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We have found 68 datasets for the keyword " landslide". You can continue exploring the search results in the list below.
Datasets: 103,380
Contributors: 42
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68 Datasets, Page 1 of 7
Landslide areas
City of Trois-Rivières landslide zones**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Groundwater Flow, Groundwater Geoscience Program
Groundwater flow is the movement of water in an aquifer or hydrogeological unit. The dataset shows groundwater flow rate and direction in the hydrogeological unit. Groundwater flow is establish from piezometric surface map. The method used to create the dataset is described in the metadata associated with the dataset. The dataset represents a description of the flow, including rate in m/d, direction, date and source. Typically, the data provided will not be in the form of a shapefile with linked properties but in the form of an image that sketches the groundwater flow. The image could also represent a cross section of the hydrogeologic units showing the regional trends of the groundwater flow.
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).**
High Resolution Digital Elevation Model Mosaic (HRDEM Mosaic) - CanElevation Series
The High Resolution Digital Elevation Model Mosaic provides a unique and continuous representation of the high resolution elevation data available across the country. The High Resolution Digital Elevation Model (HRDEM) product used is derived from airborne LiDAR data (mainly in the south) and satellite images in the north. The mosaic is available for both the Digital Terrain Model (DTM) and the Digital Surface Model (DSM) from web mapping services. It is part of the CanElevation Series created to support the National Elevation Data Strategy implemented by NRCan. This strategy aims to increase Canada's coverage of high-resolution elevation data and increase the accessibility of the products.Unlike the HRDEM product in the same series, which is distributed by acquisition project without integration between projects, the mosaic is created to provide a single, continuous representation of strategy data. The most recent datasets for a given territory are used to generate the mosaic. This mosaic is disseminated through the Data Cube Platform, implemented by NRCan using geospatial big data management technologies. These technologies enable the rapid and efficient visualization of high-resolution geospatial data and allow for the rapid generation of dynamically derived products. The mosaic is available from Web Map Services (WMS), Web Coverage Services (WCS) and SpatioTemporal Asset Catalog (STAC) collections. Accessible data includes the Digital Terrain Model (DTM), the Digital Surface Model (DSM) and derived products such as shaded relief and slope.The mosaic is referenced to the Canadian Height Reference System 2013 (CGVD2013) which is the reference standard for orthometric heights across Canada.Source data for HRDEM datasets used to create the mosaic is acquired through multiple projects with different partners.Collaboration is a key factor to the success of the National Elevation Strategy. Refer to the “Supporting Document” section to access the list of the different partners including links to their respective data.
Future - Flood Susceptibility Mapping
This series of projected future flood susceptibility maps were generated using an XGBoost machine learning model trained on major floods from 2005 to 2023. The trained model was applied to future climate scenarios for 2050, 2070, and 2100, under two SSP scenarios: 245 and 585. The model uses temperature and precipitation time series to estimate potential future flood susceptibility. These maps represent model projections and should be interpreted as indicators of potential flood susceptibility, not precise forecasts.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)- [Historic - Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/ea1384df-bf4a-4743-97bb-870dc43f8d77)- [Trends and Extremes – Flood Susceptibility Mapping]( https://open.canada.ca/data/en/dataset/3202e0a0-0afb-4120-b102-b0c41f0fb9eb)
Canada's National Earthquake Scenario Catalogue - Mystery Lake - Magnitude 5.0
A magnitude 5 earthquake scenario along an unnamed fault located about 15 km north-northeast of Burnaby City Hall and directly south of Mt Elsay. This fault is not known to be active, but this scenario represents a small but damaging event in the North Shore Mountains.
Linear hydrography
Linear hydrographic network of the City of Rouyn-Noranda. The ditches ofdrainage is not included.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
3D model spatial extents, Groundwater Geoscience Program
The dataset shows the distribution and spatial extent of the 3D models that were created in the context of Canadian aquifers mapping projects from the Geological Survey of Canada.
Prospectivity model for magmatic nickel deposits
Prospectivity model highlights areas of Canada with the greatest potential for magmatic nickel deposits. The preferred prospectivity model is based on public geological, geochemical, and geophysical datasets that were spatially indexed using the H3 discrete global grid system. Each H3 cell is associated with a prospectivity value, or class probability, calculated from the best-performing gradient boosting machines model. Model results are filtered to include the top 20% of prospectivity values for visualization purposes.
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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