Programs that perform a laboratory analysis of body fluids and tissue to determine the presence of irregularities or to identify unknown substances submitted for analysis. Definition is protected by Copyright by Information and Referral Federal of Los Angeles County, Inc (https://211taxonomy.org/subscriptions/#agreement)

This data shows anthropogenic polygon disturbance features. Features were digitized using high resolution satellite imagery and orthophotos. The following data was not included in the dataset: proposed features.Table 1. A list of attributes, associated domains, and descriptions.AttributeData TypeDomainsDescriptionREF_IDText (20) Unique feature reference IDDATABASEText (20)Historic, Most Recent, RetiredSub-database to which the feature belongsTYPE_INDUSTRYText (50)Table 2.3.2Major classification of disturbance feature by industryTYPE_DISTURBANCEText (50)Table 2.3.2Sub classification of disturbance featureSCALE_CAPTUREDLong Scale at which the feature was digitizedDATA_SOURCEText (10)Imagery, GPS, OtherData source: digitized from imagery, captured by GPS, or obtained by other meansIMAGE_NAMEText (100) Filename of source imageryIMAGE_DATEDate Date that imagery was captured (YYYYMMDD)IMAGE_RESOLUTIONDouble Resolution of source imagery in metersIMAGE_SENSORText (35) Name of sensor that captured source imageryTable 2. A list of disturbance feature types and their descriptions.TYPE_INDUSTRYTYPE_DISTURBANCEDESCRIPTIONAgricultureAgricultureFarms, ranches, or other agricultural areasForestryForestryCut blocks or other forestry related activitiesMiningBuildingA building footprint or the building and the surrounding land related to mining activities.Drill PadDrill pad features related to mineral exploration activitiesFuel CacheRemote caches of fuel allowing for mineral exploration activities (will often have fuel tanks and barrels)Gravel Pit / QuarryPit or quarry for mining gravel or aggregateLaydown areaAreas used to store materials and equipment for mining operationsMiningMiscellaneous or unknown mining activitiesPlacer Mining - MinorPlacer mining area with little disturbancePlacer Mining - SignificantPlacer mining area with greater disturbanceQuartz Mining - MinorQuartz mining area with little disturbanceQuartz Mining - SignificantQuartz mining area with greater disturbanceTailing PondTailing pond associated with mining activityCampMining campOil and GasWell PadCleared area surrounding oil or gas wellRuralCampAny camp outside of mining areas, including fishing/hunting camps, ENV conservation officer cabins/camps, outfitters, etc.HomesteadRural dwelling and associated landTransportationAirstripAirport or AirstripClearingClearings that are related to transportation but could not be clearly attributed as a turn area, pullout, road cut and fill, etc.Gravel Pit / QuarryGravel pits related to transportationPullout / Turn AreaAn area associated with transportation and is intended as a vehicle pullout or turn areaRoad Cut and FillCut slopes and moved earth for road construction purposesUnknownClearingA tract of land devoid (or nearly devoid) of natural land cover and suspected to be anthropogenic in natureGravel Pit / QuarryA gravel pit with unknown related industryUnknownUnable to identify from imagery, but suspected to be anthropogenicUrbanBuildingVisible building or structureCemeteryCemeteryClearingMiscellaneous urban clearingsCul-de-sac / Turn AreaA turn area associated with transportation or road cul-de-sacDamBarrier impounding water or streamGolf CourseRecreational golfing areaIndustrialAreas that are designated for industrial uses: factories, tank farm, transportation areaInstitutionalAny institutional buildings and immediate cleared area: School, government, etc.LandfillSite used for disposal of waste materialsPondStanding body of water, created anthropogenically; includes sewage lagoons, wastewater facilities, and artificial bodies of water.Recreation AreaVisible disturbance in Urban / Rural parks and recreation areasRural ResidentialLand use in which housing predominates in an urban or community settingTowerA tall structure, possibly used for communications or forestryUrbanMiscellaneous or unknown urban features Distributed from [GeoYukon](https://yukon.ca/en/statistics-and-data/mapping/explore-map-data-using-geoyukon) by the [Government of Yukon](https://yukon.ca/) . Discover more digital map data and interactive maps from Yukon's digital [map](https://yukon.ca:443/en/maps) data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)      

This data shows anthropogenic polyline disturbance features. Features were digitized using high resolution satellite imagery and orthophotos. Features from the National Road Network (NRN) and the National Railway Network (NRWN) were adapted and included. The following data was not included in the dataset: proposed features.Table 1. A list of attributes, associated domains, and descriptions.AttributeData TypeDomainsDescriptionREF_IDText (20) Unique feature reference IDDATABASEText (20)Historic, Most Recent, RetiredSub-database to which the feature belongsTYPE_INDUSTRYText (50)Table 2.3.2Major classification of disturbance feature by industryTYPE_DISTURBANCEText (50)Table 2.3.2Sub classification of disturbance featureWIDTH_M*Double Width of feature in metersWIDTH_CLASS**Text (5)HIGH, MED, LOWWidth of feature by classificationSCALE_CAPTUREDLong Scale at which the feature was digitizedDATA_SOURCEText (10)Imagery, GPS, OtherData source: digitized from imagery, captured by GPS, or obtained by other meansIMAGE_NAMEText (100) Filename of source imageryIMAGE_DATEDate Date that imagery was captured (YYYYMMDD)IMAGE_RESOLUTIONDouble Resolution of source imagery in metersIMAGE_SENSORText (35) Name of sensor that captured source imagery\*WIDTH_M: Linear features must be attributed with a width measurement. The width of the feature can be estimated in meters, rounded to the nearest whole number.\*\*WIDTH_CLASS: This field employs a classification scheme used by previous contractors. This classification scheme was discussed and agreed upon by Mammoth Mapping and the Project Manager in 2011-2013. The width values are the following.Table 2. Width classification breakdown.WIDTH_CLASSAnticipated Value Range (meters)LOW<4MED4-8HIGH>8Table 3. A list of disturbance feature types and their descriptions.TYPE_INDUSTRYTYPE_DISTURBANCEDESCRIPTIONMiningSurvey / CutlineA linear cleared area through undeveloped land, used for line-of-sight surveying; impossible to distinguish whether associated with quartz or placer mining (overlapping or unclear claims information)Survey / Cutline - PlacerA linear cleared area through undeveloped land, used for line-of-sight surveying; associated with placer mining (identified using claims information and/or other indicators)Survey / Cutline - QuartzA linear cleared area through undeveloped land, used for line-of-sight surveying; associated with quartz mining (identified using claims information and/or other indicators)TrenchA long, narrow excavation dug to expose vein or ore structureUnknownUnknown linear mining disturbanceOil and GasPipelineVisible pipeline or pipeline Right-of-Way (above- or below-ground)Seismic LineSeismic linesRuralDrivewayA driveway in a rural areaFenceA fence in a rural areaTransportationAccess AssumedA linear feature that is assumed to be an access road, but could also be a trailAccess RoadA road or narrow passage whose primary function is to provide access for resource extraction (i.e. mining, forestry) and may also have served in providing public access to the backcountry.Arterial RoadA major thoroughfare with medium to large traffic capacityLocal RoadA low-speed thoroughfare, provides access to front of properties, including those with potential public restrictions such as trailer parks, First Nations land, private estate, seasonal residences, gravel pits (NRN definition for Local Street/Local Strata/Local Unknown). Shows signs of regular use.Right of WayFor Road Rights as attributed in the land parcels ancillary dataTrailPath or track (typically <1.5 m wide) used for walking, cycling, ORV, or other backcountry activities. (Note: trails used for mining activities are Access Roads.)Unpaved RoadDirt or gravel road (typically >1.5 m wide) that does not necessarily access remote resourcesUnknownRight of WayA right of way with unknown industry typeSurvey / CutlineA linear cleared area through undeveloped land, used for line-of-sight surveying. A cutline may not always be associated with mineral exploration, therefore, Type: Unknown was used to differentiate all cutlines that were outside of mineral exploration.UnknownUnclassified, or unable to identify type based on imagery, but suspected to be anthropogenicUtilityElectric Utility CorridorCorridor usually running parallel to highway, where transmission lines or other utilities are visibleUnknownUnknown linear feature assumed to be a utility corridor; ancillary data is unclear.Distributed from [GeoYukon](https://yukon.ca/en/statistics-and-data/mapping/explore-map-data-using-geoyukon) by the [Government of Yukon](https://yukon.ca/) . Discover more digital map data and interactive maps from Yukon's digital [map](https://yukon.ca/en/maps) data collection.For more information: [geomatics.help@yukon.ca](mailto:geomatics.help@yukon.ca)       

This layer represents Land use polygons as determined by a combination of analytic techniques, mostly using Landsat 5 image mosaics . BTM 1 was done on a federal satellite image base that was only accurate to about 250m. The images were geo-corrected, not ortho-corrected, so there is distortion in areas of high relief. This is not a multipart feature

The Regional Deterministic Precipitation Analysis (RDPA) produces a best estimate of precipitation amounts that occurred over a period of 24 hours. The estimate integrates data from in situ precipitation gauge measurements, weather radar, satellite imagery and numerical weather prediction models. Geographic coverage is North America (Canada, United States and Mexico). Data is available at a horizontal resolution of 10 km. The 24 hour analysis is produced twice a day and is valid at 06 and 12 UTC. A preliminary analysis is available approximately 1 hour after the end of the accumulation period and a final one is generated 7 hours later in order to assimilate more gauge data.

The Regional Deterministic Precipitation Analysis (RDPA) produces a best estimate of the amount of precipitation that occurred over recent past periods of 6 or 24 hours. The estimate integrates data from in situ precipitation gauge measurements, weather radar, satellite imagery and numerical weather prediction models. Geographic coverage is North America (Canada, United States and Mexico). Data is available at horizontal resolution of 10 km. Data is only available for the surface level. Analysis data is made available four times a day for 6h intervals and twice a day for the 24h interval. A preliminary estimate is available approximately 1h after the end of the accumulation period, and revised 7h after in order to assimilate gauge data arriving later.

Locations of open water within river ice in Manitoba, Ontario, Quebec, and the Maritimes were discerned manually using publicly accessible optical satellite images spanning from 2013 to 2020. This initial effort has led to a dataset pinpointing potential sites for river hydrokinetic energy initiatives.A more comprehensive dataset encompassing the entirety of Canada’s major freezing rivers has also been developed entitled “Hydrokinetic Resource Mapping - Optical Satellite Imagery Analysis of Open Water Regions in Ice-Covered Canadian Rivers” and is available at (https://search.open.canada.ca/openmap/61b4e576-9f3a-49a1-9546-b29be14787a4). Disclaimer:The identification of open water locations within river ice in Manitoba, Ontario, Quebec, and the Maritimes, as described, was conducted manually through the analysis of publicly available optical satellite images. This dataset is subject to the following limitations:1- The manual identification method may introduce potential human error and subjectivity within the dataset. 2- The publicly accessible satellite images employed may not provide fully comprehensive or entirely accurate representations of the actual conditions in the identified locations due to image resolution constraints, cloud cover, or atmospheric interference. This dataset is intended for preliminary assessment and should not be the sole basis for making critical decisions or investments related to hydrokinetic energy projects. Further validation and in-depth analysis are strongly recommended, and users should conduct their own due diligence and additional research to verify the data accuracy and relevance for specific applications. By accessing and using this dataset, users acknowledge and accept these disclaimers. The providers of this dataset explicitly absolve themselves of any responsibility or liability for any consequences arising from the use, reliance upon, or interpretation of this dataset. Users are advised that their use of the dataset is at their own risk, and they assume full responsibility for any actions or decisions made based on the information contained therein. This disclaimer is in accordance with applicable laws and regulations, and by accessing or utilizing the dataset, users agree to release the providers of this dataset from any legal claims, damages, or liabilities that may arise from such use.

In 2013, 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 to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from the BC Ministry of Agriculture and our regional AAFC colleagues.

In 2012, 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 to for all of Canada (except Newfoundland), in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (DMC, SPOT) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues.

In 2011, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) expanded the process of generating annual crop inventory digital maps using satellite imagery to include British Columbia, Ontario, Quebec, and the Maritime provinces, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-5, DMC) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues.