This collection is a legacy product that is no longer supported. It may not meet current government standards.This inventory presents chronologically the satellite images acquired, orthorectified and published over time by Natural Resources Canada. It is composed of imagery from the Landsat7 (1999-2003) and RADARSAT-1 (2001-2002) satellites, as well as the CanImage by-product and the control points used to process the images.Landsat7 Orthorectified Imagery: The orthoimage dataset is a complete set of cloud-free (less than 10%) orthoimages covering the Canadian landmass and created with the most accurate control data available at the time of creation.RADARSAT-1 Orthorectified Imagery: The 5 RADARSAT-1 images (processed and distributed by RADARSAT International (RSI) complete the landsat 7 orthoimagery coverage. They are stored as raster data produced from SAR Standard 7 (S7) beam mode with a pixel size of 15 m. They have been produced in accordance with NAD83 (North American Datum of 1983) using the Universal Transverse Mercator (UTM) projection. RADARSAT-1 orthoimagery were produced with the 1:250 000 Canadian Digital Elevation Data (CDED) and photogrammetric control points generated from the Aerial Survey Data Base (ASDB).CanImage -Landsat7 Orthoimages of Canada,1:50 000: CanImage is a raster image containing information from Landsat7 orthoimages that have been resampled and based on the National Topographic System (NTS) at the 1:50 000 scale in the UTM projection. The product is distributed in datasets in GeoTIFF format. The resolution of this product is 15 metres.Landsat7 Imagery Control Points: the control points were used for the geometric correction of Landsat7 satellite imagery. They can also be used to correct vector data and for simultaneously displaying data from several sources prepared at different scales or resolutions.

This data set represents the digital Mineral Resource potential of the Province of Saskatchewan.This dataset represents the mineral resource potential of Saskatchewan. Methodologies used to determine a ranking system of low to high mineral potential areas. 6 being high mineral potential while 1 being low. The data was created as a file geodatabase feature class and output for public distribution. **Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse.  They are therefore identical and share the same refresh schedule. 

**Attention: there is a new version of this product (SCANFI v2)**SCANFI v2 can be found here: https://doi.org/10.23687/07653869-f303-46c2-a04e-9ab479b73cbfThis data publication contains a set of 30m resolution raster files representing 2020 Canadian wall-to-wall maps of broad land cover type, forest canopy height, degree of crown closure and aboveground tree biomass, along with species composition of several major tree species. The Spatialized CAnadian National Forest Inventory data product (SCANFI) was developed using the newly updated National Forest Inventory photo-plot dataset, which consists of a regular sample grid of photo-interpreted high-resolution imagery covering all of Canada’s non-arctic landmass. SCANFI was produced using temporally harmonized summer and winter Landsat spectral imagery along with hundreds of tile-level regional models based on a novel k-nearest neighbours and random forest imputation method. A full description of all methods and validation analyses can be found in Guindon et al. (2024). As the Arctic ecozones are outside NFI’s covered areas, the vegetation attributes in these regions were predicted using a single random forest model. The vegetation attributes in these arctic areas could not be rigorously validated. The raster file « SCANFI_aux_arcticExtrapolationArea.tif » identifies these zones.SCANFI is not meant to replace nor ignore provincial inventories which could include better and more regularly updated inputs, training data and local knowledge. Instead, SCANFI was developed to provide a current, spatially-explicit estimate of forest attributes, using a consistent data source and methodology across all provincial boundaries and territories. SCANFI is the first coherent 30m Canadian wall-to-wall map of tree structure and species composition and opens novel opportunities for a plethora of studies in a number of areas, such as forest economics, fire science and ecology.**Limitations**1- The spectral disturbances of some areas disturbed by pests are not comprehensively represented in the training set, thus making it impossible to predict all defoliation cases. One such area, severely impacted by the recent eastern spruce budworm outbreak, is located on the North Shore of the St-Lawrence River. These forests are misrepresented in our training data, there is therefore an imprecision in our estimates.2- Attributes of open stand classes, namely shrub, herbs, rock and bryoid, are more difficult to estimate through the photointerpretation of aerial images. Therefore, these estimates could be less reliable than the forest attribute estimates.3- As reported in the manuscript, the uncertainty of tree species cover predictions is relatively high. This is particularly true for less abundant tree species, such as ponderosa pine and tamarack. The tree species layers are therefore suitable for regional and coarser scale studies. Also, the broadleaf proportion are slightly underestimated in this product version.4- Our validation indicates that the areas in Yukon exhibit a notably lower R2 value. Consequently, estimates within these regions are less dependable. 5- Urban areas and roads are classified as rock, according to the 2020 Agriculture and Agri-Food Canada land-use classification map. Even though those areas contain mostly buildings and infrastructure, they may also contain trees. Forested urban parks are usually classified as forested areas. Vegetation attributes are also predicted for forested areas in agricultural regions.**Details on the product development and validation can be found in the following publication:**- Guindon, L., Manka, F., Correia, D.L.P., Villemaire, P., Smiley, B., Bernier, P., Gauthier, S., Beaudoin, A., Boucher, J., and Boulanger, Y. 2024. A new approach for Spatializing the Canadian National Forest Inventory (SCANFI) using Landsat dense time series. Can. J. For. Res. https://doi.org/10.1139/cjfr-2023-0118**Please cite this dataset as:**- Guindon L., Villemaire P., Correia D.L.P., Manka F., Lacarte S., Smiley B. 2023. SCANFI: Spatialized CAnadian National Forest Inventory data product. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/18e6a919-53fd-41ce-b4e2-44a9707c52dc **The following raster layers are available:**- NFI land cover class values: Land cover classes include Water, Rock, Bryoid, Herbs, Shrub, Treed broadleaf, Treed mixed and Treed conifer- Live aboveground dry tree biomass (tonnes/ha): biomass was derived from total merchantable volume estimates produced by provincial agencies- Height (meters): vegetation height- Crown closure (%): percentage of pixel covered by the tree canopy - Tree species cover (%): estimated as the proportion of the canopy covered by each tree species: - Balsam fir tree cover in percentage (Abies balsamea) - Black spruce tree cover in percentage (Picea mariana) - Douglas fir tree cover in percentage (Pseudotsuga menziesii) - Jack pine tree cover in percentage (Pinus banksiana) - Lodgepole pine tree cover in percentage (Pinus contorta) - Ponderosa pine tree cover in percentage (Pinus ponderosa) - Tamarack tree cover in percentage (Larix laricina) - White and red pine tree cover in percentage (Pinus strobus and Pinus resinosa) - Broadleaf tree cover in percentage (PrcB) - Other coniferous tree cover in percentage (PrcC)

This dataset provides information which is currently displayed on the Child Care Programs Map. The intent of the Child Care Programs Map is to provide an online resource to assist families searching for ministry-funded licensed child care listed by city, address, licence type and services offered. New licensed child care facilities are added as they become operational. The dataset is updated daily. [Child Care Map Application](https://catalogue.data.gov.bc.ca/dataset/d9ea3a4c-08df-48af-9776-a34a34d46201)

CanVec contains more than 60 topographic features classes organized into 8 themes: Transport Features, Administrative Features, Hydro Features, Land Features, Manmade Features, Elevation Features, Resource Management Features and Toponymic Features.This multiscale product originates from the best available geospatial data sources covering Canadian territory. It offers quality topographic information in vector format complying with international geomatics standards.CanVec can be used in Web Map Services (WMS) and geographic information systems (GIS) applications and used to produce thematic maps. Because of its many attributes, CanVec allows for extensive spatial analysis.Related Products (Open Maps Links):**[Constructions and Land Use in Canada - CanVec Series - Manmade Features](https://open.canada.ca/data/en/dataset/fd4369a4-21fe-4070-914a-067474da0fd6)****[Lakes, Rivers and Glaciers in Canada - CanVec Series - Hydrographic Features](https://open.canada.ca/data/en/dataset/9d96e8c9-22fe-4ad2-b5e8-94a6991b744b)****[Administrative Boundaries in Canada - CanVec Series - Administrative Features](https://open.canada.ca/data/en/dataset/306e5004-534b-4110-9feb-58e3a5c3fd97)****[Mines, Energy and Communication Networks in Canada - CanVec Series - Resources Management Features](https://open.canada.ca/data/en/dataset/92dbea79-f644-4a62-b25e-8eb993ca0264)****[Wooded Areas, Saturated Soils and Landscape in Canada - CanVec Series - Land Features](https://open.canada.ca/data/en/dataset/80aa8ec6-4947-48de-bc9c-7d09d48b4cad)****[Transport Networks in Canada - CanVec Series - Transport Features](https://open.canada.ca/data/en/dataset/2dac78ba-8543-48a6-8f07-faeef56f9895)****[Elevation in Canada - CanVec Series - Elevation Features](https://open.canada.ca/data/en/dataset/64aad38d-f692-4ab6-bf2c-f938586c1249)****[Map Labels - CanVec Series - Toponymic Features](https://open.canada.ca/data/en/dataset/b3fdcd34-4533-415f-8f83-68f17f9d5d68)**

GeoAI are buildings, hydrography, forests, and roads automatically extracted using Deep Learning models applied to a source dataset, typically aerial or satellite images. The primary aim of GeoAI is to increase Canada's availability of high-resolution foundational geospatial data for both spatial and temporal coverage.‌The infrastructure and expertise put in place by NRCan enables a rapid, efficient, and scalable data creation process through the use of leading-edge technology and Artificial Intelligence models. Published datasets for a given source can be revisited at a later date as more accurate models are developed and put into production. For now, only static files are available, but as the series develops, new products and services will be added.Several use cases of GeoAI data for change detection have been created. To view them, please follow the links below:- Iqaluit: https://open.canada.ca/data/en/dataset/ef29513d-a007-408c-beba-65f86e7b5b01- Calgary: https://open.canada.ca/data/en/dataset/bd07b597-5166-4b62-ae9c-245b3c62ea03- Québec City: https://open.canada.ca/data/en/dataset/4026720e-f7fb-478e-a58f-c62ebe20005d- Winnipeg: https://open.canada.ca/data/en/dataset/a6874aac-cfcd-4b92-bb3f-6031eedb5b57- Victoria: https://open.canada.ca/data/en/dataset/f011c7b9-f79e-42f8-9481-9bf9788bb189- Trois-Rivières: https://open.canada.ca/data/en/dataset/2b11a323-52c2-43d5-9c09-bc4b15b1bcc8

This collection is a legacy product that is no longer supported. It may not meet current government standards.The Canadian Digital Elevation Model (CDEM) is part of Natural Resources Canada's altimetry system designed to better meet the users' needs for elevation data and products.The CDEM stems from the existing Canadian Digital Elevation Data (CDED). In these data, elevations can be either ground or reflective surface elevations.A CDEM mosaic can be obtained for a pre-defined or user-defined extent. The coverage and resolution of a mosaic varies according to latitude and to the extent of the requested area.Derived products such as slope, shaded relief and colour shaded relief maps can also be generated on demand by using the Geospatial-Data Extraction tool. Data can then be saved in many formats.The pre-packaged GeoTiff datasets are based on the National Topographic System of Canada (NTS) at the 1:250 000 scale; the NTS index file is available in the Resources section in many formats.

This series of historic flood susceptibility maps comes from an XGBboost machine learning model trained on major floods from 2005 to 2023. The trained model is then run for each year from 2000 to 2023, including unique temporal characteristics of temperature, precipitation, land use land cover and Normalized Difference Vegetation Index (NDVI), to predict the flood susceptibility of any given year.This dataset forms part of a broader collection of flood susceptibility datasets, offering related information and analyses. The collection includes an overview page with associated publications, historic susceptibility values, temporal trends, and future projections.- [Collection – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/1074f781-85d3-4c86-86cb-fd1c339197dc)- [Trends and Extremes – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/3202e0a0-0afb-4120-b102-b0c41f0fb9eb)- [Future - Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/c00f95a3-7bab-4d28-b9cc-b30f06b5afd2)

Compiled by Alberta Data Partnerships Ltd. (ADP), on behalf of the Government of Alberta, the ATS v4.1 Polygons - Section with Road Allowance layer contains polygons that represent the location of Sections and adjacent Road Allowance Segment polygons, derived from the Master Alberta Township System points file published as ATS Version 4.1, dated March 31, 2005, and clipped to an updated Alberta Data Partnerships Ltd. (ADP) created version of the Alberta provincial boundary.

Compiled by Alberta Data Partnerships Ltd. (ADP), on behalf of the Government of Alberta, the ATS v4.1 Polygons - Quarter Section with Road Allowance layer contains polygons that represent the location of Quarter Sections and adjacent Road Allowance Segment polygons, derived from the Master Alberta Township System points file published as ATS Version 4.1, dated March 31, 2005, and clipped to an updated Alberta Data Partnerships Ltd. (ADP) created version of the Alberta provincial boundary.