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We have found 8 datasets for the keyword " snowshed". You can continue exploring the search results in the list below.
Datasets: 106,560
Contributors: 42
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8 Datasets, Page 1 of 1
Annual 30 m snow dynamics (2018-2019 to 2023-2024) – Canada
This catalog contains annual 30 m spatial resolution snow dynamics metrics for each snow-year from 2018-2019 to 2023-2024 for all of Canada. We gather all Landsat and Sentinel-2 images collected over Canada and identify the status of each pixel observation on the image collection date: snow (and ice), non-snow (i.e., land, water), unclear (i.e., clouds, shadows). We built an algorithm to calculate snow cover metrics for each pixel during each winter: start date of the first (and biggest) snow period [startF, startB], end date of the last (and biggest) snow period [endL, endB], number of days with snow cover in total (or in the biggest snow period) [lengthT, lengthB], number of snow periods (i.e., separated times with multiple confirmed snow observations) [periods], and a status classification (e.g., continuous snow, snow free) [status]. We do not obtain a clear observation every day because of satellite orbit frequencies and clouds. This means that timing-based metrics are identified by the middle date between two clear observations, with uncertainty quantified as half the length of the gap (i.e., ± days) [startF_u, startB_u, endL_u, endB_u, lengthT_u, lengthB_u].
Ungulate Winter Range - Proposed
An Ungulate Winter Range (UWR) is defined as an area that contains habitat that is necessary to meet the winter habitat requirements of an ungulate species. UWRs are based on current understanding of ungulate habitat requirements in winter, as interpreted by FLNR regional staff from current scientific and management literature, local knowledge, and other expertise from the region. UWRs within this set of data are currently in the review and consultation stage of the area designation process. As UWRs are designated they will be moved into the [Approved Ungulate Winter Range](http://catalogue.data.gov.bc.ca/dataset/ungulate-winter-range) dataset.
Ministry of Transportation (MOT) Road Structures
The Road Structures on the highway that are maintained by the Ministry. Highway structures include bridges, culverts (greater than or equal to 3m diameter), retaining walls (perpendicular height greater than or equal to 2m), sign bridges, tunnels/snowsheds. Information is recorded in the Bridge Management Information System (BMIS)
STAC-Item - SK Moose Jaw 2019 1m - Mosaic of High Resolution Digital Elevation Model (HRDEM) by LiDAR acquisition project
High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**
STAC-Item - NRCAN Red Deer 2019 1m - Mosaic of High Resolution Digital Elevation Model (HRDEM) by LiDAR acquisition project
High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**
STAC-Item - AB Upper Red Deer 1m - Mosaic of High Resolution Digital Elevation Model (HRDEM) by LiDAR acquisition project
High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**
STAC-Item - QC 600016 06 Lac Cognon MTM8 2016 1m - Mosaic of High Resolution Digital Elevation Model (HRDEM) by LiDAR acquisition project
High-Resolution Digital Elevation Model (HRDEM) generated from LiDAR. This data collection includes a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). The HRDEM product is referenced to the Canadian Geodetic Vertical Datum of 2013 (CGVD2013). Source data for HRDEM datasets is acquired through multiple projects with different partners. Since data is being acquired by project, there is no integration or edgematching done between projects. The data in this collection have been reprojected from the source reference system to the Canada Atlas Lambert projection (EPSG:3979). **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**
STAC-Item - 2018 - Annual 30 m snow dynamics (2018 2019 to 2023 2024) – Canada
This catalog contains annual 30 m spatial resolution snow dynamics metrics for each snow-year from 2018-2019 to 2023-2024 for all of Canada. We gather all Landsat and Sentinel-2 images collected over Canada and identify the status of each pixel observation on the image collection date: snow (and ice), non-snow (i.e., land, water), unclear (i.e., clouds, shadows). We built an algorithm to calculate snow cover metrics for each pixel during each winter: start date of the first (and biggest) snow period [startF, startB], end date of the last (and biggest) snow period [endL, endB], number of days with snow cover in total (or in the biggest snow period) [lengthT, lengthB], number of snow periods (i.e., separated times with multiple confirmed snow observations) [periods], and a status classification (e.g., continuous snow, snow free) [status]. We do not obtain a clear observation every day because of satellite orbit frequencies and clouds. This means that timing-based metrics are identified by the middle date between two clear observations, with uncertainty quantified as half the length of the gap (i.e., ± days) [startF_u, startB_u, endL_u, endB_u, lengthT_u, lengthB_u]. **This third party metadata element follows the Spatio Temporal Asset Catalog (STAC) specification.**
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