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We have found 24 datasets for the keyword " sirr". You can continue exploring the search results in the list below.
Datasets: 106,102
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24 Datasets, Page 1 of 3
Inventory of crash barriers and impact mitigators
The City of Montreal's Road Infrastructure Department (SIRR) is responsible for managing and maintaining restraint systems on its territory. Knowledge of the inventory of these assets is an important basic element in the process of identifying needs and planning interventions. As a result, the SIRR has developed an inventory of these assets on [the City's administrative arterial network (RAAV)] (https://donnees.montreal.ca/dataset/reseau-arteriel-administratif).Restraints under this mandate include crash barriers and impact mitigators. These assets are identified throughout the arterial network (RAAV) of the 19 boroughs of the City of Montreal. **This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Ministry of Natural Resources Region
Ministry of Natural Resources (MNR) regions were created to help manage ministry programs and resources at a regional level. Extents of the regions were originally compiled by description of: metes and bounds, topographic features, geographic township boundaries, territorial district boundaries, etc. MNR regions consist of a number of districts. This product requires the use of geographic information system (GIS) software.
Medium Resolution Digital Elevation Model (MRDEM) - CanElevation Series
**ATTENTION! The files in this dataset are designed for streaming, not downloading. For the best experience, please follow the instructions available in the resources.**In replacement of the former Canadian Digital Elevation Model (CDEM) that is no longer supported, the Medium Resolution Digital Elevation Model (MRDEM) product is a multi-source product that integrates elevation data from the Copernicus DEM** acquired during the TanDEM-X Mission (AIRBUS, 2022), and the High Resolution Digital Elevation Model data derived from airborne lidar. This product provides a complete, 30 meters resolution, nationwide coverage for Canada. It includes a Digital Terrain Model (DTM), a Digital Surface Model (DSM) and other derived products. The spatial coverage extends into the USA, where needed, to provide coverage for cross-border watersheds in support of hydrological studies and applications. The MRDEM-30-DSM is partially based on the GLO-30 version of the Copernicus DEM** (hereafter named GLO-30). Since elevation values from the GLO-30 are referenced to the EGM2008 geoid model, they were transformed to the Canadian Height Reference System of 2013 (CGVD2013), using the CGG2013 geoid model. Where available, the MRDEM-30-DSM integrates surface data from the lidar-derived HRDEM mosaic, resampled from 1 m to 30 m. The process to generate the MRDEM-30-DTM is more complex. Where available, the HRDEM Mosaic derived from lidar was used since it already provides reliable terrain elevation values. The HRDEM Mosaic data used was resampled from 1m to 30m. Elsewhere, the processing workflow combines a forest removal model and a settlement removal model that is applied to the GLO-30 values in order to estimate the terrain elevation values. Both datasets are projected to Canada Atlas Lambert NAD83 (CSRS) (EPSG:3979).The MRDEM is referenced to the CGVD2013 which is the reference standard for orthometric heights across Canada.The product Medium Resolution Digital Elevation Model (MRDEM) is part of the CanElevation Series created in support to the National Elevation Data Strategy implemented by NRCan.** This product was in part produced using Copernicus WorldDEM-30 © DLR e.V. 2010-2014 and © Airbus Defence and Space GmbH 2014- 2018 provided under COPERNICUS by the European Union and ESA; all rights reserved.The organisations in charge of the Copernicus program by law or by delegation do not incur any liability for any use of the Copernicus WorldDEM-30.
Vegetation Inventory Photo Points - Whitehorse - 10k
This point feature indicates the location of photo centre points during data capture for the Whitehorse Forest Inventory. 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. New mapping and DTM were available for this project based on that 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)
Sharp-tailed Grouse - Wildlife Key Area - 250k
Wildlife Key Areas (WKA) are locations used by wildlife for critical, seasonal life functions. WKAs are identified by interpreting observed locations of wildlife at key times of year, not through intensive habitat assessment. Polygons derived from interviews with locals and from GIS interpretation of wildlife/habitat surveys. GIS interpretation follows criteria specific for taxon and/or populations of taxon. Key Areas are based on observed locations of wildlife at key times of year, not on habitat assessment. With new information, boundaries and designations of Key Areas can change and additional Key Areas can be identified. Furthermore, Key Areas are not the only sites important for wildlife. Other information sources can identify other sites important for wildlife for reasons outside the scope of the WKA Inventory Program. Updates to Key Areas occur only periodically. For the most current information, please consult with the Regional Biologist for your area of interest. If you have questions or would like to contribute to the WKA database, please contact the WKA Inventory Program ( [wka@yukon.ca](mailto:wka@yukon.ca) ).Distributed from [GeoYukon](https://mapservices.gov.yk.ca/GeoYukon/) by the [Government of Yukon](https://yukon.ca/) . 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)
Placer Baseline Unsurveyed - 50k
Baseline of a creek or river means a traverse line following the general direction of the centre bottom lands of the valley of the creek or riverDistributed 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)
Runways - 25k
This dataset provides polygon extents of the runway surfaces at airports, aerodromes and airstrips across the territory.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)
Ontario Road Network (ORN) Composite
The Ontario Road Network (ORN) Composite product is a segmented derivative of the ORN Road Net Element (ORNELEM) data class. You can use it for mapping and general spatial analysis. Road segment information includes: * addressing * full street name * alternate street name * speed limit * number of lanes * pavement status * road class * jurisdiction * route number * direction of traffic flow * shield type information The ORN is a provincewide geographic database of over 250,000 km of: * municipal roads * provincial highways * resource and recreational roads The ORN is the authoritative source of roads data for the Government of Ontario. This product is derived from the [ORN Road Net Element](https://geohub.lio.gov.on.ca/datasets/mnrf::ontario-road-network-orn-road-net-element/about) data class. It combines three types of geometry: * road elements * ferry connections * virtual roads This product also includes additional road feature layers including: * blocked passages * underpasses * toll points * structures
Annual Crop Inventory 2022
In 2022, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery for all Canadian provinces, in support of a national crop inventory. New this year, a map of the agricultural regions in the Yukon Territory was also produced. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Landsat-9,Sentinel-2), and radar (RCM) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincialcrop insurance companies in Alberta, Saskatchewan, Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change; Ontario Ministry of Agriculture, Food and Rural Affairs; University of Guelph - Ridgetown campus; British Columbia Ministry of Agriculture; and data collection supported by our regional AAFC Research and Development Centres in St. John's, Kentville, Fredericton, Guelph, Summerland and Whitehorse.
Digital Soil Mapping
## Purpose The Ministry of Agriculture, Food and Agribusiness (OMAFA) is responsible for Ontario’s provincial soil maps and maintains and update them as necessary. Digital Soil Mapping (DSM) is a modern methodology using spatially explicit soils and environmental data to predict soil variation throughout a landscape at a high, consistent resolution. Digital soil maps are being rolled out throughout Ontario’s agricultural land base to update provincial soil maps. ## Reach Provincial soil maps are used in many decision-making processes including: * land use planning * land evaluation * farming practices * best management practices * ecological monitoring * land resource mapping Potential users of this data include: * farmers * certified crop advisors * conservation authorities * academic researchers * land use planners ## Potential impacts Digital soil maps provide more accurate and precise soils data and enables improved management of soil resources across multiple stakeholders. This allows for better decision making to maximize land use efficiency, improve economic efficiency of soil resources and promote soil health and soil conservation. ## Technical description Digital soil mapping combines geo-referenced soil observations with geo-referenced environmental layers to mathematically model soil variation as a function of environment variation. These models are based on well established, but often complex relationships, between soil properties and topography, biology, geology and hydrology.
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