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We have found 61 datasets for the keyword "rockyview". You can continue exploring the search results in the list below.
Datasets: 104,050
Contributors: 42
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61 Datasets, Page 1 of 7
Ski Resorts
Ski Resorts is a point dataset identifying the location of ski resorts in British Columbia.
Snowmobile Areas in Parks within the Cariboo Region
Designated play areas for snowmobiles in Tweedsmuir and Itcha-Ilgachuz Provincial Parks. [__Tweedsmuir Provincial Park Master Plan__](https://bcparks.ca/planning/mgmtplns/tweedsmuir/tweeds_mp.pdf?v=1618329316506) [__Itcha Ilgachuz Provincial Park Management Plan__](https://bcparks.ca/planning/mgmtplns/itcha_il/itcha_ilgachuz_mp.pdf?v=1618329451240) [__Itcha Ilgachuz Provincial Park Winter Recreation Areas Map (PDF)__](https://bcparks.ca/planning/mgmtplns/itcha_il/rec_winmap.PDF)
Benthoscape Map of German Bank
The data layer (.shp) presented is the result of an unsupervised classification method for classifying seafloor habitat on German Bank (off South West Nova Scotia, Canada). This method involves separating environmental variables derived from multibeam bathymetry (Slope, Curvature) and backscatter (principal components: Q1, Q2, and Q3) into spatial units (i.e. pixels) and classifying the acoustically separated units into 5 habitat classes (Reef, Glacial Till, Silt, Silt with Bedforms, and Sand with Bedforms) using in situ data (imagery). Benthoscape classes (synonymous to landscape classifications in terrestrial ecology) describe the geomorphology and biology of the seafloor and are derived from elements of the seafloor that were acoustically distinguishable.Unsupervised classifications (acoustic classifications) optimized at 15 classes using Idrisi CLUSTER method (pixel based)Number representing the benthoscape classes (CLASS) derived from in situ imagery and video (See Brown et al., 2012, Figure 3, Table 1).Benthoscape classes (See Brown et al., 2012, Figure 3).Reference:Brown, C. J., Sameoto, J. A., & Smith, S. J. (2012). Multiple methods, maps, and management applications: Purpose made seafloor maps in support of ocean management. Journal of Sea Research, 72, 1–13. https://doi.org/10.1016/j.seares.2012.04.009Cite this data as: Brown, C. J., Sameoto, J. A., & Smith, S. J. Data of: Benthoscape Map of German Bank. Published: February 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/b7f81d4a-2cb6-4393-b35b-e536ec63e834
Areas potentially exposed to landslides
Delineation of areas potentially exposed to landslides and protective bands.attributs:ID - Unique IdentifierType - Entity type**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Public parking
Municipal public parking.attributes:ID - Unique IDName - Parking nameNumber of parking spaces - Number of parking spaces**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Projected streets
Planned routes of new streets or street extensions.attribut:ID - Unique identifier**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Slope/Aspect Categories in Mule Deer Winter Range - Cariboo Region
Slope/aspect categories within mule deer winter range in the Cariboo Region.
Public parking areas - Saint-Hyacinthe
Surface layer of public parking areas in the city.**Collection context** Updated by engineering department technicians.**Collection method** Technical drawing.**Attributes*** `ID_STAT` (`integer`): Identifier* `TYPE` (`varchar`): Type* `NB_CASE` (`integer`): Number of boxes* `NB_CASE_HDP` (`integer`): Number of HDP boxes* `PLACE` (`varchar`): Location* `AREA` (`numeric`): Area* `SOURCE` (`varchar`): Source* `DATE_CREATION` (`smalldatetime`): Creation date* `DATE_MODIFICATION` (`smalldatetime`): Date of modification* `USER_MODIFICATION` (`varchar`): Modified byFor more information, consult the metadata on the Isogeo catalog (OpenCatalog link).**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Colorado Structure
These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.
Projected Snow Depth change based on CMIP5 multi-model ensembles
Seasonal and annual multi-model ensembles of projected change (also known as anomalies) in snow depth based on an ensemble of twenty-eight Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models are available for 1900-2100. Projected change in snow depth is with respect to the reference period of 1986-2005 and expressed as a percentage (%). The 5th, 25th, 50th, 75th and 95th percentiles of the ensemble of snow depth change are available for the historical time period, 1900-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. Twenty-year average changes in snow depth (%) for four time periods (2021-2040; 2041-2060; 2061-2080; 2081-2100), with respect to the reference period of 1986-2005, for RCP2.6, RCP4.5 and RCP8.5 are also available in a range of formats. The median projected change across the ensemble of CMIP5 climate models is provided. Note: Projections among climate models can vary because of differences in their underlying representation of earth system processes. Thus, the use of a multi-model ensemble approach has been demonstrated in recent scientific literature to likely provide better projected climate change information.
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