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We have found 60 datasets for the keyword "stratification". You can continue exploring the search results in the list below.
Datasets: 104,048
Contributors: 42
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60 Datasets, Page 1 of 6
Natural Regions and Subregions of Alberta
This dataset defines the ecological areas of Alberta known as the Natural Regions and Natural Subregions, as defined in 2004/2005. This dataset is intended to allow for the stratification of the province of Alberta based on ecological criteria. Natural Regions are the largest mapped ecological units in Alberta's classification system. They are defined geographically on the basis of landscape patterns, notably vegetation, soils and physiographic features. Natural Subregions are subdivisions of a Natural Region, generally characterized by vegetation, climate, elevation, and latitudinal or physiographic differences within a given Region.The intended scale of use of this product is 1:250 000. This version is 2005 Final. Linework changes from the previous Natural Subregion delineation are due both to better information and refined subregion definitions. Note that the Athabasca Plain subregion has been moved into the Boreal Natural Region and that the Boreal Highlands has now been split into Lower and Upper. There is an accompanying report, published 2006: https://albertaparks.ca/media/2942026/nrsrcomplete_may_06.pdf
Maritimes 4VSW Research Vessel Survey
“4VSW” missions focus on the eastern half of the Scotian Shelf, and occur primarily in March, but sets in both February, and April are also present in the data. These missions use a unique stratification scheme intended to optimize the abundance estimates of cod. Collected data includes total catch in numbers and weights by species. Length frequency data is available for most species, as are the age, sex, maturity and weight information for a subset of the individual animals. Other data such as ageing material, genetic material, and stomach contents are often also collected, but are stored elsewhere.Cite this data as: Clark, D., Emberley, J. Data of Maritimes 4VSW Research Vessel Survey. Published January 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/a851ce30-e216-4d7d-a29c-05631eef140e
Growth and Yield Samples - All Status
**NOTE** This dataset is going to be replaced by the Data Catalogue layer: [Forest Inventory Ground Plots - Public Access](https://catalogue.data.gov.bc.ca/dataset/6d6d115f-4cc2-4141-909e-3344b3a72bcf) This new layer links to the updated database for all Forest Analysis and Inventory Branch ground sample plots. Growth and Yield dataset is a provincial data set that comprised of Permanent Sample Plots (PSP). Researchers such as GY modellers and those wanting to know the position of all samples will use the all status view to better understand the spatial distribution of historic measurement data including samples that are currently destroyed or inactive
Growth and Yield Samples - Active Status
**NOTE** This layer is being replaced with the new authoritative source for PSP location: [Growth and Yield Plots - Active Status](https://catalogue.data.gov.bc.ca/dataset/5da8d02e-cdd8-40f8-b77e-d359f0e67dcd) Growth and Yield dataset is a provincial data set that comprised of Permanent Sample Plots (PSP). The Ministries and resource developers will want the active sample locations to determine where there are recognized feature conflicts with any resource development
Growing Degree Days
Growing degree days (GDDs) are used to estimate the growth and development of plants and insects during the growing season. Growing Degree Day are computed by subtracting a base value temperature from the mean daily temperature and are assigned a value of zero if negative. Base temperatures are a point below which development does not occur for the organism in question. Growing Degree Day products are created for base 0, 5, 10 and 15 degrees Celsius.GDD values are only accumulated during the Growing Season, April 1 through October 31.
Ratio of new immigrant arrivals (2001 – 2016) to older immigrant arrivals (before 2001) by census subdivision, 2016
This service shows the ratio of immigrants who arrived between 2001 and 2016 to immigrants who arrived before 2001, by census subdivision, 2016. The data is a custom extraction from the 2016 Census - 25% sample data.This data pertains to persons in private households who are immigrants by their period of immigration. 'Immigrant' includes persons who are, or who have ever been, landed immigrants or permanent residents. Such persons have been granted the right to live in Canada permanently by immigration authorities. Immigrants who have obtained Canadian citizenship by naturalization are included in this category. In the 2016 Census of Population, 'Immigrant' includes immigrants who landed in Canada on or prior to May 10, 2016. 'Period of immigration' refers to the period in which the immigrant first obtained landed immigrant or permanent resident status. For additional information refer to the 2016 Census Dictionary for 'Immigrant status' and 'Period of immigration'.For additional information refer to the 2016 Census Dictionary for 'Immigrant status' and 'Period of immigration'.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.
Statistically downscaled multi-model ensembles of maximum temperature
Statistically downscaled multi-model ensembles of maximum temperature are available at a 10km spatial resolution for 1951-2100. Statistically downscaled ensembles are based on output from twenty-four Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCM). Daily maximum temperature from GCM outputs were downscaled using the Bias Correction/Constructed Analogues with Quantile mapping version 2 (BCCAQv2). A historical gridded maximum temperature dataset of Canada (ANUSPLIN) was used as the downscaling target. The 5th, 25th, 50th, 75th and 95th percentiles of the monthly, seasonal and annual ensembles of downscaled maximum temperature (°C) are available for the historical time period, 1951-2005, and for emission scenarios, RCP2.6, RCP4.5 and RCP8.5, for 2006-2100. 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.
Percentage of population with postsecondary certificate, diploma or degree by census subdivision, 2016
This service shows the percentage of population aged 25 to 64 years in private households with a postsecondary certificate, diploma or degree by census subdivision, 2016. The data is from the Census Profile, Statistics Canada Catalogue no. 98-316-X2016001.This data pertains to the population aged 25 to 64 years in private households by the highest level of education that a person has successfully completed. Persons with a post-secondary certificate, diploma or degree includes those with an apprenticeship or trades certificate or diploma; a college, CEGEP or other non-university certificate or diploma; a university certificate or diploma below bachelor level or a university certificate, diploma or degree at bachelor level or above. For additional information refer to the 2016 Census Dictionary for ' Highest certificate, diploma or degree'.For additional information refer to the 2016 Census Dictionary for ' Highest certificate, diploma or degree'. To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census subdivision” web service, accessible in the data resources section below.
Ratio of new immigrant arrivals (2001 – 2016) to older immigrant arrivals (before 2001) by census division, 2016
This service shows the ratio of immigrants who arrived between 2001 and 2016 to immigrants who arrived before 2001, by 2016 census division. The data is a custom extraction from the 2016 Census - 25% sample data.This data pertains to persons in private households who are immigrants by their period of immigration. 'Immigrant' includes persons who are, or who have ever been, landed immigrants or permanent residents. Such persons have been granted the right to live in Canada permanently by immigration authorities. Immigrants who have obtained Canadian citizenship by naturalization are included in this category. In the 2016 Census of Population, 'Immigrant' includes immigrants who landed in Canada on or prior to May 10, 2016. 'Period of immigration' refers to the period in which the immigrant first obtained landed immigrant or permanent resident status. For additional information refer to the 2016 Census Dictionary for 'Immigrant status' and 'Period of immigration'.For additional information refer to the 2016 Census Dictionary for 'Immigrant status' and 'Period of immigration'.To have a cartographic representation of the ecumene with this socio-economic indicator, it is recommended to add as the first layer, the “NRCan - 2016 population ecumene by census division” web service, accessible in the data resources section below.
Wildfire Year/dNBR/Mask 1985-2015
Wildfire Year/dNBR/Mask 1985-2015Wildfire change magnitude 85-15. Spectral change magnitude for wildfires that occurred from 1985 and 2015. The wildfire change magnitude included in this product is expressed via differenced Normalized Burn Ratio (dNBR), computed as the variation between the spectral values before and after the change event. This dataset is composed of three layers: (1) binary wildfire mask, (2) year of greatest wildfire disturbance, and (3) differenced Normalized Burn Ratio (dNBR) transformed for data storage efficiency to the range 0-200. The actual dNBR value is derived as follows: dNBR = value / 100. Higher dNBR values are related to higher burn severity. The information outcomes represent 30 years of wildfires in Canada's forests, derived from a single, consistent spatially-explicit data source in a fully automated manner. Time series of Landsat data with 30-m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by wildfire for the period 1985-2015 for Canada's 650 million hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. (Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution and time series change detection methods applied, as well as information on independent accuracy assessment of the data.Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., 2015. An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. (Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., 2015. Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. (Hermosilla et al. 2015b).Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011
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