The DND Air Weapons Range dataset is comprised of all the polygons that represent the Air Weapons Range established by the Department of National Defence, Government of Canada, within the Province of Alberta. Air Weapons Range is the area used as a practice and firing range with restricted access provisions and which is owned and operated by the Department of National Defence, Government of Canada.

Average of the hourly Direct Normal Irradiance (DNI) 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/.

The purpose of this feature layer is to provide the 1997 overland flooding boundary in the Red River Valley.This dataset shows the extent of peak overland flooding in the Red River Valley in 1997 . Data is based on RADARSAT – 1 satellite imagery. During processing, the raw data set was resampled to 12.5 meter pixel resolution, then classified using PCI Geomatica software which is a specialized software designed to manipulate space born imagery. The final output depicting the flooding boundary is available as a TIFF or Shapefile. Launched in November 1995, RADARSAT-1 was a Canadian-led project which provided useful information to both commercial and scientific users in such fields as disaster management, agriculture, cartography, hydrology, forestry, oceanography, ice studies and coastal monitoring. Equipped with a powerful synthetic aperture radar (SAR) instrument, it acquired images of the Earth day or night, in all weather and through cloud cover, smoke and haze. As of March 2013, the satellite was declared non-operational and is no longer collecting data. Many applications were developed to take advantage of RADARSAT-1 capacity for detecting the presence of water. These included monitoring flooding and the build-up of river ice, and mapping the melting of snow-covered areas. When used for flood monitoring, RADARSAT-1 data helped assess the impact of flooding, predicted the extent and duration of floodwaters, analyzed the environmental impact of water diversion projects, and developed flood mitigation measures. Fields Included:FID : Internal feature numberNAME : Flooded area nameAREA_SQKM : Size of flooded area

The DND Military Base dataset is comprised of all the polygons that represent the Military Bases established for the Department of National Defence, Government of Canada, within the Province of Alberta. A Military Base is an area owned by the Department of National Defence, Government of Canada where various military activities occur.

The Ontario Road Network (ORN) Composite product is a segmented derivative of the ORN Road Net Element (ORNELEM) data class. You can use it for mapping and general spatial analysis. Road segment information includes: * addressing * full street name * alternate street name * speed limit * number of lanes * pavement status * road class * jurisdiction * route number * direction of traffic flow * shield type information The ORN is a provincewide geographic database of over 250,000 km of: * municipal roads * provincial highways * resource and recreational roads The ORN is the authoritative source of roads data for the Government of Ontario. This product is derived from the [ORN Road Net Element](https://geohub.lio.gov.on.ca/datasets/mnrf::ontario-road-network-orn-road-net-element/about) data class. It combines three types of geometry: * road elements * ferry connections * virtual roads This product also includes additional road feature layers including: * blocked passages * underpasses * toll points * structures

The surficial material dataset was developed as part of the Western Economic Partnership Agreement (WEPA) project covering all of NTS 73M, the southern three-quarters of 74D and southeast part of 84A. Part of the dataset was compiled by airphoto interpretations and followed by random ground-truthing by AGS geologists (NTS 73M). The dataset was later merged with other existing surficial geology maps (74D and 84A). The mapping scheme chosen for the 1:50 000 scale terrain classification is a variant of the scheme used in Alberta Geological Survey Bulletin 57 to map the surficial geology of the Sand River area (Map 178), NTS 73L, directly south of the study area. In this terrain classification scheme, each map unit includes a component of genesis, morphology and relief. Where available, additional information regarding the properties of the genetic unit was included as a genetic modifier. For example, the map unit 'sMh1' denotes hummocky (h), low relief (1), sandy (s) moraine (M). Genesis of geological material is considered to be the primary component of the map unit thus colours on the map depict differences in genesis. In the above example, the map unit colour would correspond to the legend colour chosen for moraine (M). An attempt has been made to reclassify the surficial geological units depicted in the surficial geology map of area NTS 74D (Map 148) using this mapping scheme, without significantly changing the polygon shapes of that previous work.

This dataset is a compilation of numerous data files recovered as part of a data request in 2024 from a historical archive of DFO research data. Sediment and Suspended Particulate Matter (SPM) samples were collected over more than a decade as part of Dr. Douglas Loring’s research program while working at the Bedford Institute of Oceanography (BIO). Samples were collected as part of individual and collaborative research projects, and links to the relevant primary science publications and reports are included in the data in an effort to provide context to the data, as well as describe the field and laboratory techniques used to generate the attached data.

Pipeline centre-lines associated with oil and gas pipeline activity and falling within the area representing the pipeline right of way. This dataset contains line features collected on or after July 11, 2016 for approved pipeline centre-line locations. The dataset is updated nightly.

This polygon layer reflects short-range (up to 84 hours) accumulated precipitation forecasts from the Regional Deterministic Prediction System (RDPS), a high-resolution (~10 km) weather model developed by Environment and Climate Change Canada (ECCC). It supports flood forecasting, hydrological modeling, and operational planning by providing refined, near-real-time precipitation guidance for Canada and surrounding areas.Short-Range Forecasts: RDPS runs multiple times per day, offering precipitation outlooks for days 0–3.5 with updates every six hours. High Resolution: At ~10 km, RDPS captures critical mesoscale phenomena like localized downpours, lake-effect snow, and terrain-driven precipitation. Hydrological Utility: Especially valuable for sub-basin-level flood risk assessment and water resource management in near-term scenarios. Technical Basis: The RDPS is a limited-area configuration of the GEM model, using initial/boundary conditions from ECCC’s Global Deterministic Prediction System (GDPS).

This polygon layer depicts sub-basin average observed precipitation from the High Resolution Deterministic Precipitation Analysis (HRDPA). Offers insight into how much rain/snow actually fell across each watershed in the past observation period. Observation periods we are interested are for past 1 day, 3 days and 7 days.HRDPA is ECCC’s high-resolution precipitation analysis, merging gauge, radar, and HRDPS model data. This layer aggregates the final (or preliminary) HRDPA accumulations to sub-basin polygons. Each record indicates the average precipitation that truly occurred over each watershed, vital for verifying model forecasts, calibrating hydrological models, and conducting post-event analyses of flood or drought severity.