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We have found 688 datasets for the keyword " cartographie superficielle". You can continue exploring the search results in the list below.
Datasets: 103,380
Contributors: 42
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688 Datasets, Page 1 of 69
Database of areas at risk of flooding (BDZI)
Data on flood zones include mapping carried out as part of the mapping program of the Canada-Quebec Convention from 1976 to 2001, the Program for the determination of flood ratings from 2001 to 2004 (PDCC), as well as the mapping carried out after that date by the Centre d'expertise du Québec (CEH) and its various partners.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Base Hydrography Point Event
The Base Hydrography Point Event layer contains hydrographic point features representing the locations of water or water related features captured through the 1:20000 Provincial Base Mapping Project, the 1:50000 Resource Access Mapping Program, the Alberta Vegetation Inventory Program and the Federal Government National Topographic Data Base 1:50000 mapping.
Southern Ontario Surficial 3D Model
To support improved groundwater geoscience knowledge for southern Ontario, a regional 3-D model of the surficial geology of southern Ontario has been developed as a part of a collaboration between the Ontario Geological Survey and the Geological Survey of Canada. Covering approximately 66,870 km2 in area, the model is a synthesis of existing geological models, surficial geology mapping, and subsurface data. The model is a simplified 9-layer reclassification of numerous mapped local surficial sediment formations in places over 200 m thick with a total volume of approximately 2,455 km3. The model integrates 1:50,000 scale surficial geology mapping with 90 m bathymetrically corrected topographic digital elevation model (DEM) and 8 existing local 3-D models. Archival subsurface data include 10,237 geotechnical and stratigraphic boreholes, 3,312 picks from geophysical surveys, 15,902 field mapping sites and sections, 537 monitoring and water supply wells and 282,995 water well records. Roughly corresponding to regional aquifer and aquitard layers, primary model layers are (from oldest to youngest): Bedrock, Basal Aquifer, Lower Sediment, Regional Till, Post Regional Till Channel Fill, Glaciofluvial Sediment, Post Regional Till Mud, Glaciolacustrine Sand and Recent Sediment / Organics. Modelling was completed using an implicit modelling application (LeapFrog®) complemented by an expert knowledge approach to data classification and rules-based Expert System procedure for data interpretation and validation. An iterative cycle of automated data coding, intermediate model construction and manual data corrections, expert evaluations, and revisions lead to the final 3-D model. A semi-quantitative confidence assessment has been made for each model layer surface based on data quality, distribution and density. This surficial geology model completes the development of a series of regional 3-D geological and hydrogeological models for southern Ontario.
Ground ice map of Canada - relict ice
The mapping depicts the relative abundance of relict (buried glacier) ice preserved in upper permafrost at a national scale. The mapping is updated and based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019). The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations between geological and environmental conditions and ground ice type and abundance. It provides a foundation for hypothesis testing related to broad-scale controls on ground ice formation, preservation, and melt.
Ground ice map of Canada - wedge ice
The mapping depicts the relative abundance of wedge ice in upper permafrost at a national scale. The mapping is based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019). The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations between geological and environmental conditions and ground ice type and abundance. It provides a foundation for hypothesis testing related to broad-scale controls on ground ice formation, preservation, and melt.
Surficial Geology of the Wapiti Map Area (NTS 83L) (GIS data, polygon features)
This dataset was digitized from an unedited version of surficial geology map of the Wapiti area, NTS 83L, compiled by Laurence Andriashek in 1983 (Alberta Geological Survey Open File Report 1983-23). Mapping scale is 1:250,000.
Ground ice map of Canada - segregated ice
The mapping depicts the relative abundance of segregated ice in upper permafrost at a national scale. The mapping is based on modelling by O'Neill et al. (2019) (https://doi.org/10.5194/tc-13-753-2019). The mapping offers an improved depiction of ground ice in Canada at a broad scale, incorporating current knowledge on the associations between geological and environmental conditions and ground ice type and abundance. It provides a foundation for hypothesis testing related to broad-scale controls on ground ice formation, preservation, and melt.
Canada’s National Highway System
NHS as officially accepted by the Council of Ministers, mapping by Transport Canada.
Shore Unit Classifications - Polygon
The Shore Unit Classifications Polygons depict the most current areas of Shorezone mapping for the Province of British Columbia. Shorezone is an aerial imaging, habitat classification, and mapping system used to inventory alongshore and across-shore geomorphological and biological attributes of the coast. Habitat attributes are interpreted from oblique aerial imagery acquired during the lowest tides of the year. The mapping project was first developed as an oil spill response tool for British Columbia, and now ShoreZone extends from Oregon to Alaska and has many other uses including ecological studies, marine conservation planning, coastal flooding and vulnerability assessments, and community education.
Historic - Flood Susceptibility Mapping
This series of historic flood susceptibility maps comes from an XGBboost machine learning model trained on major floods from 2005 to 2023. The trained model is then run for each year from 2000 to 2023, including unique temporal characteristics of temperature, precipitation, land use land cover and Normalized Difference Vegetation Index (NDVI), to predict the flood susceptibility of any given year.This dataset forms part of a broader collection of flood susceptibility datasets, offering related information and analyses. The collection includes an overview page with associated publications, historic susceptibility values, temporal trends, and future projections.- [Collection – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/1074f781-85d3-4c86-86cb-fd1c339197dc)- [Trends and Extremes – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/3202e0a0-0afb-4120-b102-b0c41f0fb9eb)- [Future - Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/c00f95a3-7bab-4d28-b9cc-b30f06b5afd2)
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