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/vertical 2D decomposition is approximate and assumes constant viewing geometry and the absence of horizontal-north deformation.In the line-of-sight (LOS) map computed from ascending orbit data, a negative signal approximately corresponds to either subsidence or eastward motion, while a positive signal corresponds to uplift or westward motion. In the LOS map computed from descending orbit data, a negative signal approximately corresponds to either subsidence or westward motion, while a positive signal corresponds to uplift or eastward motion.In the horizontal-east map, a negative signal corresponds to westward motion, while a positive signal corresponds to eastward motion. In the vertical map, a negative signal indicates subsidence, while a positive signal indicates uplift.The maps were calculated from Sentinel-1 Synthetic Aperture Radar data collected between 2017 and 2024 during the snow-free season. Interferometric analysis of Sentinel-1 data was performed using GAMMA Software (https://www.gamma-rs.ch), and the long-term deformation rate was computed with the Multidimensional Small Baseline Subset (MSBAS) Software Version 10 (https://doi.org/10.1080/07038992.2024.2424753) at the Canada Centre for Mapping and Earth Observation, Natural Resources Canada.Long-wavelength signals caused by postglacial rebound and tectonic motion were filtered to enhance the visibility of small-scale deformation processes, such as those originating from landslides and mining. Field studies have confirmed only a few of these processes to date. The maps are expected to contain processing artifacts, which will be addressed in future work.References:Samsonov, S. V., & Feng, W. (2023). Deformation Retrievals for North America and Eurasia from Sentinel-1 DInSAR: Big Data Approach, Processing Methodology and Challenges. Canadian Journal of Remote Sensing, 49(1). https://doi.org/10.1080/07038992.2023.2247095Samsonov, S. V. (2024). Multidimensional Small Baseline Subset (MSBAS) Software for Constrained and Unconstrained Deformation Analysis of Partially Coherent DInSAR and Speckle Offset Data. Canadian Journal of Remote Sensing, 50(1). https://doi.org/10.1080/07038992.2024.2424753Limitation of Liability :The information contained on this website is provided on an “as is” basis and Natural Resources Canada makes no representations or warranties respecting the information, either expressed or implied, arising by law or otherwise, including but not limited to, effectiveness, completeness, accuracy or fitness for a particular purpose. Natural Resources Canada does not assume any liability in respect of any damage or loss based on the use of this website. In no event shall Natural Resources Canada be liable in any way for any direct, indirect, special, incidental, consequential, or other damages based on any use of this website or any other website to which this site is linked, including, without limitation, any lost profits or revenue or business interruption.

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.**

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 Global Deterministic Prediction System (GDPS) is a coupled atmosphere (GEM), ocean and sea ice (NEMO-CICE) deterministic numerical weather prediction model. Forecasts are carried out twice a day for 10 days lead time. The geographical coverage is global at 15 km horizontal resolution. Data is available on some thirty vertical levels and interpolated on a global latitude-longitude uniform grid with 0.15 degree horizontal resolution. Variables availability in number and time frequency is a function of forecast lead time.

This dataset includes daily averages of solar irradiance on tilted surfaces for all of Canada based on the period of 1998 - 2022.Daily averages of solar irradiance are displayed on both a monthly and annual basis for ten different tilt and tracking methods relative to the ground (horizontal) and latitude of the location. The daily averages were derived from multi-year satellite-derived solar resource datasets at an hourly temporal resolution and gridded geospatial resolution of approximately 10 km by 10 km.The data can be used to further assess the potential of solar energy technologies in Canada, including solar photovoltaics (PV) for electricity and solar thermal for domestic hot water and space heating. Maps of solar resource potential in Canada – Data Format The data stored in these files includes the daily-average insolation on tilted surfaces in units of kW·hr/m² for a given period. Each band represents period, numbered in order: band 1 = Annual, band 2 = January, band 3 = February, ..., band 13 = December.The period of averaging is the year 1998-2022, inclusive.Four fixed tilted surfaces of 0° (horizontal), 30°, 60°, and 90° (vertical) relative to the horizontal plane:- fixed tilted surfaces of 0° (vertical) relative to the horizontal plane (H+ 00 S+00)- fixed tilted surfaces of 30° (vertical) relative to the horizontal plane (H+ 30 S+00)- fixed tilted surfaces of 60° (vertical) relative to the horizontal plane (H+ 60 S+00)- fixed tilted surfaces of 90° (vertical) relative to the horizontal plan (H+ 90 S+00)Three fixed tilted surfaces of 0°, +15°, and -15°, relative to the local latitude:- fixed tilted surfaces of 0° relative to the local latitude (L+00 S+00)- fixed tilted surfaces of +15°, relative to the local latitude (L+00 S+00)- fixed tilted surfaces of -15°, relative to the local latitude (L+00 S+00)- A two-axis tracking surface that follows the sun throughout the day (T+00 T+00)- A single-axis tracking surface with the axis aligned north-south, tracking the sun east to west (A+00_S+90)- A single-axis tracking surface with the axis aligned east-west, tracking the sun's elevation (A+00_S+00)

Average of the hourly Global Horizontal Irradiance (GHI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE").The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.

Data has been collected primarily using a depth measurement device, such as an echo-sounder, in combination with a Global Positioning System (GPS) for horizontal positioning. Other survey methods, such as bathymetric LiDAR may also have been used. The survey method used in each body of water is shown in the [Bathymetry Index](https://geohub.lio.gov.on.ca/datasets/mnrf::bathymetry-index ).