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We have found 19 datasets for the keyword "gfq". You can continue exploring the search results in the list below.
Datasets: 105,253
Contributors: 42
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19 Datasets, Page 1 of 2
Range Units
A Range Unit is an administrative area established to assist in the management of the range program. Typically made up of one or more pastures. Generally, one or more Range Units make up a Stock Range
Solar Resource, NSRDB PSM Direct Normal Irradiance (DNI) - North American Cooperation on Energy Information
Average of the hourly Direct Normal Irradiance (DNI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE").The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.
Stock Range
A Stock Range is an administrative area established to coincide with local livestock association areas. Generally, stock ranges are made up of one or more range units. Stock ranges are found in select areas of the province where applicable; not all areas of the province contain stock ranges
Solar Resource, NSRDB PSM Global Horizontal Irradiance (GHI) - North American Cooperation on Energy Information
Average of the hourly Global Horizontal Irradiance (GHI) over 17 years (1998-2014). Data extracted from the National Solar Radiation Database (NSRDB) developed using the Physical Solar Model (PSM) by National Renewable Energy Laboratory ("NREL"), Alliance for Sustainable Energy, LLC, U.S. Department of Energy ("DOE").The current version of the National Solar Radiation Database (NSRDB) (v2.0.1) was developed using the Physical Solar Model (PSM), and offers users the solar resource datasets from 1998 to 2014). The NSRDB comprises 30-minute solar and meteorological data for approximately 2 million 0.038-degree latitude by 0.038-degree longitude surface pixels (nominally 4 km2). The area covered is bordered by longitudes 25° W on the east and 175° W on the west, and by latitudes -20° S on the south and 60° N on the north. The solar radiation values represent the resource available to solar energy systems. The AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) model uses half-hourly radiance images in visible and infrared channels from the GOES series of geostationary weather satellites, a climatological albedo database and mixing ratio, temperature and pressure profiles from Modern Era-Retrospective Analysis (MERRA) to generate cloud masking and cloud properties. Cloud properties generated using PATMOS-x are used in fast radiative transfer models along with aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary sources to estimate Direct Normal Irradiance (DNI) and Global Horizontal Irradiance (GHI). A daily AOD is retrieved by combining information from the MODIS and MISR satellites and ground-based AERONET stations. Water vapor and other inputs are obtained from MERRA. For clear sky scenes the direct normal irradiance (DNI) and GHI are computed using the REST2 radiative transfer model. For cloud scenes identified by the cloud mask, Fast All-sky Radiation Model for Solar applications (FARMS) is used to compute the GHI. The DNI for cloud scenes is then computed using the DISC model. The data in this layer is an average of the hourly GHI over 17 years (1998-2014). NOTE: The Geographical Information System (GIS) data and maps for solar resources for Global Horizontal Irradiance (GHI) and Direct Normal Irradiance (DNI) were developed by the U.S. National Renewable Energy Laboratory (NREL) and provided for Canada as an estimate. At present, neither the NREL data, nor the Physical Solar Model (PSM) on which the NREL data is based, have been either assessed or validated for the particular Canadian weather applications. A Canadian GHI map developed by the department of Natural Resources Canada (NRCan) is based on the State University of New York (SUNY) model and has been assessed and validated for the particular Canadian weather applications. The Canadian GHI map is available at http://atlas.gc.ca/cerp-rpep/en/.
Game Hunting Areas
The purpose of this dataset is to give an accurate representation of the game hunting boundaries in Manitoba.The purpose of this dataset is to give an accurate representation of the game hunting boundaries in Manitoba.Game Hunting Areas (GHAs) are defined under the Hunting Areas and Zones Regulation (220/86) of The Wildlife Act (CCSM c. W130). Game Hunting Areas are used to support boundaries for species-specific hunting seasons, harvest allocations, bag limits and associated regulations. Refer to the Hunting Areas and Zones Regulation for GHA boundary descriptions.Fields included (Alias (Field Name): Field description)OBJECTID (OBJECTID): sequential unique whole numbers that are automatically generated GHA (GHA): the number assigned to each Game Hunting Area Shape_Length (Shape_Length): the length of the feature in internal units Shape_Area (Shape_Area): area of the feature in internal units squared
CA FAO Forest (2019)
Satellite-based forest area consistent with FAO definitions for Canada. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The forest area is based on the Food and Agricultural Organization of the United Nations (FAO) definition. The FAO definition incorporates land use, whereby trees removed by fire and harvesting for instance, remain forest as the trees will return. The included map displays the current forest cover for year as noted (i.e. 2022), plus the satellite-based temporally informed forest area where tree cover has been temporarily lost due to stand replacing disturbances (i.e., fire, harvest). For an overview of the methods, data, image processing, as well as information on accuracy assessment see Wulder et al. (2020).Open Access: Wulder, M.A., T. Hermosilla, G. Stinson, F.A. Gougeon, J.C. White, D.A. Hill, B.P. Smiley. (2020). Satellite-based time series land cover and change information to map forest area consistent with national and international reporting requirements. Forestry: An International Journal of Forest Research 93(3), 331-34, https://doi.org/10.1093/forestry/cpaa0063 . ( Wulder et al. 2020)
FADM - Cascade Mountain Boundary
The spatial representation for a polygon defining the area of the province defined as west of the Cascade Mountains
Total forest volume 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)**
FADM - Tree Farm License Agreement Boundary (TFL)
This view reflects what is in the Tree Farm License Agreement. Once an agreement is signed additions and deletions and changes occur that are not reflected in this layer. If you would like to see the current boundary please use the FADM - Tree Farm License Current View (TFL). Further information on Tree Farm Licenses please visit this website: https://www2.gov.bc.ca/gov/content?id=A93E6DFD8C164AD19CD17880450289A3 The spatial representation for a Tree Farm License, which is an agreement entered into under Part 3, Division 5 of the Forest Act which grants the rights to harvest timber. A tree farm licence has a term of 25 years and requires a management plan providing for the establishment, management, and harvesting of timber in a described area (Crown and private land) on a sustained or perpetual yield basis
Manitoba Forest Management Units – Version 4
This feature class represents Manitoba's Forest Management Unit (FMU) boundaries.Forest Management Units (FMU's) define a forested area with common forest conditions that are managed in a similar manner. Forest Sections are comprised of FMU's. Forest inventories within Forest Management Units are analysed to determine allowable harvest limits of softwood and hardwood tree species within each Forest Management Unit. Version 3: The southern portion of FMU 67 within the Highrock Forest Section has been adjusted to align with base features captured in 2009. Additionally, an 11 hectare portion of the Saskatchewan River Forest Section (FMU 59) has been added to the Highrock Forest Section. Version 4: The northern portion of FMU 68 along the Rail Haul within the Highrock Forest Section has been adjust so that the boundary falls within water only. Additionally, version 4 splits the 'White Zone' forest section (FMU 76) by ecozones, creating FMU 76 (Taiga Shield), FMU 77 (Southern Arctic), FMU 78 (Hudson Plain) and FMU 79 (Boreal Shield). Version 4 is dated February 8, 2013. Fields Included: OBJECTID: Sequential unique whole numbers that are automatically generated . MANAGEMENT_UNIT_NUMBER : Management Unit (MU) number . S ECTION : Forest section number . SECTION_NAME : Forest section name .
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