Home /Search
Search datasets
We have found 270 datasets for the keyword " éléments géomorphologiques". You can continue exploring the search results in the list below.
Datasets: 103,380
Contributors: 42
Results
270 Datasets, Page 1 of 27
Pacific Marine Ecological Classification System and its Application to the Northern and Southern Shelf Bioregions
Description:Biophysical Units: Under the Pacific Marine Ecological Classification System (PMECS; DFO 2016; Rubidge et al. 2016), biophysical units are areas of distinct physiographic and oceanographic conditions and processes that shape species composition at spatial extents of 1000s of km. Geomorphic units:Geomorphic units or geozones are discrete geomorphological structures at the scale of 100s of km that are assumed to have distinctive biological assemblages (e.g., plateaus, ridges, seamounts, canyons). Although the spatial scale of geomorphic units is nested within biophysical units, a single geomorphic unit such as a trough may span more than one biophysical unit. The following 5 layers are included in this geodatabase:1. Biophysical_Units_L4A - Predicted PMECS Biophysical Units (Level 4A) output from the random forest analysis2. Biophysical_Units_L4B - Predicted PMECS Biophysical Units (Level 4B) output from the random forest analysis3. Biophysical_Units_ProbAssign_L4AB - Layer showing the probability that a grid cell was assigned to a given biophysical unit in the final random forest predictive modelling step4. Cluster_L4AB - Layer showing the output of species assemblage cluster analysis5. Geomorphic_Units - Geomorphic units for the BC coast that combines geomorphic units produced by Rubidge et al. 2016) and Proudfoot and Robb (2022).Methods:Biophysical Units:Rubidge et al. (2016) used a two-step process to identify biophysical units in British Columbia. First, a cluster analysis based on the similarity of species composition was used to group sites with similar species into distinct biological assemblages. Second, a random forest analysis was used to identify environmental correlates of the biological assemblages identified by the cluster analysis and to predict and assign the biological assemblage present in areas with too few biological data. Two different similarity thresholds were used to identify two levels (4A, 4B) of biophysical units; see Rubidge et al. (2016) for details. Indicator species for each assemblage (biophysical unit) were also identified.Geomorphic units:Rubidge et al. (2016) used the benthic terrain modeller (BTM) tool with broad and fine-scale benthic positioning index (BPI) parameters to define geomorphic units on the continental shelf in the Northern Shelf Bioregion and the continental slope in both the Northern Shelf Bioregion and Southern Shelf Bioregion. In 2022, geomorphic units were produced for the Strait of Georgia and Southern Shelf Bioregions following the same methods as Rubidge et al. (2016) (Proudfoot and Robb 2022). The geomorphic units produced as part of the PMECS process were merged with the geomorphic units produced for the Strait of Georgia and Southern Shelf bioregions to produce a continuous spatial data product representing geomorphic units for the Canadian Pacific continental shelf and slope. After merging, the geomorphic units produced in 2016 were unchanged (i.e., they are consistent with the original geomorphic units described in Rubidge et al. 2016).Data Sources:From Rubidge et al. (2016): Species data was taken from Fisheries and Oceans Canada (DFO) standardized fisheries-independent research surveys: groundfish trawl and long-line (2003-2013), Tanner Crab trawl and trap (2000–2006), and Dungeness Crab trap (2000–2014). Environmental data came from NASA, the Canadian Hydrographic Service, Fisheries and Oceans Canada, Bio-ORACLE, and elsewhere (details in Rubidge et al. 2016). From Proudfoot and Robb (2022): bathymetry data came from Natural Resources Canada (details in Proudfoot and Robb 2022).Uncertainties:The data is intended for use at the bioregional scale, and caution should be used for finer-scale analyses.
Hydrology: Hydrologic Zone Boundaries of British Columbia
Zones that represent areas of homogeneous hydrologic and geomorphological characteristics
Urban furniture
Location of elements of urban furniture in the City of Repentigny.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Miscellaneous line
The dataset represents prominent linear (man-made or natural) features including: * cliffs * dykes * fences * walls * hedgerows * feature outlines * racetrack centre lines * racetrack edges We are no longer updating this data. It is best suited for historical research and analysis.
buildings
Geometric and conventional representation of building roofs in 2.5D plan. That is, the elements are shown in 2D planimetry in addition to altimetry information represented by point elevation dimensions.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Cratonic Elements
This map service provides access to the Cratonic Elements dataset shown on the GeoAtlas application.**Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse. They are therefore identical and share the same refresh schedule. This dataset shows the Cratonic Elements of the province of Saskatchewan at 1:1 million scale. This data was compiled using years of bedrock mapping, compiled into a file geodatabase feature class and output for public distribution.
Weather Elements on Grid based on the High Resolution Deterministic Prediction System
Weather Elements on Grid (WEonG) based on the High Resolution Deterministic Prediction System (HRDPS) is a post-processing system designed to compute the weather elements required by different forecast programs (public, marine, aviation, air quality, etc.). This system amalgamates numerical and post-processed data using various diagnostic approaches. Hourly concepts are produced from different algorithms using outputs from the pan-Canadian High Resolution Deterministic Prediction System (HRDPS-NAT).
Yukon road network
The Yukon Road Network is the authoritative source of road data for Yukon. This dataset represents road centrelines for road features administered by Government of Yukon. Road features not administered by Government of Yukon are supplied by Canvec Road Network. Please contact [transportation.gis@yukon.ca](mailto:transportation.gis@yukon.ca) with any errors or omissions.Distributed from [GeoYukon](https://yukon.ca/geoyukon) by the [Government of Yukon](https://yukon.ca/maps) . Discover more digital map data and interactive maps from Yukon's digital map data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)
Named geographic features
Data set contains geographical referencing information like: * type of feature or place * location coordinates * geographic township * municipal and map references Also contains places and background information behind their official naming like: * name status * naming date * name origin * naming history This layer used to be distributed under the name "Geographic Name Extent" but was modified to "Geographic Named Extent" in November 2011. [About Geographic Names](https://www.ontario.ca/page/geographic-names)
Granular Aggregate
This layer contains polygon features that represent granular aggregate deposits in New Brunswick. ‘Granular Aggregate’ is the term used to describe naturally occurring deposits of sand and gravel formed during the last ice-age when glaciers were melting and receding. These important resources, which are used for infrastructure construction and maintenance.
Tell us what you think!
GEO.ca is committed to open dialogue and community building around location-based issues and topics that matter to you.
Please send us your feedback