Each pixel value corresponds to the best quality maximum NDVI recorded within that pixel over the week specified. Poor quality pixel observations are removed from this product. Observations whose quality is degraded by snow cover, shadow, cloud, aerosols, and/or low sensor zenith angles are removed (and are assigned a value of “missing data”). In addition, negative Max-NDVI values, occurring where R reflectance > NIR reflectance, are considered non-vegetated and assigned a value of 0. This results in a Max-NDVI product that should (mostly) contain vegetation-covered pixels. Max-NDVI values are considered high quality and span a biomass gradient ranging from 0 (no/low biomass) to 1 (high biomass).

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.

The ‘Circa 1995 Landcover of the Prairies’dataset is a geospatial raster data layer portraying the rudimentaryland cover types of all grain-growing areas of Manitoba, Saskatchewan, Alberta and northeastern British Columbia at a 30-metre resolution for the 1995 timeframe. It is the collection of all the classified imagery (1993 to 1995) of the Western Grain Transition Payment Program (WGTPP) assembled into a single seamless raster data layer.

The “Land Cover for Agricultural Regions of Canada (circa 2000), Date Index” dataset is a geospatial data layer containing polygon features representing the Landsat scene number, associated dates and other products that were incorporated into the thematic land cover classification which is contained within the AAFC Landcover (circa 2000) product.

The VMap1 collection is a legacy product that is no longer supported. It may not meet current government standards. VMap1 is a vector digital topographic reference product developed by Natural Resources Canada (NRCan) and The Department of National Defence (DND). VMap1 complies with international military specifications vector map, level 1. There are 24 VMap1 libraries covering the Canadian territory. The National Topographic Data Base (NTDB) at scale of 1:250 000 is the main source used to populate the Canadian VMap1 Libraries. Administrative Boundaries from Statistics Canada are used to add international borders, provincial and Indian reserve limits. NRCan paper maps at scale of 1:250 000 and the information in the Canadian Geographical Names Data Base (CGNDB) are used to capture the names. The JOG (Joint Operations Graphic) paper maps were used by DND for the production of libraries 37, 38 and 66. Topographic features mainly from the NTDB have not been updated. VMap1 is published once and no product revision is planned.

BTM ( Baseline Thematic Mapping) Landsat Image Catalogue Acquisition Dates. This polygon coverage contains the date of capture of the Landsat images making up the seamless BC Landsat image catalogue. This is not a multipart feature

[IS] Skýjalaus miðgildismósaík úr Sentinel-2 myndum frá júlí og ágúst árin 2023 til 2025, í 10 m upplausn, með böndunum B2, B3, B4, B5, B6, B7, B8, B8A, B11 og B12. 60 m böndum var sleppt. [EN] Cloudless median mosaic of Sentinel 2 in July and August of the year 2023 to 2025 in 10m resolution with bands B2, B3, B4, B5, B6, B7, B8, B8A, B11, B12. Skipped were 60m bands.

Each pixel value corresponds to the actual number (count) of valid Best-quality Max-NDVI values used to calculate the mean weekly values for that pixel. Since 2020, the maximum number of possible observations used to create the Mean Best-Quality Max-NDVI for the 2000-2014 period is n=20. However, because data quality varies both temporally and geographically (e.g. cloud cover and snow cover in spring; cloud near large water bodies all year), the actual number (count) of observations used to create baselines can vary significantly for any given week and year.