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We have found 85 datasets for the keyword " donnee ouverte". You can continue exploring the search results in the list below.
Datasets: 103,380
Contributors: 42
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85 Datasets, Page 1 of 9
Quartz Staking Directions - 50k
A location line is defined as a straight line opened or indicated throughout between No. 1 and No. 2 location posts of a mineral claim and joining them.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)
Sites Registry (Open Government Licence)
This dataset is a subset of the Sites Registry dataset. The Sites Registry is a collection of locations that are important to government carrying out its business, including sharing information with citizens. Most locations have civic addresses and are government offices or facilities, e.g. hospitals, schools, post-secondary institutions, court houses, tourism centres. It is comprised of all sites licensed under the Open Government Licence – British Columbia. For more information see the [Sites Registry](https://catalogue.data.gov.bc.ca/dataset/5476ee87-0f59-4614-abf0-e653b4702aeb) catalogue record.
RESULTS - Openings svw
RESULTS Openings are administrative boundaries for areas harvested with silviculture obligations or natural disturbances with intended forest management activities on Crown Land. The RESULTS openings_svw is a spatial view made up of a number of tables containing information on disturbance dates, generalized bec, forest district, opening category, opening status, previous tree species, opening gross area, average slope, average elevation, aspect, along with maximum and minimum elevation values, and many more fields.
NCC Rideau Canal Skateway - Ice condition
Rideau Canal Skateway - Ice condition by sectionEach winter, the NCC transforms the historic Rideau Canal into the world’s largest skating rink. The Rideau Canal Skateway winds its way through the heart of the National Capital over a total length of 7.8 km. A UNESCO World Heritage Site, the Rideau Canal in winter becomes a treasure that is the pride of the National Capital and a signature destination.The skating season typically runs from January to early March, but it is weather-dependent. When open, the Skateway is free and accessible 7 days a week, 24 hours a day.When the Skateway is open, ice conditions are monitored by section twice daily, at approximately 8 am and 4 pm.
Local and Regional Greenspaces
This dataset contains spatial and attribute information for local and regional greenspaces in British Columbia. Local and regional greenspaces are municipal or regional district lands designated by local government agencies and managed for public enjoyment, ecosystem or wildlife values. Spatial boundaries were sourced from municipal and regional district web sites, which in some cases provide datasets under Open Government Licence, and in other cases, publicize parks and greenspaces on web maps or pdf maps. Boundaries were edge-matched to the ParcelMap BC cadastre. This spatial layer contains multipart polygons.
GeoAI - Change detection use case - Trois-Rivières
Temporal analysis of changes in Trois-Rivières, Québec, based on GeoAI features automatically extracted from satellite images acquired in 2013 and 2021-22. Simple geospatial analysis intersecting Statistics Canada's Open Database of Buildings, version 3 (ODB v3) with GeoAI multidate building features enables the detection of buildings observed in 2021-22 that were not detected in 2013. The addition of new buildings is a good indicator of urban development and/or sprawl.GeoAI enables temporal coverage of various areas in Canada, thus providing a useful tool for change detection and trend analysis at high resolution. While the series is still fairly new, and such examples are limited for the time being, NRCan strives to gradually increase its GeoAI data offering for both spatial and temporal coverage.For more information about the GeoAI - GeoBase Series, please visit the following link: https://open.canada.ca/data/en/dataset/74738ff5-5367-5958-9aee-98fffdcd1876
GeoAI - Change detection use case - Iqaluit
Temporal analysis of changes in the Iqaluit region, Nunavut, based on GeoAI features automatically extracted from satellite images acquired in 2012 and 2022. Simple geospatial analysis intersecting GeoAI multidate building features enables the detection of buildings observed in 2022 that were not detected in 2012. The addition of new buildings is a good indicator of urban development and/or sprawl.GeoAI enables temporal coverage of various areas in Canada, thus providing a useful tool for change detection and trend analysis at high resolution. While the series is still fairly new, and such examples are limited for the time being, NRCan strives to gradually increase its GeoAI data offering for both spatial and temporal coverage.For more information about the GeoAI - GeoBase Series, please visit the following link: https://open.canada.ca/data/en/dataset/74738ff5-5367-5958-9aee-98fffdcd1876
Distribution of peatlands in Canada using National Forest Inventory forest structure and ancillary land cover data (2011)
Organic soils in the boreal forest commonly store as much carbon as the vegetation above ground. While recent efforts through the National Forest Inventory has yielded new spatial datasets of forest structure across the vast area of Canada’s boreal forest, organic soils are poorly mapped. In this geospatial dataset, we produce a map primarily of forested and treed peatlands, those with more than 40 cm of peat accumulation and over 10% tree canopy cover. National Forest Inventory ground plots were used to identify the range of forest structure that corresponds to the presence of over 40 cm of peat soils. Areas containing that range of forest cover were identified using the National Forest Inventory k-NN forest structure maps and assigned a probability (0-100% as integer) of being a forested or treed peatland according to a statistical model. While this mapping product captures the distribution of forested and treed peatlands at a 250 m resolution, open, completely treeless peatlands are not fully captured by this mapping product as forest cover information was used to create the maps. The methodology used in the creation of this product is described in:Thompson DK, Simpson BN, Beaudoin A. 2016. Using forest structure to predict the distribution of treed boreal peatlands in Canada. Forest Ecology and Management, 372, 19-27. https://cfs.nrcan.gc.ca/publications?id=36751 This distribution uses an updated forest attribute layer current to 2011 from:Beaudoin A, Bernier PY, Villemaire P, Guindon L, Guo XJ. 2017. Species composition, forest properties and land cover types across Canada’s forests at 250m resolution for 2001 and 2011. Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Quebec, Canada. https://doi.org/10.23687/ec9e2659-1c29-4ddb-87a2-6aced147a990 Additionally, this distribution varies slightly from the original published in 2016 in that here slope data is derived from the CDEM: https://open.canada.ca/data/en/dataset/7f245e4d-76c2-4caa-951a-45d1d2051333 The above peatland probability map was further processed to delineate bogs vs fens (based on mapped Larix content via the k-NN maps), as well as an approximation of the extent of open peatlands using EOSD data. The result is a 9-type peatland map with a more complete methodology as detailed in: Webster, K. L., Bhatti, J. S., Thompson, D. K., Nelson, S. A., Shaw, C. H., Bona, K. A., Hayne, S. L., & Kurz, W. A. (2018). Spatially-integrated estimates of net ecosystem exchange and methane fluxes from Canadian peatlands. Carbon Balance and Management, 13(1), 16. https://doi.org/10.1186/s13021-018-0105-5 In plain text, the legend for the 9-class map is as follows:value="0" label="not peat" alpha="0"value="1" label="Open Bog" alpha="255" color="#0a4b32"value="2" label="Open Poor Fen" alpha="255" color="#5c5430"value="3" label="Open Rich Fen" alpha="255" color="#792652"value="4" label="Treed Bog" alpha="255" color="#6a917b"value="5" label="Treed Poor Fen" alpha="255" color="#aba476"value="6" label="Treed Rich Fen" alpha="255" color="#af7a8f"value="7" label="Forested Bog" alpha="255" color="#aad7bf"value="8" label="Forested Poor Fen" alpha="255" color="#fbfabc"value="9" label="Forested Rich Fen" alpha="255" color="#ffb6db"This colour scale is given in qml/xml format in the resources below. The 9-type peatland map from Webster et al 2018 was further refined slightly following two simple conditions: (1) any 250-m raster cell with greater than 40% pine content is classified as upland (non-peat); (2) all 250-m raster cells classified as water or agriculture via the NRCan North American Land Cover Monitoring System (https://doi.org/10.3390/rs9111098) is also classified as non-peatland (value of zero in the 9-class map. This mapping scheme was used at a regional scale in the following paper: Thompson, D. K., Simpson, B. N., Whitman, E., Barber, Q. E., & Parisien, M.-A. (2019). Peatland Hydrological Dynamics as A Driver of Landscape Connectivity and Fire Activity in the Boreal Plain of Canada. Forests, 10(7), 534. https://doi.org/10.3390/f10070534 And is reproduced here at a national scale. Note that this mapping product does not fully capture all permafrost peatland features covered by open canopy spruce woodland with lichen ground cover. Nor are treeless peatlands near the northern treeline captured in the training data, resulting in unknown mapping quality in those regions.
GeoAI - Change detection use case - Winnipeg
Temporal analysis of changes in Winnipeg, Manitoba, based on GeoAI features automatically extracted from satellite images acquired in 2013 and 2023. Simple geospatial analysis enables the detection of features present in 2023 that were not already there in 2013. The addition of new buildings is a good indicator of urban development and/or sprawl. Complementarily, an analysis of changes in the forest coverage from the GeoAI datasets is done. This analysis reflects the gains and losses between both dates.GeoAI enables temporal coverage of various areas in Canada, thus providing a useful tool for change detection and trend analysis at high resolution. While the series is still fairly new, and such examples are limited for the time being, NRCan strives to gradually increase its GeoAI data offering for both spatial and temporal coverage.For more information about the GeoAI - GeoBase Series, please visit the following link: https://open.canada.ca/data/en/dataset/74738ff5-5367-5958-9aee-98fffdcd1876
ACIMS Non-Sensitive Element Occurrences
An Element Occurrence (EO) is an area of land and/or water in which a species or ecological community is, or was, present. An Element is either a species (or subspecies taxa) or an ecological community, the Occurrence is the documented location. The EO concept is part of NatureServe methodology. This methodology is used throughout the NatureServe network. EOs are created based on the Element Occurrence Data Standard and are a derived product developed from submitted observations. An EO should have practical conservation value for the Element as evidenced by potential continued (or historical) presence and/or regular recurrence at a given location. For Species Elements, the EO often corresponds with the local population, but when appropriate may be a portion of a population (e.g., for long distance dispersers) or may be a group of nearby populations (e.g., metapopulation). For Ecological Community Elements, the EO may represent a stand or patch of a natural community, or a cluster of stands or patches of a natural community. This dataset contains Non-sensitive EOs. Non-Sensitive EOs are locations (i.e. occurrences) of species or communities that are rare (or of conservation concern for some other reason) and for which there are no restrictions regarding public access to location data (beyond agreeing to the Terms and Conditions detailed below). This data updates on a daily basis.
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