This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census subdivision. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.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.

This service shows the ratio of persons aged 0 to 14 and 65 and over (children and seniors) versus persons aged 15 to 64 (working-age) by census division. The data is a custom extraction from the 2016 Census - 100% data.This data pertains to the total population by age. 'Age' refers to the age at last birthday before the reference date, that is, before May 10, 2016. For additional information refer to 'Age' in the 2016 Census Dictionary.For additional information refer to 'Age' in the 2016 Census Dictionary.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.

Landsat-derived forest age for Canada 2022Satellite-based forest age map for 2022 across Canada's forested ecozones at a 30-m spatial resolution. Remotely sensed data from Landsat (disturbances, surface reflectance composites, forest structure) and MODIS (Gross Primary Production) are utilized to determine age. Age can be determined where disturbance can be identified directly (disturbance approach) or inferred using spectral information (recovery approach) or using inverted allometric equations to model age where there is no evidence of disturbance (allometric approach). The disturbance approach is based upon satellite data and mapped changes and is the most accurate. The recovery approach also avails upon satellite data plus logic regarding forest succession, with an accuracy that is greater than pure modeling. Given the lack of widespread recent disturbance over Canada's forests, the allometric approach is required over the greatest area (86.6%). Using information regarding realized heights and growth and yield modeling, ages are estimated where none are otherwise possible. Trees of all ages are mapped, with trees >150 years old combined in an - old tree - category. This product was developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS).See Maltman et al. (2023) for an overview of the methods, data, image processing, as well as information on agreement assessment using Canada's National Inventory (NFI). Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C., 2023. Estimating and mapping forest age across Canada's forested ecosystems. Remote Sensing of Environment 290, 113529. ( Maltman et al. 2023).

Landsat-derived forest age for Canada 2022Satellite-based forest age map for 2022 across Canada's forested ecozones at a 30-m spatial resolution, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Remotely sensed data from Landsat (disturbances, surface reflectance composites, forest structure) and MODIS (Gross Primary Production) are utilized to determine age. Age can be determined where disturbance can be identified directly (disturbance approach) or inferred using spectral information (recovery approach) or using inverted allometric equations to model age where there is no evidence of disturbance (allometric approach). The disturbance approach is based upon satellite data and mapped changes and is the most accurate. The recovery approach also avails upon satellite data plus logic regarding forest succession, with an accuracy that is greater than pure modeling. Given the lack of widespread recent disturbance over Canada's forests, the allometric approach is required over the greatest area (86.6%). Using information regarding realized heights and growth and yield modeling, ages are estimated where none are otherwise possible. Trees of all ages are mapped, with trees >150 years old combined in an - old tree - category.See Maltman et al. (2023) for an overview of the methods, data, image processing, as well as information on agreement assessment using Canada's National Inventory (NFI). Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C., 2023. Estimating and mapping forest age across Canada's forested ecosystems. Remote Sensing of Environment 290, 113529. ( Maltman et al. 2023).

Landsat-derived forest age for Canada 2022Satellite-based forest age map for 2022 across Canada's forested ecozones at a 30-m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Remotely sensed data from Landsat (disturbances, surface reflectance composites, forest structure) and MODIS (Gross Primary Production) are utilized to determine age. Age can be determined where disturbance can be identified directly (disturbance approach) or inferred using spectral information (recovery approach) or using inverted allometric equations to model age where there is no evidence of disturbance (allometric approach). The disturbance approach is based upon satellite data and mapped changes and is the most accurate. The recovery approach also avails upon satellite data plus logic regarding forest succession, with an accuracy that is greater than pure modeling. Given the lack of widespread recent disturbance over Canada's forests, the allometric approach is required over the greatest area (86.6%). Using information regarding realized heights and growth and yield modeling, ages are estimated where none are otherwise possible. Trees of all ages are mapped, with trees >150 years old combined in an - old tree - category.See Maltman et al. (2023) for an overview of the methods, data, image processing, as well as information on agreement assessment using Canada's National Inventory (NFI). Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C., 2023. Estimating and mapping forest age across Canada's forested ecosystems. Remote Sensing of Environment 290, 113529. ( Maltman et al. 2023).

"Fall" missions occur primarily in October and November, but sets from September and December are also present in the data. 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."Fall" cruises occur in September, October, November and December.Cite this data as: Clark, D., Emberley, J. Data of Maritimes Fall Research Vessel Survey. Published January 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/5f82b379-c1e5-4a02-b825-f34fc645a529

“Summer” missions occur in June, July and August and these focus on the Scotian Shelf and Bay of Fundy (i.e. 4VWX 5Yb, expanding recently to include the Laurentian Channel and Georges Bank (5Zc). 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.“Summer” cruises occur in May, June, July and August and these focus on the Scotian Shelf and Bay of Fundy (i.e. 4VWX).Cite this data as: Clark, D., Emberley, J. Data of MARITIMES SUMMER RESEARCH VESSEL SURVEYS. Published January 2021. Population Ecology Division, Fisheries and Oceans Canada, Dartmouth, N.S. https://open.canada.ca/data/en/dataset/1366e1f1-e2c8-4905-89ae-e10f1be0a164

Biological samples of Geoduck Clams have been collected during surveys in British Columbia as part of the broader survey objectives of determining Geoduck density, distribution and population structure. Samples of Geoducks were collected from 41 locations throughout British Columbia between 1993 and 2002. Clams were measured for total weight, shell length, shell weight and were aged. Biological parameters are presented here for individual clams sampled. See Bureau D., W. Hajas, N.W. Surry, C.M. Hand, G. Dovey and A. Campbell. 2002. Age, size structure and growth parameters of Geoducks (Panopea abrupta, Conrad 1849) from 34 locations in British Columbia sampled between 1993 and 2000. Can Tech. Rep. Fish. Aquat. Sci. 2413: 84 p. and Bureau D., W. Hajas, C.M. Hand and G. Dovey. 2003. Age, size structure and growth parameters of Geoducks (Panopea abrupta, Conrad 1849) from seven locations in British Columbia sampled in 2001 and 2002. Can. Tech. Rep. Fish. Aquat. Sci. 2494: 29 p.

This polygon dataset identifies the habitat suitability rating for Flammulated Owl (FLOW) within the Cariboo Natural Resource Region. The habitat suitability rating is based on Biogeoclimatic Ecosystem Classification (BEC), forest age class, crown closure, tree species, harvest activity, silviculture activity, slope and aspect.

The Yukon Geological Survey (YGS) has compiled over 195 surficial geology maps into a standardized GIS format, providing approximately 80% coverage of the territory. The maps range in scales from 1:250,000 to 1:10,000 with spatial overlap between scales. The original maps were produced by various agencies, including the Geological Survey of Canada, YGS, Yukon Government, universities, and the City of Whitehorse.All original feature descriptions have been preserved and also converted to standardized values using the Yukon terrain classification system. The compilation includes 4 GIS datasets and supporting documents available for download via [YGS integrated data system](https://data.geology.gov.yk.ca/Compilation/33) (YGSIDS) or GeoYukon. A .lyr file is [provided](https://data.geology.gov.yk.ca/Compilation/33) to symbolize feature classes and differentiate overlapping maps at different scales. Additionally, there is a surficial geology map index.The polygon attributes captured include surficial material, texture, age, surface expression, and geomorphological processes.Line features include geological contacts, glacial limits, glacial landforms (cirques, arêtes, eskers, meltwater channels, moraines), and non-glacial landforms (faults, lineaments, landslides, escarpments).Point features include field station, fossil and sample locations, glacial landforms (erratics, kames, kettles, drumlins, flutings), permafrost features (pingos, palsas, patterned ground, thermokarst depressions), and other non-glacial landforms (landslides, tors).The map index provides information on each map publication such as author, map title, map scale, publisher.These data are valuable for land-use applications in the territory, including: mineral and placer exploration, geotechnical engineering, infrastructure planning, granular resource assessments, permafrost modeling, agricultural assessments, forest management, and biophysical or ecological land classification.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)