fisheries and Oceans Canada across a broad area of the shallow coastal zone of the St. Lawrence Estuary and Gulf. The sampling targeted the lower intertidal and subtidal zones, to a maximum depth of approximately 10 m, with an emphasis on eelgrass beds and macroalgae. These targeted surveys were primarily intended to produce ground-truth data for the mapping of estuarine and marine macrophytes of the Québec maritime region (Provencher-Nolet et al., 2025), supporting oil spill preparedness and response activities.This dataset summarizes information generated from the analysis of underwater video footage collected at 3,179 sampling stations using small boats equipped with a pole-mounted camera system, as described in Grégoire et al. (2025). The dataset documents multiple characteristics of coastal ecosystems, including the cover of erect vegetation, vegetation assemblages, dominant and minor vegetation, substrates, fauna, as well as the presence of encrusting algae, for each sampling station. The different attributes recorded during video analysis, along with certain identification criteria, are presented in the visual dictionary of Grégoire et al. (2022).