Surface Type describes the type of surface material used on road

IBL - Imagery, basemaps, and land cover (imageryBaseMapsEarthCover) Basemaps. For example, resources describing land cover, topographic maps, and classified and unclassified images

The Common Attribute Schema for Forest Resource Inventories (CASFRI) is a Canadian forest resource inventory data repository. Forest resource inventory datasets in CASFRI are harmonized to a common data model so that data collected by different agencies following different standards can be used together. Participating provincial, territorial and federal government departments and agencies share current and historical map-based forest resource inventory datasets through CASFRI so that their data are available to users who’s areas of interest span multiple jurisdictions. CASFRI was originally developed by academic researchers (Cumming et al., https://doi.org/10.1139/cjfr-2014-0102). This flavour of CASFRI (CASFRIv5) was developed anew in collaboration with academic researchers at the University of Laval to provide a government version of CASFRI that is findable, accessible, interoperable, and reusable. It uses the most up-to-date forest inventory data provided by participating provincial, territorial, and federal government departments and agencies. CASFRIv5 is hosted on the Canadian Council of Forest Ministers’ data portal, the National Forest Information System (http://nfis.org).

To assess the current distribution of kelp beds and other macroalgae in Nova Scotia and Southwest New Brunswick, subtidal drop camera surveys were performed from 2022-2023 at 140 sites. For each site, a GoPro HERO 10 camera was towed along a deep (7-12m) and shallow (3-5m) depth contour until 20 images were acquired per depth. Where possible, species were identified from photos, with particular care given to kelps (defined here as orders Laminariales and Tilopteridales) and fucoids (order Fucales). Crust-forming algae was not counted. Percent cover was calculated using a 10x10 point grid overlaid on each image and recording the dominant cover type at each point. The depth (in meters) of each photo after correcting for tide height ranged from ~0.5m to ~12m. Depths were corrected to chart datum (lowest astronomical tide) using tide predictions from the nearest tide station, taken from tides.gc.ca. Sampling was performed between July and October. Cite this data as: Krumhansl K, Brooks C, Lowen B, DiBacco C, (2025). Camera Surveys of the Subtidal Flora of Nova Scotia and Southwest New Brunswick 2022-2023. Version 1.7. Fisheries and Oceans Canada. Samplingevent dataset. https://ipt.iobis.org/obiscanada/resource?r=camera_surveys_of_the_subtidal_flora_of_nova_scotia_2022-2023&v=1.7For additional information please see:Krumhansl K.A., Brooks C.M., Lowen B., O’Brien J., Wong M., DiBacco C. Loss, resilience and recovery of kelp forests in a region of rapid ocean warming. Annals of Botany 2024 Mar 8; 133(1):73-92. Brooks C.M., Krumhansl K.A. 2023. First record of the Asian Antithamnion sparsum Tokida, 1932 (Ceramiales, Rhodophyta) in Nova Scotia, Canada. BioInvasions Records 12(3):745-725.

Wall-to-wall map of water bodies across Canada's forested ecosystems for the year 2022, derived from the "water" class of the annual Virtual Land Cover of Engine (VLCE) product. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The VLCE maps are based on Landsat image time-series composites and represent annual land cover classifications from 1984 to 2022 at a spatial resolution of 30 m. The classification process integrates forest change information and ancillary topographic and hydrologic variables, applying a regional modeling framework based on a 150x150 km tiling system ( Hermosilla et al., 2022). Training data are drawn from multiple land cover sources and selected proportionally to land cover distributions using a distance-weighted approach. Classifications are refined over time using a Hidden Markov Model to ensure consistency and reduce classification noise between years.Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C. 2022. Land cover classification in an era of big and open data: Optimizing localized implementation and training data selection to improve mapping outcomes. Remote Sensing of Environment. 268, 112780. https://doi.org/10.1016/j.rse.2021.112780. ( Hermosilla et al., 2022)Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W. 2018. Disturbance-Informed Annual Land Cover Classification Maps of Canada's Forested Ecosystems for a 29-Year Landsat Time Series. Canadian Journal of Remote Sensing. 44(1) 67-87. https://doi.org/10.1080/07038992.2018.1437719.( Hermosilla et al., 2018)

A novel, bay – scale (i.e. tens of km) survey method was employed to examine algal populations on the southwestern shore of Cape Breton, Canada, for the purposes of potential economic exploitation. Since traditional remote sensing methods were unlikely to be successful in these waters, underwater video and acoustic methods were applied. A transponder positioned towfish housing video camera and sidescan sonar was hauled along predetermined transects perpendicular to shore to provide information on bottom type and algal cover. The towfish data were used to ground truth echosounder data (bottom type and macrophyte canopy height) collected along 5, 10 and 20 m depth contours. The survey area was divided into six zones comprising a range of exposure, depth and bottom types. Destructive quadrat samples were collected at each depth plus shore stations to provide biomass estimates. Over thirty five taxa were enumerated, indicating depths and zones of common occurrence. Ascophyllum was abundant at some of the shore stations. The genera Chondrus, Cystoclonium, Desmarestia, Fucus, Phyllophora, Polysiphonia, and Saccharina were common at 5 m. Desmarestia and Saccharina dominated at 10 m with wet weights sometimes over 1 kg·m-2. Agarum dominated at 20 m. The towfish / echosounder grid sampling system was relatively coarse in order to cover the 140 km2 survey area within 12 days. As a result, the survey did not produce spatially detailed information. However, adequate information was gathered to describe the general characteristics of bottom type and algal cover by zone and for focusing further exploration--Abstract, p. vi.Cite this data as: Vandermeulen H. Data of: A Novel Video and Acoustic Survey of the Seaweeds of Isle Madame. Published: August 2021. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/ebdd8f91-9131-45f0-8aec-aba9f65e3fae

The National Rail Network (NRWN) is a geometric and attributive description of the Canadian rail network.The NRWN product consists of the features classes: Track Segment, Railway Crossing, Railway Station, Marker Post, Junction and Railway Structure. Descriptive attributes include amongst others: Track Classification, Track Name, Track Operator, Track User, Track Owner, Subdivision Name, Junction Type, Crossing Type, Level of Crossing, Warning System, Transport Canada Identifier, Station Name, Station Type, Station User, Structure Type.

RESULTS opening's forest cover poylgons with silviculture component provided. Current forest cover subimssion into RESULTS must contain attribute and map information. However, there are historical forest cover polygon infomration where maps are not available. Forest Cover is provided at three critical milestones of at harvesting, at regeneration, and at free growing. This is a part o fthe Silviculture and Land Status Tracking dataset, which includes tracking achievement of silviculture obligations on Crown Land

RESULTS opening's forest cover polygons with inventory component provided. Current forest cover submissions into RESULTS must contain attribute and map information. However, there are historical forest cover polygon information where maps are not available. Forest Cover is provided at three critical milestones of at harvesting, at achieved regeneration and at free growing. This is part of the Silviculture and Land status Tracking dataset, which includes tracking achievement of silviculture obligations on Crown Land

Land cover information is necessary for a large range of environmental applications related to climate impacts and adaption, emergency response, wildlife habitat, etc. In Canada, a 2008 user survey indicated that the most practical land cover data is provided in a nationwide 30 m spatial resolution format, with an update frequency of five years. In response to this need, the Canada Centre for Remote Sensing (CCRS) has generated a 30 m land cover map of Canada for the base year 2010, as well as this 2015 land cover map. This land cover dataset is also the Canadian contribution to the 30 m spatial resolution 2015 Land Cover Map of North America, which is produced by Mexican, American and Canadian government institutions under a collaboration called the North American Land Change Monitoring System (NALCMS). This land cover dataset for Canada is produced using observation from Operational Land Imager (OLI) Landsat sensor. An accuracy assessment based on 806 randomly distributed samples shows that land cover data produced with this new approach has achieved 79.90% accuracy with no marked spatial disparities.- [Land Cover of Canada - Cartographic Product Collection](https://open.canada.ca/data/en/dataset/11990a35-912e-4002-b197-d57dd88836d7)