High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**

This data set contains Manitoba market cattle prices and volumes sold at local auction marts.Description of Cattle Prices -source

The Moisture Anomaly Index (Palmer-Z) is an estimate of the moisture difference from normal (a 30-year mean). It attempts to express conditions for the current month regardless of what may have occurred before the month in question.

The daily mean is the average of all unit values for a given day.

The monthly mean is the average of daily mean values for a given month.

High resolution forest change for Canada (Change Year) 1985-2011The forest change data included in this product is national in scope (entire forested ecosystem) and represents the first wall-to-wall characterization of wildfire and harvest in Canada at a spatial resolution commensurate with human impacts. The information outcomes represent 27 years of stand replacing change in Canada’s forests, derived from a single, consistent spatially-explicit data source, derived in a fully automated manner. This demonstrated capacity to characterize forests at a resolution that captures human impacts is key to establishing a baseline for detailed monitoring of forested ecosystems from management and science perspectives. Time series of Landsat data were used to characterize national trends in stand replacing forest disturbances caused by wildfire and harvest for the period 1985–2011 for Canada's 650 million hectare forested ecosystems (https://authors.elsevier.com/sd/article/S0034425717301360 ). Landsat data has a 30m spatial resolution, so the change information is highly detailed and is commensurate with that of human impacts. These data represent annual stand replacing forest changes. The stand replacing disturbances types labeled are wildfire and harvest, with lower confidence wildfire and harvest, also shared. The distinction and sharing of lower class membership likelihoods is to indicate to users that some change events were more difficult to allocate to a change type, but are generally found to be in the correct category. For an overview on the data, image processing, and time series change detection methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2016; http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1187673).The data available is, 1. a binary change/no-change; 2. Change year; and, 3. Change type. When using this data, please cite as: White, J.C., M.A. Wulder, T. Hermosilla, N.C. Coops, and G. Hobart. (2017). A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment. 192: 303-321. DOI: 10.1016/j.rse.2017.03.035. https://authors.elsevier.com/sd/article/S0034425717301360Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011

Normal Annual Runoff for 1961 - 1990, in mm

A feature is a representation of a real world object, such as a lake, stream, dam or rapid. There are three hydrographic feature classes:  points, lines and polys.   All may impede or be hazardous to waterflow and/or navigation on a watercourse or waterbody. This data shows natural and manmade poly features.  Examples include: * break walls * dams * rapids * shipwrecks [Technical Bulletin: Data migrated to new Ontario Hydro Network (OHN) - Hydrographic Feature Data Classes (PDF)](http://geo2.scholarsportal.info/proxy.html?http:__maps.scholarsportal.info/files/PDFS/public/OGDE/OHN/TB-OHN-PostMigration_101112.pdf)

Data represents surface water occurrence frequency (percentage), which describes the frequency for each grid appeared as water in the 30 years time period of 1991 to 2020. The data covers Canada’s entire landmass including all transboundary watersheds, and is at 30-meter spatial resolution. The surface water occurrence frequency is derived using the surface water model of Wang et al. (2023) from all-available monthly water data observed by the Landsat satellites (Pekel et al., 2016). Here, permanent waters are represented by 100%, and permanent land surfaces by 0%, of water occurrence for a 30-meter by 30-meter grid.References:Pekel, J.-F., A. Cottam, N. Gorelick, A.S. Belward, 2016, High-resolution mapping of global surface water and its long-term changes. Nature, 540, 418-422.Wang, S., J. Li, and H. A. J. Russell, 2023, Methods for Estimating Surface Water Storage Changes and Their Evaluations. Journal of Hydrometeorology, DOI: https://doi.org/10.1175/JHM-D-22-0098.1.