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We have found 1,814 datasets for the keyword " vector data production". You can continue exploring the search results in the list below.
Datasets: 106,102
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1,814 Datasets, Page 1 of 182
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)
Benthic invertebrates in seagrass and bare soft sediments in Atlantic Nova Scotia
This dataset contains the abundance (per m²) and the biomass (mg dry per m²) of macrofauna (≥ 500µm) in eelgrass and adjacent bare soft sediments, collected at sites in the Atlantic of Nova Scotia from 2009 to 2013.Cite this data as: Wong M.C. Data of Benthic invertebrates in seagrass and bare soft sediments in Atlantic Nova Scotia Published May 2020. Coastal Ecosystems Science Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/05d5f46a-7f19-11ea-8a4e-1860247f53e3Publications: Wong, M. C., & Dowd, M. (2021). Functional trait complementarity and dominance both determine benthic secondary production in temperate seagrass beds. Ecosphere. 12(11), e03794. https://doi.org/10.1002/ecs2.3794Wong, M. C. (2018). Secondary Production of Macrobenthic Communities in Seagrass (Zostera marina, Eelgrass) Beds and Bare Soft Sediments Across Differing Environmental Conditions in Atlantic Canada. Estuaries and Coasts, 41, 536–548. https://doi.org/10.1007/s12237-017-0286-2
Agricultural Ecumene Boundary File - 1991
The national agricultural ecumene includes all dissemination areas with 'significant' agricultural activity. Agricultural indicators, such as the ratio of agricultural land on census farms relative to total land area, and total economic value of agricultural production, are used. Regional variations are also taken into account. The ecumene is generalized for small-scale mapping.A new version of the agricultural ecumene is generated every census years (in vector format) since 1986.This file was produced by Statistics Canada, Agriculture Division, Ottawa.
Agricultural Ecumene Boundary File - 1996
The national agricultural ecumene includes all dissemination areas with 'significant' agricultural activity. Agricultural indicators, such as the ratio of agricultural land on census farms relative to total land area, and total economic value of agricultural production, are used. Regional variations are also taken into account. The ecumene is generalized for small-scale mapping.A new version of the agricultural ecumene is generated every census years (in vector format) since 1986.This file was produced by Statistics Canada, Agriculture Division, Ottawa.
Principal Mineral Areas, Producing Mines, and Oil and Gas Fields (900A)
This dataset is produced and published annually by Natural Resources Canada. It contains a variety of statistics on Canada’s mineral production, and provides the geographic locations of significant metallic, nonmetallic and coal mines, oil sands mines, selected metallurgical works, helium facilities, and oil and gas fields for the provinces and territories of Canada.Related product:- **[Top 100 Exploration Projects](https://open.canada.ca/data/en/dataset/b64179f3-ea0f-4abb-9cc5-85432fc958a0)**
Ontario Vector Topographic Data Cache
The Ontario Vector Topographic Data Cache is a collection of topographic data, that has been preprocessed for fast, seamless display at predefined scales. The topographic data includes constructed and natural features that make up Ontario’s landscape. The cache provides limited data from areas outside Ontario’s boundaries, such as the United States and adjacent provinces and territories. __Technical information__ Two versions of the Topographic Data Cache are available: 1. The traditional raster version is available for a variety of GIS applications and is updated annually. 2. The vector version is suitable for online web map applications as well as modern GIS software and is updated twice a year. Contributing data layers may have different maintenance and update cycles. Some cache layers have been processed in a way that makes it easier for them to be displayed in a mapping product. Other layers are unchanged from the authoritative data. The cartographic symbology used in the data cache is intentionally muted to allow users to showcase their data. The Ontario Vector Topographic Data Cache is created from many source datasets, which are described in the Ontario Vector Topographic Data Cache user guide. If you are interested in getting this authoritative data, you can download it from the [Ontario GeoHub](http://www.ontario.ca/geohub). For instructions on getting a copy of either version of the cache for use in mapping applications, visit the [Ontario GeoHub](http://www.ontario.ca/geohub).
Agricultural Ecumene Boundary File - 2011
The national agricultural ecumene includes all dissemination areas with 'significant' agricultural activity. Agricultural indicators, such as the ratio of agricultural land on census farms relative to total land area, and total economic value of agricultural production, are used. Regional variations are also taken into account. The ecumene is generalized for small-scale mapping.A new version of the agricultural ecumene is generated every census years (in vector format) since 1986.This file was produced by Statistics Canada, Agriculture Division, Remote Sensing and Geospatial Analysis section, 2017, Ottawa.
Agricultural Ecumene Boundary File - 1986
The national agricultural ecumene includes all dissemination areas with 'significant' agricultural activity. Agricultural indicators, such as the ratio of agricultural land on census farms relative to total land area, and total economic value of agricultural production, are used. Regional variations are also taken into account. The ecumene is generalized for small-scale mapping.A new version of the agricultural ecumene is generated every census years (in vector format) since 1986.This file was produced by Statistics Canada, Agriculture Division, Ottawa.
Agricultural Ecumene Boundary File - 2001
The national agricultural ecumene includes all dissemination areas with 'significant' agricultural activity. Agricultural indicators, such as the ratio of agricultural land on census farms relative to total land area, and total economic value of agricultural production, are used. Regional variations are also taken into account. The ecumene is generalized for small-scale mapping.A new version of the agricultural ecumene is generated every census years (in vector format) since 1986.This file was produced by Statistics Canada, Agriculture Division, Remote Sensing and Geospatial Analysis section, 2017, Ottawa.
Agricultural Ecumene Boundary File - 2016
The national agricultural ecumene includes all dissemination areas with 'significant' agricultural activity. Agricultural indicators, such as the ratio of agricultural land on census farms relative to total land area, and total economic value of agricultural production, are used. Regional variations are also taken into account. The ecumene is generalized for small-scale mapping.A new version of the agricultural ecumene is generated every census years (in vector format) since 1986.This file was produced by Statistics Canada, Agriculture Division, Remote Sensing and Geospatial Analysis section, 2017, Ottawa.
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