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We have found 53 datasets for the keyword "gamme". You can continue exploring the search results in the list below.
Datasets: 103,466
Contributors: 42
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53 Datasets, Page 1 of 6
Range Units
A Range Unit is an administrative area established to assist in the management of the range program. Typically made up of one or more pastures. Generally, one or more Range Units make up a Stock Range
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
Utilities Line - 50k
1:50,000 NTDB Utility Features Line Based on Edition 2.x.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)
Ungulate Winter Range - Approved
The dataset contains approved legal boundaries for ungulate winter range and specified areas for ungulate species.
Non Legal Planning Features - Current - Line
A spatially identified line on land and/or water that has been mapped for specific land and/or resource uses as determined through a strategic land and resource planning process. This layer represents non-legalized planning lines only, thus the direction given within the planning designation is policy only and is not legally enforceable. This layer contains line geometries. Current SLRP non-legal line features are included in this layer. For all SLRP non-legal line features (retired and current), please see the layer [Non Legal Planning Features - All - Line](https://catalogue.data.gov.bc.ca/dataset/f72a0619-0a7a-4ade-bf1a-946339aedfd1).
Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region
Species distribution models (SDMs) are tools that combine species observations of occurrence, abundance, or biomass with environmental variables to predict the distribution of a species in unsampled locations. To produce accurate predictions of occurrence, abundance or biomass distribution, a wide range of physical and/or biological variables is desirable. Such data is often collected over limited or irregular spatial scales, and require the application of geospatial techniques to produce continuous environmental surfaces that can be used for modelling at all spatial scales. Here we provide a review of 102 environmental data layers that were compiled for the entire spatial extent of Fisheries and Oceans Canada’s (DFO) Maritimes Region. Variables were obtained from a broad range of physical and biological data sources and spatially interpolated using geostatistical methods. For each variable we document the underlying data distribution, provide relevant diagnostics of the interpolation models and an assessment of model performance, and present the final standard error and interpolation surfaces. These layers have been archived in a common (raster) format at the Bedford Institute of Oceanography to facilitate future use. Based on the diagnostic summaries in this report, a subset of these variables has subsequently been used in species distribution models to predict the distribution of deep-water corals, sponges, and other significant benthic taxa in the Maritimes Region.Cite this data as: Beazley, Lindsay; Guijarro, Javier, Lirette; Camille; Wang, Zeliang; Kenchington, Ellen (2020). Characteristics of Environmental Data Layers for Use in Species Distribution Modelling in the Maritimes Region. Published July 2023. Ocean Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/34a917cb-a0e3-403c-91c7-af3dc20628b1
Aquifer Vulnerability, Groundwater Geoscience Program
A measure of the intrinsic susceptibility of an aquifer representing the tendency or likelihood for contaminants to reach a specified position in the groundwater system after introduction at some location above the uppermost aquifer. The method used to create the dataset is described in the metadata associated with the dataset. The dataset is a general assessment of the vulnerability of the hydrogeological unit considered as a whole. It features the local and regional qualifiers in a controlled vocabulary list referring to the extent where the vulnerability value is valid. Because the vulnerability is assessed using contextual indices linked to the regional hydrogeological settings, it is very unlikely to have an homogeneous range of data throughout the various hydrogeologic units across the country for this dataset. Hence, the vulnerability dataset will not qualify as an homogeneous dataset. A more generic reclassification using for examples three vulnerability classes could then be used to solve this problem. Each sub layers used to create the global vulnerability index can be provided along with the final vulnerability index map.
GEPS Forecasted Accumulated Precipitation - 384 hrs
This polygon layer displays ensemble-based, medium-range precipitation forecasts from the Global Ensemble Prediction System (GEPS), offering a probabilistic view of future rainfall or snowfall over a 16‑day horizon. It aids in uncertainty analysis, risk assessment, and strategic resource planning.Ensemble Approach: GEPS runs multiple perturbed members of ECCC’s GEM model, capturing a range of atmospheric evolutions and yielding probability distributions for precipitation. Global Domain: Similar coverage to the GDPS but focuses on ensemble mean, spreads, and probabilities rather than a single deterministic outcome. Longer-Range Outlook: Extends up to 16 days, supporting risk-based planning for potential floods, extended rainfall events, or dryness. Data Utility: Allows decision-makers to weigh confidence levels in precipitation scenarios, vital for water management, agriculture, and emergency contingency strategies.
Electoral districts 2017 - Saint-Hyacinthe
Electoral division of the 2017 election.**Collection context** Creation of districts in collaboration with the legal services and the electoral data of the Chief Electoral Officer (DGE). Balancing of districts according to anthropogenic constraints and number of voters.**Collection method** Computer-aided mapping.**Attributes*** `ID_SEC_DIS` (`long`): Identifier* `NAME_DISTRI` (`varchar`): District name* `NO` (`long`): District number* `AREA` (`varchar`): Area* `ADVISORY_NAME` (`varchar`): Name of the advisor* `SOURCE` (`varchar`): Source* `DATE_CREAT` (`date`): Creation date* `DATE_MODIF` (`date`): Date of modification* `USER_MODIF` (`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).**
GHA Hunting Season Table
The purpose of this dataset is to give an accurate representation of the game hunting boundaries in Manitoba.The purpose of this dataset is to give an accurate representation of the game hunting boundaries in Manitoba.Game Hunting Areas (GHAs) are defined under the Hunting Areas and Zones Regulation (220/86) of The Wildlife Act (CCSM c. W130). Game Hunting Areas are used to support boundaries for species-specific hunting seasons, harvest allocations, bag limits and associated regulations. Refer to the Hunting Areas and Zones Regulation for GHA boundary descriptions.Fields included (Alias (Field Name): Field description)OBJECTID (OBJECTID): sequential unique whole numbers that are automatically generated GHA (GHA): the number assigned to each Game Hunting Area Shape_Length (Shape_Length): the length of the feature in internal units Shape_Area (Shape_Area): area of the feature in internal units squared
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