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 map includes a variety of Landsat services which have been time enabled and can be explored using the Time Slider in the ArcGIS.COM Map Viewer or Explorer. Each layer has a predefined useful band combination already set on the services. For more information about each layer, click on the hyperlink bellow. Data Source: This map includes image services compiled from the following Global Land Survey (GLS) datasets: GLS 2005, GLS 2000, GLS 1990, and GLS 1975. GLS datasets are created by the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) using Landsat images. These global minimal-cloud cover, orthorectified Landsat data products support global assessments of land-cover, land cover-change, and ecosystem dynamics such as disturbance and vegetation health.

Contained within the 5th Edition (1978 to 1995) of the National Atlas of Canada is a map that shows Canada as seen from space in August, 1990 using uninterrupted 1.1 kilometer resolution imagery; final colors are adjusted to approximate those of the land cover portrayed.

The satellite image of Canada is a composite of several individual satellite images form the Advanced Very High Resolution Radiometre (AVHRR) sensor on board various NOAA Satellites. The colours reflect differences in the density of vegetation cover: bright green for dense vegetation in humid southern regions; yellow for semi-arid and for mountainous regions; brown for the north where vegetation cover is very sparse; and white for snow and ice. An inset map shows a satellite image mosaic of North America with 35 land cover classes, based on data from the SPOT satellite VGT (vegetation) sensor.

The Canada Geospatial Imagery Analytics Market report segments the industry into Type (Imagery Analytics, Video Analytics), Deployment Mode (On-premise, Cloud), Organization Size (SMEs, Large Enterprises), and Verticals (Insurance, Agriculture, Defense and Security, Environmental Monitoring, Engineering and Construction, Government, Other Verticals). Five years of historic data and five-year forecasts are provided.

This image service contains high resolution satellite imagery for selected regions throughout the Yukon. Imagery is 1m pixel resolution, or better. Imagery was supplied by the Government of Yukon, and the Canadian Department of National Defense. All the imagery in this service is licensed. If you have any questions about Yukon government satellite imagery, please contact Geomatics.Help@gov.yk.can. This service is managed by Geomatics Yukon.

This dataset contains georeferenced three-band orthomosaics of green, red, and near-infrared (NIR) digital imagery at 1m resolution collected over selected surface waters across Alaska and Canada between July 9 and August 17, 2017. The orthomosaics were generated from individual images collected by a Cirrus Designs Digital Camera System (DCS) mounted on a Beechcraft Super King Air B200 aircraft from approximately 8-11 km altitude. Flights were over the following areas: Saskatchewan River, Saskatoon, Inuvik, Yukon River including Yukon Flats, Sagavanirktok River, Arctic Coastal Plain, Old Crow Flats, Peace-Athabasca Delta, Slave River, Athabasca River, Yellowknife, Great Slave Lake, Mackenzie River and Delta, Daring Lake, and other selected locations. Most locations were imaged twice during two flight campaigns in Canada and Alaska extending roughly SE-NW then NW-SE up to a month apart. The data were georeferenced using 303 ground control points (GCPs) across the study region.

Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per ground surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem, weather and climate modelling and monitoring. This product consists of a national scale coverage (Canada) of monthly maps of the maximum LAI during a growing season (May-June-july-August-September) at 20m. References: L. Brown, R. Fernandes, N. Djamai, C. Meier, N. Gobron, H. Morris, C. Canisius, G. Bai, C. Lerebourg, C. Lanconelli, M. Clerici, J. Dash. Validation of baseline and modified Sentinel-2 Level 2 Prototype Processor leaf area index retrievals over the United States IISPRS J. Photogramm. Remote Sens., 175 (2021), pp. 71-87, https://doi.org/10.1016/j.isprsjprs.2021.02.020. https://www.sciencedirect.com/science/article/pii/S0924271621000617 Richard Fernandes, Luke Brown, Francis Canisius, Jadu Dash, Liming He, Gang Hong, Lucy Huang, Nhu Quynh Le, Camryn MacDougall, Courtney Meier, Patrick Osei Darko, Hemit Shah, Lynsay Spafford, Lixin Sun, 2023. Validation of Simplified Level 2 Prototype Processor Sentinel-2 fraction of canopy cover, fraction of absorbed photosynthetically active radiation and leaf area index products over North American forests, Remote Sensing of Environment, Volume 293, https://doi.org/10.1016/j.rse.2023.113600. https://www.sciencedirect.com/science/article/pii/S0034425723001517

These products are derived from RGB (red/green/blue) images, a satellite processing technique that uses a combination of satellite sensor bands (also called channels) and applies a red/green/blue (RGB) filter to each of them. The result is a false-color image, i.e. an image that does not correspond to what the human eye would see, but offers high contrast between different cloud types and surface features. The on-board sensor of a weather satellite obtains two basic types of information: visible light data (reflected light) reflecting off clouds and different surface types, also known as "reflectance", and infrared data (emitted radiation) which are long-wave radiations emitted by clouds and surface features. RGBs are specially designed to combine this type of satellite data, resulting in an information-rich final product. Four types of products are currently generated from the GOES-West and GOES-East satellites: "NightIR" and "NightMicrophysics", at 2km resolution, are generated 24 hours a day with infrared channels, so are visible both night and day, and "NaturalColour" and "DayCloudConvection", at 1km resolution, which combine visible light channels with infrared channels; their higher resolution makes the latter two products more popular, but they are not available during most of the night (between 02UTC and 07UTC for GOES-Est, and between 06UTC and 11UTC for GOES-Ouest) given the absence of reflected sunlight. Other RGB products should be added gradually in the future to meet different needs.

The Ontario Imagery Web Map Service (OIWMS) is an open data service available to everyone free of charge. It provides instant online access to the most recent, highest quality, province wide imagery. GEOspatial Ontario (GEO) makes this data available as an Open Geospatial Consortium (OGC) compliant web map service or as an ArcGIS map service. Imagery was compiled from many different acquisitions which are detailed in the Ontario Imagery Web Map Service Metadata Guide linked below. Instructions on how to use the service can also be found in the Imagery User Guide linked below.Note: This map displays the Ontario Imagery Web Map Service Source, a companion ArcGIS web map service to the Ontario Imagery Web Map Service. It provides an overlay that can be used to identify acquisition relevant information such as sensor source and acquisition date. OIWMS contains several hierarchical layers of imagery, with coarser less detailed imagery that draws at broad scales, such as a province wide zooms, and finer more detailed imagery that draws when zoomed in, such as city-wide zooms. The attributes associated with this data describes at what scales (based on a computer screen) the specific imagery datasets are visible.Available ProductsOntario Imagery OCG Web Map Service – public linkOntario Imagery ArcGIS Map Service – public linkOntario Imagery Web Map Service Source – public linkOntario Imagery ArcGIS Map Service – OPS internal linkOntario Imagery Web Map Service Source – OPS internal linkAdditional DocumentationOntario Imagery Web Map Service Metadata Guide (PDF)Imagery User Guide (Word)StatusCompleted: Production of the data has been completedMaintenance and Update FrequencyAnnually: Data is updated every yearContactOntario Ministry of Natural Resources, Geospatial Ontario, imagery@ontario.ca

This image service contains high resolution satellite imagery for selected regions throughout the Yukon. Imagery is 1m pixel resolution, or better. Imagery was supplied by the Government of Yukon, and the Canadian Department of National Defense. All the imagery in this service is licensed. If you have any questions about Yukon government satellite imagery, please contact Geomatics.Help@gov.yk.can. This service is managed by Geomatics Yukon.

The Canadian satellite-based Earth observation market is experiencing robust growth, driven by increasing demand across diverse sectors. The market, valued at an estimated $200 million CAD in 2025 (a reasonable estimate given the global market size and Canada's significant contribution to space technology), is projected to exhibit a Compound Annual Growth Rate (CAGR) of 8.14% from 2025 to 2033. This growth is fueled by several key factors. Government initiatives promoting space exploration and technological advancements are creating a favorable environment for market expansion. Furthermore, the rising adoption of satellite imagery for precise agriculture practices, effective urban planning, resource management (energy and raw materials), and environmental monitoring (climate services) is a significant catalyst. The increasing need for accurate and timely data for infrastructure development and cultural heritage preservation further contributes to market growth. The market is segmented by data type (Earth observation data and value-added services), satellite orbit (Low Earth Orbit, Medium Earth Orbit, and Geostationary Orbit), and end-users (agriculture, urban development, climate services, energy, infrastructure, and others). The competitive landscape comprises both international giants like Airbus Defense and Space and Maxar Technologies, and domestic players. While technological advancements present opportunities, challenges include high initial investment costs for satellite technology and data processing, as well as the need for robust data security and privacy regulations. The forecast period (2025-2033) anticipates sustained growth, primarily driven by technological innovations leading to improved image resolution, faster data processing, and the development of advanced analytical tools. Specific segments, like those utilizing Low Earth Orbit satellites for high-resolution imagery and value-added services focusing on data analytics and customized solutions, are poised for exceptional growth. Government investment in research and development, combined with the increasing adoption of cloud-based platforms for data storage and processing, will further propel market expansion. While the market faces challenges, the long-term outlook for the Canadian satellite-based Earth observation market remains optimistic, promising substantial contributions to economic growth and technological advancements within the country. Recent developments include: May 2023: The University of Saskatchewan Canadian CubeSat Project used the spaceX CRS-28 rocket to launch the RADSAT-SK satellite. The satellite will collect radiation data for a year while in orbit., October 2022: The Canadian government announced that it would fund the development of a satellite and instruments for a NASA-led Earth science program. The Canadian government will fund the manufacturing of the satellite and other sensors for a NASA-led Earth research program.. Key drivers for this market are: New Technologies Implementation in earth observation satellite technologies, Increasing demand of high-resolution imaging services. Potential restraints include: New Technologies Implementation in earth observation satellite technologies, Increasing demand of high-resolution imaging services. Notable trends are: New Technologies Implementation in Earth Observation Satellite Technologies.

Note: To visualize the data in the viewer, zoom into the area of interest. The National Air Photo Library (NAPL) of Natural Resources Canada archives over 6 million aerial photographs covering all of Canada, some of which date back to the 1920s. This collection includes Time Series of aerial orthophoto mosaics over a selection of major cities or targeted areas that allow the observation of various changes that occur over time in those selected regions. These mosaics are disseminated through the Data Cube Platform implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The data is available as Cloud Optimized GeoTIFF (COG) for direct access and as Web Map Services (WMS) or Web Coverage Services (WCS) with a temporal dimension for consumption in Web or GIS applications. The NAPL mosaics are made from the best spatial resolution available for each time period, which means that the orthophotos composing a NAPL Time Series are not necessarily coregistrated. For this dataset, the spatial resolutions are: 100 cm for the year 1932 and 50 cm for the year 1950. The NAPL indexes and stores federal aerial photography for Canada, and maintains a comprehensive historical archive and public reference centre. The Earth Observation Data Management System (EODMS) online application allows clients to search and retrieve metadata for over 3 million out of 6 million air photos. The EODMS online application enables public and government users to search and order raw Government of Canada Earth Observation images and archived products managed by NRCan such as aerial photos and satellite imagery. To access air photos, you can visit the EODMS web site: https://eodms-sgdot.nrcan-rncan.gc.ca/index-en.html

The Canadian geospatial imagery analytics market is experiencing robust growth, driven by increasing government investments in infrastructure development and modernization, coupled with the rising adoption of advanced technologies like AI and machine learning for data analysis. The market's Compound Annual Growth Rate (CAGR) of 21.76% from 2019-2024 suggests significant potential, projecting substantial expansion through 2033. Key drivers include enhanced precision agriculture needs, improving infrastructure management, bolstering national security efforts, and the growing demand for environmental monitoring solutions. The market segmentation reveals strong demand across diverse sectors, with insurance, agriculture, defense and security, and environmental monitoring demonstrating particularly high growth rates. The adoption of cloud-based solutions is also accelerating market expansion, offering accessibility and scalability advantages to both SMEs and large enterprises. Competition is active, with established players like Harris Corporation, Trimble Inc., and Google LLC alongside specialized firms such as EOS Data Analytics contributing to the market's dynamism. The forecast period (2025-2033) is expected to see continued growth, fueled by factors such as the increasing availability of high-resolution satellite imagery, advancements in analytics capabilities, and government initiatives to promote the adoption of geospatial technologies. The on-premise segment might see slower growth compared to cloud-based solutions, due to the latter's cost-effectiveness and flexibility. The large enterprises segment is likely to dominate in terms of market share, owing to their higher budget allocation for advanced technologies. However, SMEs are also anticipated to show increasing adoption rates, driven by the availability of affordable and user-friendly cloud-based solutions. Canada's strong focus on sustainable development and environmental protection will further boost the demand for geospatial imagery analytics in the environmental monitoring sector. The overall market outlook remains positive, with substantial growth opportunities across various segments and applications. Recent developments include: October 2023: Canada will invest CAD 1.01 billion (USD 740.90 million) in satellite technology over the next 15 years to boost the Earth observation data it uses to track wildfires and other environmental crises. The new initiative called Radarsat+ will gather information about Earth's oceans, land, climate, and populated areas. Data collected from earth observation technologies allows scientists to see how the planet changes and make decisions for emergencies like wildfires or longer-term issues like climate change., December 2022: Carl Data Solutions, a player in predictive analytics for environmental monitoring as a service (EMaaS) and smart city applications driven by compliance, signed a strategic partnership agreement with K2 Geospatial, a Montreal-based company. Over 350 cities and municipalities, seaports, airports, road authorities, and utilities across North America and Europe are among the 500 organizations using K2 Geospatial. JMap, a spatial analysis mapping integration platform made to connect silos in a fully integrated IT ecosystem, is used by K2 users., In September 2022, CAPE Analytics, a provider of AI-powered geospatial property intelligence, partnered with weather technology firm Canopy Weather to launch a product for storm-related damage. Canopy Weather applies an application-first approach to deliver weather data products with specific, real-world business applications. Powered by machine learning, the rating indicates the likelihood of post-storm damage to roofs after severe weather. It can predict the subset of claims eligible for automated, straight-through processing with over 96% accuracy.. Key drivers for this market are: Increasing Demand for Location-based Services, Technological Innovations in Geospatial Imagery Services. Potential restraints include: Increasing Demand for Location-based Services, Technological Innovations in Geospatial Imagery Services. Notable trends are: Increasing Adoption of 5G in Canada is Boosting the Market Growth.

Knowledge of the location of Earth’s surface water in time and space is critical to inform policy decisions on environment, wildlife, and human security. Dynamic surface water maps generally represent water occurrence, also referred to as inundation frequency, depicting the percentage of valid observations when water is detected at the surface. The location and duration of surface water varies from areas of permanent water with 100% inundation frequency where water is always observed, to areas of permanent land with 0% inundation where water never occurs. Between these two extremes are areas of ephemeral water that experience periodic flooding with inundation frequencies between 0-100%. National-scale dynamic surface water information was generated for years 1984-2023 at 30m spatial resolution from the historical Landsat archive over Canada. The complete dataset consists of annual water maps and derived products including inundation frequency and inter-annual wetting and drying trends calculated using per-pixel logistic regression. The complete dataset enables an assessment of the timing, duration, and trends towards wetting or drying at regional to national scales. Associated publication: https://www.sciencedirect.com/science/article/pii/S0034425722002358

Note: To visualize the data in the viewer, zoom into the area of interest. The National Air Photo Library (NAPL) of Natural Resources Canada archives over 6 million aerial photographs covering all of Canada, some of which date back to the 1920s. This collection includes Time Series of aerial orthophoto mosaics over a selection of major cities or targeted areas that allow the observation of various changes that occur over time in those selected regions. These mosaics are disseminated through the Data Cube Platform implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The data is available as Cloud Optimized GeoTIFF (COG) for direct access and as Web Map Services (WMS) or Web Coverage Services (WCS) with a temporal dimension for consumption in Web or GIS applications. The NAPL mosaics are made from the best spatial resolution available for each time period, which means that the orthophotos composing a NAPL Time Series are not necessarily coregistrated. For this dataset, the spatial resolutions are: 100 cm for the year 1947 and 50 cm for the year 1967. The NAPL indexes and stores federal aerial photography for Canada, and maintains a comprehensive historical archive and public reference centre. The Earth Observation Data Management System (EODMS) online application allows clients to search and retrieve metadata for over 3 million out of 6 million air photos. The EODMS online application enables public and government users to search and order raw Government of Canada Earth Observation images and archived products managed by NRCan such as aerial photos and satellite imagery. To access air photos, you can visit the EODMS web site: https://eodms-sgdot.nrcan-rncan.gc.ca/index-en.html

Note: To visualize the data in the viewer, zoom into the area of interest. The National Air Photo Library (NAPL) of Natural Resources Canada archives over 6 million aerial photographs covering all of Canada, some of which date back to the 1920s. This collection includes Time Series of aerial orthophoto mosaics over a selection of major cities or targeted areas that allow the observation of various changes that occur over time in those selected regions. These mosaics are disseminated through the Data Cube Platform implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The data is available as Cloud Optimized GeoTIFF (COG) files for direct access and as Web Map Services (WMS) or Web Coverage Services (WCS) with a temporal dimension for consumption in Web or GIS applications. The NAPL mosaics are made from the best spatial resolution available for each time period, which means that the orthophotos composing a NAPL Time Series are not necessarily coregistered. For this dataset, the spatial resolutions are: 25 cm for the year 1950, 50 cm for the year 1959, 50 cm for the year 1967, 50 cm for the year 1972, 50 cm for the year 1978 and 70 cm for the year 1982. The NAPL indexes and stores federal aerial photography for Canada, and maintains a comprehensive historical archive and public reference centre. The Earth Observation Data Management System (EODMS) online application allows clients to search and retrieve metadata for over 3 million out of 6 million air photos. The EODMS online application enables public and government users to search and order raw Government of Canada Earth Observation images and archived products managed by NRCan such as aerial photos and satellite imagery. To access air photos, you can visit the EODMS web site: https://eodms-sgdot.nrcan-rncan.gc.ca/index-en.html

FCOVER corresponds to the amount of the ground surface that is covered by vegetation, including the understory, when viewed vertically (from nadir). FCOVER is an indicator of the spatial extent of vegetation independent of land cover class. It is a dimensionless quantity that varies from 0 to 1, and as an intrinsic property of the canopy, is not dependent on satellite observation conditions.This product consists of FCOVER indicator during peak-season (June-July-August) at 100m resolution covering Canada's land mass.

Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per ground surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem, weather and climate modelling and monitoring. This product consists of a national scale coverage (Canada) of monthly maps of the maximum LAI during a growing season (May-June-july-August-September) at 20m. References: L. Brown, R. Fernandes, N. Djamai, C. Meier, N. Gobron, H. Morris, C. Canisius, G. Bai, C. Lerebourg, C. Lanconelli, M. Clerici, J. Dash. Validation of baseline and modified Sentinel-2 Level 2 Prototype Processor leaf area index retrievals over the United States IISPRS J. Photogramm. Remote Sens., 175 (2021), pp. 71-87, https://doi.org/10.1016/j.isprsjprs.2021.02.020. https://www.sciencedirect.com/science/article/pii/S0924271621000617 Richard Fernandes, Luke Brown, Francis Canisius, Jadu Dash, Liming He, Gang Hong, Lucy Huang, Nhu Quynh Le, Camryn MacDougall, Courtney Meier, Patrick Osei Darko, Hemit Shah, Lynsay Spafford, Lixin Sun, 2023. Validation of Simplified Level 2 Prototype Processor Sentinel-2 fraction of canopy cover, fraction of absorbed photosynthetically active radiation and leaf area index products over North American forests, Remote Sensing of Environment, Volume 293, https://doi.org/10.1016/j.rse.2023.113600. https://www.sciencedirect.com/science/article/pii/S0034425723001517

Aerial Imagery (.sid file) of the City of Waterloo, Ontario, Canada, captured in spring 2020. Note this is a large file and may take some time to download.