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We have found 328 datasets for the keyword " haute". You can continue exploring the search results in the list below.
Datasets: 103,401
Contributors: 42
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328 Datasets, Page 1 of 33
FRR - Losses and gains in forest areas in Montérégie - GéoMont 2023
This project was carried out thanks to the financial support of component 2.2 of the MAMAH Regions and Rurality Fund (FRR).The updates were made using orthophotos from spring 2020. The project covers the territory of the MRCs of Haut-Saint-Laurent, Haute-Yamaska, Haute-Yamaska, Roussillon, Rouville, Vaudreuil-Soulanges as well as the agglomeration of Longueuil.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
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).
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.
Northeast Pacific Monthly Mean Ocean Current Climatology (October - March)
This dataset provides 1/36-degree monthly mean ocean current climatology (October - March) in the Northeast Pacific. The climatological fields are derived from hourly ocean currents for the perid from 1993 to 2020, simulated using a high-resolution Northeast Pacific Ocean Model (NEPOM).
Level curves
Level curves with an equidistance of 1 m derived from a lidar survey conducted in 2024.attributes:ID - Unique IDSubtype - Master (1) or secondary (2) level curve SCORE - Elevation value (m) The High Resolution Digital Elevation Model (m) product The High Resolution Digital Elevation Model (HRDM) product is available on the Open Government website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Lot fabric improved
The spatial accuracy of the lot fabric for some townships has been improved through the Ontario Parcel, Township Realignment and Township Improvement projects. Improvements to the fabric may include: * road allowance widths * spatial changes to better represent the location of lot boundaries * more consistent concession names. Data is collected on an on-going basis. The time period "end date" may be more recent than indicated here.
Town
The Town dataset is comprised of all the polygons that represent Towns in Alberta. Town is a municipality type defined under the authority of the Municipal Government Act. The formation of a Town can occur if a majority of buildings are on parcels of land smaller than 1850 square metres and there is a population of 1000 or more.
Visual Landscape Inventory
The VLI identifies and delineates areas of visual sensitivity near communities and along travel corridors throughout the province. It includes information about the visual condition, characteristics and sensitivity to alteration. It also houses scenic area and established Visual Quality Objective ( VQO ) attributes.
Stock Range
A Stock Range is an administrative area established to coincide with local livestock association areas. Generally, stock ranges are made up of one or more range units. Stock ranges are found in select areas of the province where applicable; not all areas of the province contain stock ranges
Bay of Fundy Sea Scallop Meat Weight and Shell Height Data 2011 to 2023
This dataset represents meat weight and shell height data of commercial size Sea Scallop (Placopecten magellanicus; ≥ 80 mm shell height) from 2011-2023 from the Bay of Fundy Inshore Scallop Survey collected from June to mid-August. Wet meat weights were recorded to a tenth of a gram and shell heights are measured in millimeters. Meat weights and shell heights are sampled from a subset of scallops caught on survey and this detailed sampling is conducted from approximately half of the tows conducted. Each row in the dataset represents an individual scallop and contains information such as tow number, tow date, cruise name, geographical coordinates (decimal degrees, WGS 84) and the Scallop Production Area in which the tow took place. Survey protocols are documented in Glass (2017). This dataset contains tow data from a comparative survey conducted in 2012 (Smith et al., 2013). Further, these data correspond to the publication of Hebert et al. (2025).ReferencesGlass, A. 2017. Maritimes Region Inshore Scallop Assessment Survey: Detailed Technical Description. Can. Tech. Rep. Fish. Aquat. Sci. 3231: v + 32 p.Hebert, N, Sameoto, J.A., Keith, D.M., Murphy, O.A., Brown, C.J., Flemming, J. 2025. Interannual variability in the length–weight relationship can disrupt the abundance–biomass correlation of sea scallop (Placopecten magellanicus). ICES. J. Mar. Sci. Smith, S.J., Glass, A., Sameoto. J., Hubley, B., Reeves, A., and Nasmith, L. 2013. Comparative survey between Digby and Miracle drag gear for scallop surveys in the Bay of Fundy. DFO Can. Sci. Advis. Sec. Res. Doc. 2012/161. iv + 20 p.Cite this data as: Sameoto, J.A. Data of: Bay of Fundy Sea Scallop Meat Weight and Shell Height Data 2011 to 2023. Published: December 2025. Population Ecology Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/65d32794-2d81-4682-b0ea-8d8bbe907a58
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