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We have found 413 datasets for the keyword " forêt aléatoire". You can continue exploring the search results in the list below.
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413 Datasets, Page 1 of 42
Pacific Marine Ecological Classification System and its Application to the Northern and Southern Shelf Bioregions
Description:Biophysical Units: Under the Pacific Marine Ecological Classification System (PMECS; DFO 2016; Rubidge et al. 2016), biophysical units are areas of distinct physiographic and oceanographic conditions and processes that shape species composition at spatial extents of 1000s of km. Geomorphic units:Geomorphic units or geozones are discrete geomorphological structures at the scale of 100s of km that are assumed to have distinctive biological assemblages (e.g., plateaus, ridges, seamounts, canyons). Although the spatial scale of geomorphic units is nested within biophysical units, a single geomorphic unit such as a trough may span more than one biophysical unit. The following 5 layers are included in this geodatabase:1. Biophysical_Units_L4A - Predicted PMECS Biophysical Units (Level 4A) output from the random forest analysis2. Biophysical_Units_L4B - Predicted PMECS Biophysical Units (Level 4B) output from the random forest analysis3. Biophysical_Units_ProbAssign_L4AB - Layer showing the probability that a grid cell was assigned to a given biophysical unit in the final random forest predictive modelling step4. Cluster_L4AB - Layer showing the output of species assemblage cluster analysis5. Geomorphic_Units - Geomorphic units for the BC coast that combines geomorphic units produced by Rubidge et al. 2016) and Proudfoot and Robb (2022).Methods:Biophysical Units:Rubidge et al. (2016) used a two-step process to identify biophysical units in British Columbia. First, a cluster analysis based on the similarity of species composition was used to group sites with similar species into distinct biological assemblages. Second, a random forest analysis was used to identify environmental correlates of the biological assemblages identified by the cluster analysis and to predict and assign the biological assemblage present in areas with too few biological data. Two different similarity thresholds were used to identify two levels (4A, 4B) of biophysical units; see Rubidge et al. (2016) for details. Indicator species for each assemblage (biophysical unit) were also identified.Geomorphic units:Rubidge et al. (2016) used the benthic terrain modeller (BTM) tool with broad and fine-scale benthic positioning index (BPI) parameters to define geomorphic units on the continental shelf in the Northern Shelf Bioregion and the continental slope in both the Northern Shelf Bioregion and Southern Shelf Bioregion. In 2022, geomorphic units were produced for the Strait of Georgia and Southern Shelf Bioregions following the same methods as Rubidge et al. (2016) (Proudfoot and Robb 2022). The geomorphic units produced as part of the PMECS process were merged with the geomorphic units produced for the Strait of Georgia and Southern Shelf bioregions to produce a continuous spatial data product representing geomorphic units for the Canadian Pacific continental shelf and slope. After merging, the geomorphic units produced in 2016 were unchanged (i.e., they are consistent with the original geomorphic units described in Rubidge et al. 2016).Data Sources:From Rubidge et al. (2016): Species data was taken from Fisheries and Oceans Canada (DFO) standardized fisheries-independent research surveys: groundfish trawl and long-line (2003-2013), Tanner Crab trawl and trap (2000–2006), and Dungeness Crab trap (2000–2014). Environmental data came from NASA, the Canadian Hydrographic Service, Fisheries and Oceans Canada, Bio-ORACLE, and elsewhere (details in Rubidge et al. 2016). From Proudfoot and Robb (2022): bathymetry data came from Natural Resources Canada (details in Proudfoot and Robb 2022).Uncertainties:The data is intended for use at the bioregional scale, and caution should be used for finer-scale analyses.
Manitoba Provincial Forests – Version 6
Manitoba's Provincial Forest Boundaries (version 6): There are currently 15 provincial forests totalling almost 22,000 km2. Attributes include the name of the provincial forest, the year it was established and its area. Detailed descriptions of Manitoba’s provincial forests are provided in the Provincial Forest Act Regulations.Manitoba's Provincial Forest B oundaries ( V ersion 6 ). Manitoba's provincial forests reserve certain areas in the province for perpetual growth of timber, preserve the forest cover thereon and provide for a reasonable use of all the resources that the forest lands contain. All Crown lands within a provincial forest are withdrawn from disposition, sale, settlement or occupancy, except under authority of the Forest Act . Before the Province of Manitoba was established, European settlers were promised 160 acres of free land if they lived on it and cleared it for agriculture. As a result, farms began replacing our southern forests. The federal government decided they must retain some forests for building material. In 1885 , they established Turtle Mountain, Spruce Woods and Riding Mountain (now a national park) as timber reserves. Duck Mountain and Porcupine Mountain followed in 1906. What started out as federal timber reserves 100 years ago have become our provincial forests of today. Manitoba has 15 provincial forests , totalling almost 22,000 sq. km . These forests are among the highest quality timber stands in the province. Today, our provincial forests are much more than reserves for timber. They are also places for wildlife, recreation and research. Control of Manitoba's forests was transferred from the federal to the provincial governments in 1930. Provincial forests are Crown lands owned by the people of Manitoba. The feature class name (BDY_MB_PROV_FOREST_PY) components include: 1. ISO 19115 Topic Category Name (BDY for boundary); 2. Location code (MB for Manitoba); 3. Intuitive or descriptive name (PROV_FOREST); 4. Data/geometry type (PY for polygon); 5. Version number (v 6 ).Manitoba's provincial forests include Agassiz Provincial Forest, Belair Provincial Forest, Brightstone Sand Hills Provincial Forest, Cat Hills Provincial Forest, Cormorant Provincial Forest, Duck Mountain, Moose Creek Provincial Forest, Northwest Angle Provincial Forest, Porcupine Provincial Forest, Sandilands Provincial Forest, Spruce Woods Provincial Forest, Swan-Pelican Provincial Forest, Turtle Mountain Provincial Forest, Wampum Provincial Forest, and Whiteshell Provincial Forest.Detailed descriptions of Manitoba’s Provincial Forests are provided in the Provincial Forest Act Regulations. The dataset includes the following fields : Name / Nom Alias Description PROV_FOREST_ID Provincial Forest ID / No de la forêt provinciale Provincial Forest identifier Identificateur de la forêt provinciale PROV_FOREST_NAME Provincial Forest Name Provincial Forest name -- NOM_FORET_PROV Nom de la forêt provinciale -- Nom de la forêt provinciale ESTABLISHED Year Established / Année d’établissement The year that the provincial forest was established L’année où la forêt provinciale a été établie AREA_HA Area / Surface (Hectares) Area in hectares La surface en hectares
FADM - Provincial Forest Addition
The spatial representation for a Forest Addition, which is any Forest land that is to be designated by the Lieutenant Governor, into an established forest, to be managed and used for the social and economic benefit of the Province
BC Wildfire Fire Perimeters - Current
Wildfire perimeters for the current fire season, including both active and inactive fires, supplied from various sources. The data is refreshed from operational systems every 15 min. These perimeters are rolled over to Historical Fire Polygons on April 1 of each year Wildfire data may not reflect the most current fire situation, and therefore should only be used for reference purposes. Wildfire data is refreshed when practicable and individual fire update frequency will vary. The information is intended for general purposes only and should not be relied on as accurate because fires are dynamic and circumstances may change quickly.
BC Wildfire Fire Locations - Current
Wildfire location points for the current fire season. This includes both active and inactive fires. Data is supplied through various sources and is updated from the operational systems every 15 minutes. These points are rolled over to Historical Fire Points on April 1 of each year. Wildfire data may not reflect the most current fire situation, and therefore should only be used for reference purposes. Wildfire data is refreshed when practicable and individual fire update frequency will vary. The information is intended for general purposes only and should not be relied on as accurate because fires are dynamic and circumstances may change quickly.
FADM - Provincial Forest Deletion
The spatial representation for a Forest Deletion, which is any Forest land that is to be removed from the land designated by the Lieutenant Governor into an established forest
Sablefish Offshore Stratified Random Trap Survey
Fishing event data (e.g. year, date, time, location, catch and effort) and associated biological data from the Offshore Stratified Random Survey component of the annual Sablefish Research and Assessment Survey on the British Columbia coast.IntroductionDFO and the Canadian Sablefish Association (CSA) collaborate to undertake an annual fishery-independent research survey under a joint agreement. The survey employs longline trap gear to obtain catch rate data, gather biological samples, capture oceanographic measurements, and collect tag release and recapture data.Data summaries provided here are for the offshore stratified random sampling design (StRS) component of the survey, which has been conducted annually since 2003. The design of the sablefish survey has developed over time by incorporating and discontinuing components, including individual experimental studies (not available on OpenData). This StRS Survey component differs in methodology from the other two survey components: (1) Standardized trap survey – mainland inlets (1994-present; available on OpenData using link below), and (2) Standardized trap survey – offshore indexing and offshore tagging (1990 – 2010; not yet available on OpenData). The Sablefish offshore stratified random trap survey (StRS) follows a depth and area stratified random sampling design. The survey area is partitioned into five spatial strata (S1 to S5) and three depth strata (RD1 to RD3) for a total of 15 strata. The five spatial strata are S1 (South West Coast Vancouver Island or SWCVI), S2 (North West Coast Vancouver Island or NWCVI), S3 (Queen Charlotte Sound or QCS), S4 (South West Coast of Haida Gwaii or SWCHG), and S5 (North West Coast of Haida Gwaii or NWCHG). The three depth strata are 100-250 fathoms (RD1), 250-450 fathoms (RD2), and 450-750 fathoms (RD3). The area within each of the 15 strata are sectioned into 2 km x 2 km grid cells or ‘fishing blocks’ from which set locations are randomly chosen each year. Survey procedures are standardized and documented in Canadian Technical Reports of Fisheries and Aquatic sciences.Data tables provided for the offshore stratified random survey include (i) effort, (ii) catch, (iii) biological information, (iv) the sampling frame from which blocks are selected for sampling each year, and (v) the calculated coastwide Sablefish biomass index. StRS EffortThis table contains information about the annual survey trips and fishing events (sets). Trip-level information includes the year the survey took place, a unique trip identifier, the vessel that conducted the survey and the trip start and end dates (the dates the vessel was away from the dock conducting the survey). Set-level information includes the date, time, location and depth that fishing took place, the survey spatial and depth strata for the set, reason for the set, soak time, number of traps deployed and number of traps fished. All successful fishing events are included, i.e., those sets that conformed to specified survey standards.StRS CatchThis table contains the catch information from successful fishing events. Catches are identified to species or to the lowest taxonomic level possible. Catches are recorded as fish counts and / or weight. The unique trip identifier and set number are included so that catches can be related to the fishing event information (including capture location).StRS Biological InformationThis table contains the biological data for sampled catches. Data may include any or all of length, weight, sex, maturity, and age. Most of the sampled catch is Sablefish; however, some biological information has been collected on Rockfish, Flatfish and other Roundfish species in some years. Age structures are collected and are archived until required for analyses; therefore, all existing structures have not been aged at this time. Tissue samples (usually a fin clip) may be collected for genetic (DNA) analysis for specific species. Genetic samples may be archived until required for analyses; for more information, please see the data contacts. The unique trip identifier and set number are included so that samples can be related to the fishing event and catch information.Sample FrameThis table contains a list of all of the 2km x 2km grid cells or ‘fishing blocks’ that are part of the stratified random sampling frame. A subset of blocks are randomly selected for sampling each year from this list. For each grid cell, the corresponding depth and spatial strata ID is included. This sample frame can be used to calculate design-based abundance indices for the survey.StRS Biomass IndexThis table contains a coastwide relative biomass index for Sablefish based on the annual StRS survey. Stratified random sampling mean index values and 95% confidence intervals are calculated by year using the classical survey stratified random sampling estimator (Cochran 1977) and the number of possible sampling units per stratum provided by Wyeth et al. (2007). The relative biomass index has been input to the operating model and management procedure used to provide management advice for BC Sablefish since 2011 (Cox et al. 2011).
Grassland Encroachment for the Cariboo Region
Forest encroachment onto grasslands
Wildfire Year/dNBR/Mask (1985-2015)
Wildfire Year/dNBR/Mask 1985-2015Wildfire change magnitude 85-15. Spectral change magnitude for wildfires that occurred from 1985 and 2015. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The wildfire change magnitude included in this product is expressed via differenced Normalized Burn Ratio (dNBR), computed as the variation between the spectral values before and after the change event. This dataset is composed of three layers: (1) binary wildfire mask, (2) year of greatest wildfire disturbance, and (3) differenced Normalized Burn Ratio (dNBR) transformed for data storage efficiency to the range 0-200. The actual dNBR value is derived as follows: dNBR = value / 100. Higher dNBR values are related to higher burn severity. The information outcomes represent 30 years of wildfires in Canada's forests, derived from a single, consistent spatially-explicit data source in a fully automated manner. Time series of Landsat data with 30-m spatial resolution were used to characterize national trends in stand replacing forest disturbances caused by wildfire for the period 1985-2015 for Canada's 650 million hectare forested ecosystems.When using this data, please cite as: Hermosilla, T., M.A. Wulder, J.C. White, N.C. Coops, G.W. Hobart, L.B. Campbell, 2016. Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring. International Journal of Digital Earth 9(11), 1035-1054. (Hermosilla et al. 2016).See references below for an overview on the data processing, metric calculation, change attribution and time series change detection methods applied, as well as information on independent accuracy assessment of the data.Hermosilla, T., Wulder, M. A., White, J. C., Coops, N.C., Hobart, G.W., 2015. An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites. Remote Sensing of Environment 158, 220-234. (Hermosilla et al. 2015a).Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., 2015. Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics. Remote Sensing of Environment 170, 121-132. (Hermosilla et al. 2015b).Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011
Provincial Forest Boundary Line
Represents the boundary line of Saskatchewan Crown resource lands designated as provincial forests as described in The Forest Resources Management Regulations, F-19.1 Reg 1, amended June 2020.Boundaries of the Canwood, Nisbet, Fort a la Corne, Torch River, and Porcupine Provincial Forests are described, as well as the southern portion of the Northern Provincial Forest. Crown resource lands contained within these boundaries are designated as provincial forest. Certain lands have been deemed to be withdrawn from the provincial forest pursuant to subsection 12(4) of the Act. The Forest Resources Management Act The Forest Resources Management Regulations The provincial forest boundary is described by clauses and subclauses in The Forest Resources Management Regulations. Each provincial forest boundary description clause and subclause has a corresponding line feature in FORESTRY.PLANNING_Forest_Boundary. Clause descriptions position provincial forest boundary line features according to Saskatchewan’s Land Survey System by Township, Range, and Meridian. Subclause descriptions further positions provincial forest boundary line features within the clause. When a subclause describes the provincial forest boundary according to a water body or water course bank, line features are digitized from the Saskatchewan Geospatial Imagery Collaborative 2016 three-band (red, green, blue) SPOT 6 and 7 satellite imagery mosaic, pan-sharpened to 1.5 m resolution (IMAGERY.SGIC_SPOT_RGB_2016_Ref). In certain situation, applying this satellite imagery to the provincial forest boundary description results in a gap between land and water. In such cases, in order to maintain a contiguous boundary, a new line feature is created that has no corresponding clause and subclause in The Forest Resources Management Regulations. These “Land to Water Gap” features are identified as such in the SUBCLAUSE_DESCR field. When a subclause describes the provincial forest boundary according to the Saskatchewan Land Survey System, line features are extracted from Information Services Corporation CADASTRE data (CADASTRE.SG_SECTION, .SG_QUARTERSECTION, .SG_LEGALSUBDIVISION, .surface, .boundary, .right_of_way). By convention, the west boundary of a line feature is defined by the vector west of the road allowance and the south boundary of a line feature is defined by the vector south of the road allowance. In certain situation, applying this convention to the provincial forest boundary description results in a gap created by an adjacent east or north road allowance. In such cases, in order to maintain a contiguous boundary, a new line feature is created that has no corresponding clause and subclause in The Forest Resources Management Regulations. These “Road Allowance Gap” features are identified as such in the SUBCLAUSE_DESCR field. In spite of west / south boundary road allowance convention, when a road allowance forms the boundary of the provincial forest, in FORESTRY.PLANNING_Forest_Boundary, the line feature is drawn such that the road allowance is excluded from the provincial forest.
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