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We have found 76 datasets for the keyword "essential skills". You can continue exploring the search results in the list below.
Datasets: 106,057
Contributors: 42
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76 Datasets, Page 1 of 8
Essential Skills Training Projects
The Essential Skills Playbook projects map is developed to highlight projects featured as part of the “Essential Skills Playbook” published by the Office of Literacy and Essential Skills program (OLES) at Employment and Social Development Canada (ESDC). The playbook is developed as a showcase for sharing promising practices, case studies and partnerships, based on OLES projects that were funded through grants and contributions generally dating back to 2012. This map allows users to visualize OLES-funded projects and explore various data variables such as the targeted groups, essential skills, and industry sectors of each project.
Day Programs
Day programs provide employment, skills training, and day program opportunities for adults with disabilities in communities across Nova Scotia. They help people with disabilities develop meaningful relationships and expand skills that increase self-reliance and independence.
QGIS Training Tutorials: Using Spatial Data in Geographic Information Systems
Have you ever wanted to create your own maps, or integrate and visualize spatial datasets to examine changes in trends between locations and over time? Follow along with these training tutorials on QGIS, an open source geographic information system (GIS) and learn key concepts, procedures and skills for performing common GIS tasks – such as creating maps, as well as joining, overlaying and visualizing spatial datasets. These tutorials are geared towards new GIS users. We’ll start with foundational concepts, and build towards more advanced topics throughout – demonstrating how with a few relatively easy steps you can get quite a lot out of GIS. You can then extend these skills to datasets of thematic relevance to you in addressing tasks faced in your day-to-day work. Each tutorial video is also accompanied by a written script, providing a step-by-step reference that users can follow alongside the video or consult afterwards.
Forestry Education and Skills Resource Inventory
The dataset contains information relating to forestry-related trades education, associations, education, innovation, education/macro-credentials, institutions, and research.
NCC National Interest Land Mass (NILM)
The National Interest Land Mass (NILM) comprises a set of lands (mainly-NCC owned) considered essential to the functioning and experience of Canada's Capital. The NILM is the dominant tool guiding federal land management and ownership in support of Capital functions. The NILM was approved by Treasury Board in 1998 and the first update was approved in 2001. The 2020 NILM Update is the second update.
Time Series of Leaf Area Index for Reclamation Sites in Alberta 2016-2025
Leaf area index (LAI) quantifies the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per groud surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem,weather and climate modelling and monitoring. This product consists of time series of LAI observed between 2016 and 2025 over reclamation sites in Alberta, Canada May and October. The temporal frequency depends on cloud cover.
Peak Season Leaf Area Index of Canada from Medium Resolution Satellite Imagery
Leaf area index (LAI) quantified the density of vegetation irrespective of land cover. LAI quantifies the total foliage surface area per groud surface area. LAI has been identified by the Global Climate Observing System as an essential climate variable required for ecosystem,weather and climate modelling and monitoring. This product consists of annual maps of the maximum LAI during a grownig season (June-July-August) at 100m resolution covering Canada's land mass.
RADARSAT-1 - Heatmap of processed archived images
RADARSAT-1, in operation from 1995 to 2013, is Canada's first earth observation satellite. Developed and operated by the Canadian Space Agency (CSA), it has provided essential information to government, scientists and commercial users.Ultimately, the RADARSAT-1 mission generated the largest synthetic-aperture radar (SAR) data archive in the world. In April 2019, 36,000 images were made accessible through the Earth Observation Data Management System (eodms-sgdot.nrcan-rncan.gc.ca).A heatmap of processed images was produced by the CSA and helps visualize the density of images available by mapped sector during the RADARSAT-1 mission.
Vegetation Inventory Field Plots - Whitehorse - 10k
The field plots were used to help during the photo interpretation process. The temporary plots provided essential information to interpreters to relate photo observed attributes with field measurements. The field work for the inventory was carried out during the winter of 2004/2005 with the project delivered by the contractor in October 2005. Delineation was based on 1:10,000 black and white photography acquired by the City of Whitehorse in 2001. Mapping and DTM were available for this project based on the 2001 photography.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)
HRDPA Observed Accumulated Precipitation - Past 1day, 3 days & 7 days
This polygon layer visualizes actual observed precipitation polygons (classed by amounts) from the HRDPA product, offering a clear map-based depiction of recent rainfall or snowfall distribution. Observation periods depicted are past 1 day, past 3 days and past 7 days.This polygon layer is generated by taking HRDPA’s gridded precipitation data (6h, 24h, or multi-day accumulations) and grouping them into precipitation ranges, then polygonizing. Each feature shows how much precipitation truly fell in that zone. This is essential for event verification against forecasts, analyzing localized extremes, and updating water resource or flood models with real observed input.
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