Home /Search
Search datasets
We have found 15 datasets for the keyword " lancer". You can continue exploring the search results in the list below.
Datasets: 106,579
Contributors: 42
Results
15 Datasets, Page 1 of 2
Landscape Units of British Columbia - Current
Landscape Units are spatially identified areas of land and/or water used for long-term planning of resource management activities. Landscape units are important for designing strategies and objectives to maintain landscape level biodiversity and for managing other forest resources. Landscape units are also used to initiate landscape unit plans, which provide direction on biodiversity, old growth forest retention, wildlife habitat maintenance and timber harvesting. LUs may also be used as planning zones for other stakeholders in addition to forest licensees and MOFR. This spatial view was created based on the selection from the layer LANDSCAPE UNIT SP, where the DATE OF RETIREMENT is null. Therefore, only current LU shapes are included in this layer
Walking trails
Trails designed for hiking.attribut:ID - Unique identifier**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Bicycle paths
Bicycle path routes.attribute:Name - Name of the bike pathTypeLane - Type of bike path**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Douglas-firs (Genus Pseudotsuga) in Canada2011
The raster maps depict a suite of forest attributes in 2001* and 2011 at 250 m by 250 m spatial resolution. The maps were produced using the k nearest neighbours method applied to MODIS imagery and trained from National Forest Inventory photo plot data. For detailed information about map production methods please refer to Beaudoin et al. (2018) "Tracking forest attributes across Canada between 2001 and 2011 using the k nearest neighbours mapping approach applied to MODIS imagery." Canadian Journal of Forest Research 48, 85-93. https://cfs.nrcan.gc.ca/publications?id=38979 The map datasets may be downloaded from https://nfi.nfis.org/downloads/nfi_knn2011.zip or https://open.canada.ca/data/en/dataset/ec9e2659-1c29-4ddb-87a2-6aced147a990 * Note: the forest composition (leading tree genus) map depicts forest attributes in 2001.How can this data be used?The resolution and accuracy of these map products are best suited for strategic-level forest reporting and informing policy and decision making at regional to national scales. As these maps also offer a coherent set of quantitative values for a large suite of forest attributes, they can be used as baseline information for modelling and in calculations such as merchantable forest volume or percentage of tree species. It is also possible to overlay these maps with other maps produced on the same pixel grid to make assessments of disturbance impacts, such as fire and harvests.
Martimes Summer Research Vessel Survey
“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
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.
Bicycle network
Rouyn-Noranda cycling network**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Latest Site Treatments - Multi-Agency Ground Plot (MAGPlot) Database: A Repository for pan-Canadian Forest Ground Plot Data
Multi-Agency Ground Plot (MAGPlot) database (DB) is a pan-Canadian forest ground-plot data repository. The database synthesize forest ground plot data from various agencies, including the National Forest Inventory (NFI) and 12 Canadian jurisdictions: Alberta (AB), British Columbia (BC), Manitoba (MB), New Brunswick (NB), Newfoundland and Labrador (NL), Nova Scotia (NS), Northwest Territories (NT), Ontario (ON), Prince Edward Island (PE), Quebec (QC), Saskatchewan (SK), and Yukon Territory (YT), contributed in their original format. These datasets underwent data cleaning and quality assessment using the set of rules and standards set by the contributors and associated documentations, and were standardized, harmonized, and integrated into a single, centralized, and analysis-ready database. The primary objective of the MAGPlot project is to collate and harmonize forest ground plot data and to present the data in a findable, accessible, interoperable, and reusable (FAIR) format for pan-Canadian forest research. The current version includes both historical and contemporary forest ground plot data provided by data contributors. The standardized and harmonized dataset includes eight data tables (five site related and three tree measurement tables) in a relational database schema. Site-related tables contain information on geographical locations, treatments (e.g. stand tending, regeneration, and cutting), and disturbances caused by abiotic factors (e.g., weather, wildfires) or biotic factors (e.g., disease, insects, animals). Tree-related tables, on the other hand, focus on measured tree attributes, including biophysical and growth parameters (e.g., DBH, height, crown class), species, status, stem conditions (e.g., broken or dead tops), and health conditions. While most contributors provided large and small tree plot measurements, only NFI, AB, MB, and SK contributed datasets reported at regeneration plot level (e.g., stem count, regeneration species). Future versions are expected to include updated and/or new measurement records as well as additional tables and measured and compiled (e.g., tree volume and biomass) attributes. MAGPlot is hosted through Canada’s National Forest Information System (https://nfi.nfis.org/en/maps). ---------------------------------------------------LATEST SITE TREATMENTS LAYER:---------------------------------------------------Shows the most recently applied treatment class for each MAGPlot site. These treatment classes are broad categories, with more specific treatment details available in the full dataset.-----------NOTES:----------- The MAGPlot release (v1.0 and v1.1) does not include NL and SK datasets due to pending Data Sharing Agreements, ongoing data processing, or restrictions on third-party sharing. These datasets will be included in future releases. While certain jurisdictions permit open or public data sharing, given that requestor signs and adheres the Data Use agreement, there are some jurisdictions that require a jurisdiction-specific request form to be signed in addition to the Data Use Agreement form. For the MAGPlot Data Dictionary, other metadata, datasets available for open sharing (with approximate locations), data requests (for other datasets or exact coordinates), and available data visualization products, please check all the folders in the “Data and Resources” section below. Coordinates in web services have been randomized within 5km of true location to preserve site integrityAccess the WMS (Web Map Service) layers from the “Data and Resources” section below. A data request must be submitted to access historical datasets, datasets restricted by data-use agreements, or exact plot coordinates using the link below.NFI Data Request Form: https://nfi.nfis.org/en/datarequestform---------------------------------ACKNOWLEDGEMENT:--------------------------------- We acknowledge and recognize the following agencies that have contributed data to the MAGPlot database: Government of Alberta - Ministry of Agriculture, Forestry, and Rural Economic Development - Forest Stewardship and Trade Branch Government of British Columbia - Ministry of Forests - Forest Analysis and Inventory Branch Government of Manitoba - Ministry of Economic, Development, Investment, Trade, and Natural Resources - Forestry and Peatlands Branch Government of New Brunswick - Ministry of Natural Resources and Energy Development - Forestry Division, Forest Planning and Stewardship Branch Government of Newfoundland & Labrador - Department of Fisheries, Forestry and Agriculture - Forestry Branch Government of Nova Scotia - Ministry of Natural Resources and Renewables - Department of Natural Resources and Renewables Government of Northwest Territories - Department of Environment & Climate Change - Forest Management Division Government of Ontario - Ministry of Natural Resources and Forestry - Science and Research Branch, Forest Resources Inventory Unit Government of Prince Edward Island - Department of Environment, Energy, and Climate Action - Forests, Fish, and Wildlife Division Government of Quebec - Ministry of Natural Resources and Forests - Forestry Sector Government of Saskatchewan - Ministry of Environment - Forest Service Branch Government of Yukon - Ministry of Energy, Mines, and Resources - Forest Management Branch Government of Canada - Natural Resources Canada - Canadian Forest Service - National Forest Inventory Projects Office
Dominant Genus - Common Attribute Schema for Forest Resource Inventories
The Common Attribute Schema for Forest Resource Inventories (CASFRI) is a Canadian forest resource inventory data repository. Forest resource inventory datasets in CASFRI are harmonized to a common data model so that data collected by different agencies following different standards can be used together. Participating provincial, territorial and federal government departments and agencies share current and historical map-based forest resource inventory datasets through CASFRI so that their data are available to users who’s areas of interest span multiple jurisdictions. CASFRI was originally developed by academic researchers (Cumming et al., https://doi.org/10.1139/cjfr-2014-0102). This flavour of CASFRI (CASFRIv5) was developed anew in collaboration with academic researchers at the University of Laval to provide a government version of CASFRI that is findable, accessible, interoperable, and reusable. It uses the most up-to-date forest inventory data provided by participating provincial, territorial, and federal government departments and agencies. CASFRIv5 is hosted on the Canadian Council of Forest Ministers’ data portal, the National Forest Information System (http://nfis.org).
Maples (Genus Acer) in Canada 2006
Canada's National Forest Inventory (NFI) sampling program is designed to support reporting on forests at the national scale. On the other hand, continuous maps of forest attributes are required to support strategic analyses of regional policy and management issues. We have therefore produced maps covering 4.03 × 106 km2 of inventoried forest area for the 2001 base year using standardised observations from the NFI photo plots (PP) as reference data. We used the k nearest neighbours (kNN) method with 26 geospatial data layers including MODIS spectral data and climatic and topographic variables to produce maps of 127 forest attributes at a 250 × 250 m resolution. The stand-level attributes include land cover, structure, and tree species relative abundance. In this article, we report only on total live aboveground tree biomass, with all other attributes covered in the supplementary data (http://nrcresearchpress.com/doi/suppl/10.1139/cjfr-2013-0401). In general, deviations in predicted pixel-level values from those in a PP validation set are greater in mountainous regions and in areas with either low biomass or sparse PP sampling. Predicted pixel-level values are overestimated at small observed values and underestimated at large ones. Accuracy measures are improved through the spatial aggregation of pixels to 1 km2 and beyond. Overall, these new products provide unique baseline information for strategic-level analyses of forests (https://nfi.nfis.org)Collection:- **[Canada's National Forest Inventory (NFI) 2006](https://open.canada.ca/data/en/dataset/e2fadaeb-3106-4111-9d1c-f9791d83fbf4)**
Tell us what you think!
GEO.ca is committed to open dialogue and community building around location-based issues and topics that matter to you.
Please send us your feedback