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We have found 19 datasets for the keyword " pli". You can continue exploring the search results in the list below.
Datasets: 103,401
Contributors: 42
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19 Datasets, Page 1 of 2
Prairie Landscape Inventory (PLI) - Mixed Grassland Accuracy
This raster file is to accompany the Prairie Landscape Inventory (PLI) - Mixed Grassland Classification, and depicts its estimated level of accuracy. Accuracy has been calculated based on peer-review research and gathered survey information from the PLI-Review Web Application.Download: here This raster file is to accompany the Prairie Landscape Inventory (PLI) - Mixed Grassland Classification, and depicts its estimated level of accuracy. Accuracy has been calculated based on peer-review research and gathered survey information from the PLI-Review Web Application. The Prairie Landscape Inventory (PLI) working team of Habitat Unit in the Fish, Wildlife and Lands Branch, Ministry of Environment aims to develop improved methods of assessing land cover and land use for conservation. Native grassland, in particular, has been one of the most hard to map at risk ecosystems because of difficulty for imagery classification methods to distinguish native from tame grasslands. Improved classification methods will provide valuable information for habitat suitability, identifying high biodiversity potential and invasion risk potential. This reliability map brings the understanding of classification accuracy (certainty) into a spatial scale prospective, illustrating the level of accuracy of the PLI Classification raster for each location. This map is scaled between 100 to 0, 100 is representing the highest accuracy, and 0 is absolutely the highest uncertainty. The Prairie Landscape Inventory (PLI) - Mixed Grassland Classification raster has a resolution of 10m and was based on machine learning analysis and remote sensing data of Sentinel-1 and Sentinel-2 imagery.
Standardized Precipitation Evapotranspiration Index (SPEI)
The Standardized Precipitation Evapotranspiration Index (SPEI) is computed similarly to the SPI. The main difference is that SPI assesses precipitation variance, while SPEI also considers demand from evapotranspiration which is subtracted from any precipitation accumulation prior to assessment.Unlike the SPI, the SPEI captures the main impact of increased temperatures on water demand.
Industrial parks
Industrial sectors.attributs:ID - Unique identifierName - Industrial park name**This third party metadata element was translated using an automated translation tool (Amazon Translate).**
Recreational Features Inventory
The RFI identifies areas of land and water encircling a recreation feature or combination of features that support, or have the potential to support, one or more recreation activities. These areas are rated for their significance or importance to recreation and for their sensitivity to alteration
National Agroclimate Series of Derived Indicators (NASDI) - Standardized Precipitation Index (SPI)
The Standardized Precipitation Index (SPI) is widely regarded as one of the most accessible tools for quantifying and reporting meteorological drought. At shorter timescales, SPI values are highly correlated with soil moisture, while at extended timescales, they reflect variations in groundwater and reservoir storage. The SPI model derives probability distributions from historical precipitation records, which are then normalized using an incomplete gamma function across multiple timescales. SPI values indicate the number of standard deviations the observed anomaly departs from the long-term period of record, with positive values corresponding to wetter-than-average conditions.Time periods calculated for monthly precipitation percentiles are 1, 2, 3, 6, 9, 12, 18, 24 months. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday. Historical record goes back to 1980Indices values were calculated using the xclim python package The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.
FRI: Forest stands
Forest stands (FSTAND) is a vector delineation of relatively homogeneous forest stands or naturally non-forested areas as polygons with a 0.5 ha minimum area and a 2.0 ha median area.Download: Here The Saskatchewan Ministry of Environment, Forest Service Branch, has developed a forest resource inventory (FRI) which meets a variety of strategic and operational planning information needs for the boreal plains. Such needs include information on the general land cover, terrain, and growing stock (height, diameter, basal area, timber volume and stem density) within the provincial forest and adjacent forest fringe. This inventory provides spatially explicit information as 10 m or 20 m raster grids and as vectors polygons for relatively homogeneous forest stands or naturally non-forested areas with a 0.5 ha minimum area and a 2.0 ha median area. Forest stands (FSTAND) is a vector delineation of relatively homogeneous forest stands or naturally non-forested areas as polygon with a 0.5 ha minimum area and a 2.0 ha median area. For more information, see the Forest Inventory Standard of the Saskatchewan Environmental Code, Forest Inventory Chapter.
Forest Reserve Range Distribution Units
The Forest Reserve Range Distribution Units dataset represent the functional grazing management areas within the Rocky Mountains Forest Reserve. Boundaries of the allotments and/or distribution units may be defined by fencelines, height of land, natural boundaries, and/or a combination of these. This is currently the most accurate representation of the distribution unit boundary and is subject to change. In some cases these boundaries may extend beyond the boundary of the Rocky Mountains Forest Reserve. In these cases this is a representation of the management unit as a whole.
Forest Inventory Label Additional Table
This table is a list of polygon attributes to be used in map production for the vegetation Inventory map series. It contains attribute information for polygons in the inventory that are not labeled with the Inventory Annotation. Attribute information is pulled from this table to use as additional labels on the map layout for the Forest Inventory map series.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)
National Agroclimate Series of Derived Indicators (NASDI) - Standardized Precipitation Evapotranspiration Index (SPEI)
The Standardized Precipitation Evapotranspiration Index (SPEI) is computed similarly to the SPI. The main difference is that SPI assesses precipitation variance, while SPEI also considers demand from evapotranspiration which is subtracted from any precipitation accumulation prior to assessment.Unlike the SPI, the SPEI captures the main impact of increased temperatures on water demand SPI values indicate the number of standard deviations the observed anomaly departs from the long-term period of record, with positive values corresponding to wetter-than-average conditions.Time periods calculated for monthly precipitation percentiles are 1, 2, 3, 6, 9, 12, 18, 24 months. Each ISO week is numbered from 1 to 52 (sometimes 53) within a year. An ISO week starts on Monday and ends on Sunday. Historical record goes back to 1980Indices values were calculated using the xclim python package The National Agroclimate Series of Derived Indicators (NASDI) products provide a collection of comprehensive and regularly updated datasets on key agroclimatic variables, including accumulated precipitation, standardized precipitation index, and difference from normal temperature, among others. These datasets incorporate both real-time and historical climate information, offering enhanced insight into conditions and trends across Canada’s diverse agricultural regions.
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).
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