As part of a scientific assessment of critical habitat for boreal woodland caribou (Environment Canada 2011, see full reference in accompanying documentation), Environment Canada's Landscape Science and Technology Division was tasked with providing detailed anthropogenic disturbance mapping, across known caribou ranges, as of 2010. The attached dataset comprises the second 5-year update (first one in 2015) bringing the data up to 2020.The original disturbance mapping was based on 30-metre resolution Landsat-5 imagery from 2008-2010. Since then, anthropogenic disturbances within 51 caribou ranges across Canada were remapped every five years to create a nationally consistent, reliable and repeatable geospatial dataset that followed a common methodology. The ranges were defined by individual provinces and territories across Canada. The methods developed were focused on mapping disturbances at a specific point of time, and were not designed to identify the age of disturbances, which can be of particular interest for disturbances that can be considered non-permanent, for example cutblocks. The resultant datasets were used for a caribou resource selection function (habitat modeling) and to assess overall disturbance levels on each caribou ranges. As with the 2010 mapping project, anthropogenic disturbance was defined as any human-caused disturbance to the natural landscape that could be visually identified from Landsat 30-metre multi-band imagery at a viewing scale of 1:50,000. The same concept was followed for the 2015 and 2020 disturbance mapping and any additional disturbance features that were observed since the original mapping date, were added. The 2015 database was used as a starting point for the 2020 database. Unlike the previous iteration, features were not removed in the mapping process which was a decision made in the name of time. Interpretation was carried out based on the most recent cloud free imagery available up to mid fall for a given year. Each disturbance feature type was represented in the database by a line or polygon depending on their geometric description. Linear disturbances included: roads, railways, powerlines, seismic exploration lines, pipelines, dams, air strips, as well as unknown features. Polygonal disturbances included: cutblocks, harvest (added in 2020), mines, built-up areas, well sites, agriculture, oil and gas facilities, as well as unknown features. For each type of anthropogenic disturbance, a clear description was established (see Appendix 7.2 of the science assessment) to maintain consistency in identifying the various disturbances in the imagery by the different interpreters. Features were only digitized if they were clearly visible in the Landsat imagery at the prescribed viewing scale. In comparison to the previous mapping protocol, one enhancement to the mapping process in 2020 was the addition of CFS harvest polygons (Ref: NRCan-CFS NTEMS; Wulder 2020) into the database prior to interpretation. This considerably reduced the digitizing time for polygons and accelerated the data collection process. The CFS harvest polygons were checked before inclusion, removing some which had been generated erroneously in their process.A 2nd interpreter quality-control phase was carried out to ensure high quality, complete and consistent data collection. Subsequently, the vector data of individual linear and polygonal disturbances were buffered by a 500-metre radius, representing their extended zone of impact upon boreal caribou herds. Additionally, forest fire polygons for the past forty years (CNFDB 1981-2020) were merged into the buffered anthropogenic footprint in order to create an overall disturbance footprint. These buffered datasets were used in the calculation of range disturbance levels and for integrated risk assessment analysis.

As part of a scientific assessment of critical habitat for boreal woodland caribou (Environment Canada 2011, see full reference in accompanying documentation), Environment Canada's Landscape Science and Technology Division was tasked with providing detailed anthropogenic disturbance mapping, across known caribou ranges, as of 2015. This data comprises a 5-year update to the mapping of 2008-2010 disturbances, and allows researchers to better understand the attributes that have a known effect on caribou population persistence. The original disturbance mapping was based on 30-metre resolution Landsat-5 imagery from 2008 -2010. The mapping process used in 2010 was repeated using 2015 Landsat imagery to create a nationally consistent, reliable and repeatable geospatial dataset that followed a common methodology. The methods developed were focused on mapping disturbances at a specific point of time, and were not designed to identify the age of disturbances, which can be of particular interest for disturbances that can be considered non-permanent, for example cutblocks. The resultant datasets were used for a caribou resource selection function (habitat modeling) and to assess overall disturbance levels on each caribou ranges. Anthropogenic disturbances within 51 caribou ranges across Canada were mapped. The ranges were defined by individual provinces and territories across Canada. Disturbances were remapped across these ranges using 2015 Landsat-8 satellite imagery to provide the most up-to-date data possible. As with the 2010 mapping project, anthropogenic disturbance was defined as any human-caused disturbance to the natural landscape that could be visually identified from Landsat imagery with 30-metre multi-band imagery at a viewing scale of 1:50,000. A minimum mapping unit MMU of 2 ha (approximately 22 contiguous 30-metre pixels) was selected. Each disturbance feature type was represented in the database by a line or polygon depending on their geometric description. Polygonal disturbances included: cutblocks, mines, reservoirs, built-up areas, well sites, agriculture, oil and gas facilities, as well as unknown features. Linear disturbances included: roads, railways, powerlines, seismic exploration lines, pipelines, dams, air strips, as well as unknown features. For each type of anthropogenic disturbance, a clear description was established (see Appendix 7.2 of the science assessment) to maintain consistency in identifying the various disturbances in the imagery by the different interpreters. Features were only digitized if they were visible in the Landsat imagery at the prescribed viewing scale. A 2nd interpreter quality-control phase was carried out to ensure high quality, complete and consistent data collection. For this 2015 update an additional, separate higher-resolution database was created by repeating the process using 15-metre panchromatic imagery. For the 30-metre database only, the line and poly data were buffered by a 500-metre radius, representing their extended zone of impact upon boreal caribou herds. Additionally, forest fire polygons were merged into the anthropogenic footprint in order to create an overall disturbance footprint. These buffered datasets were used in the calculation of range disturbance levels and for integrated risk assessment analysis.

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)      

Fisheries and Oceans Canada has conducted a cumulative human impact mapping analysis for Pacific Canada to support ongoing Marine Spatial Planning. Cumulative impact mapping (CIM) combines spatial information on human activities, habitats, and a matrix of vulnerability weights into an intuitive relative ‘cumulative impact score’ that shows where cumulative human impacts are greatest and least. To map cumulative impacts, a recently developed ecosystem vulnerability assessment for Pacific Canadian waters (Murray et al. 2022) was combined with spatial information on thirty-eight (38) different habitat types and forty-five (45) human activities following the methodology from Halpern et al.(2008) and Murray et al. (2015). The cumulative impact map is provided in a 1x1 km grid used for oceans management by Fisheries and Oceans Canada. For further information, please contact the data provider.

The area of Crown land disturbance for applications falling within a Ministry of Transportation and Infrastructure (MOTI) road allowance. The BC Energy Regulator issues cutting permits for any new Crown land disturbance within MOTI unconstructed road allowances. The Regulator does not issue land tenure over MOTI right of ways. This dataset contains polygon features for proposed applications collected through the Regulator's Application Management System (AMS). This dataset is updated nightly.

Landsat-derived forest age for Canada 2022Satellite-based forest age map for 2022 across Canada's forested ecozones at a 30-m spatial resolution. Remotely sensed data from Landsat (disturbances, surface reflectance composites, forest structure) and MODIS (Gross Primary Production) are utilized to determine age. Age can be determined where disturbance can be identified directly (disturbance approach) or inferred using spectral information (recovery approach) or using inverted allometric equations to model age where there is no evidence of disturbance (allometric approach). The disturbance approach is based upon satellite data and mapped changes and is the most accurate. The recovery approach also avails upon satellite data plus logic regarding forest succession, with an accuracy that is greater than pure modeling. Given the lack of widespread recent disturbance over Canada's forests, the allometric approach is required over the greatest area (86.6%). Using information regarding realized heights and growth and yield modeling, ages are estimated where none are otherwise possible. Trees of all ages are mapped, with trees >150 years old combined in an - old tree - category. This product was developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS).See Maltman et al. (2023) for an overview of the methods, data, image processing, as well as information on agreement assessment using Canada's National Inventory (NFI). Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C., 2023. Estimating and mapping forest age across Canada's forested ecosystems. Remote Sensing of Environment 290, 113529. ( Maltman et al. 2023).

Landsat-derived forest age for Canada 2022Satellite-based forest age map for 2022 across Canada's forested ecozones at a 30-m spatial resolution. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Remotely sensed data from Landsat (disturbances, surface reflectance composites, forest structure) and MODIS (Gross Primary Production) are utilized to determine age. Age can be determined where disturbance can be identified directly (disturbance approach) or inferred using spectral information (recovery approach) or using inverted allometric equations to model age where there is no evidence of disturbance (allometric approach). The disturbance approach is based upon satellite data and mapped changes and is the most accurate. The recovery approach also avails upon satellite data plus logic regarding forest succession, with an accuracy that is greater than pure modeling. Given the lack of widespread recent disturbance over Canada's forests, the allometric approach is required over the greatest area (86.6%). Using information regarding realized heights and growth and yield modeling, ages are estimated where none are otherwise possible. Trees of all ages are mapped, with trees >150 years old combined in an - old tree - category.See Maltman et al. (2023) for an overview of the methods, data, image processing, as well as information on agreement assessment using Canada's National Inventory (NFI). Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C., 2023. Estimating and mapping forest age across Canada's forested ecosystems. Remote Sensing of Environment 290, 113529. ( Maltman et al. 2023).

Landsat-derived forest age for Canada 2022Satellite-based forest age map for 2022 across Canada's forested ecozones at a 30-m spatial resolution, developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). Remotely sensed data from Landsat (disturbances, surface reflectance composites, forest structure) and MODIS (Gross Primary Production) are utilized to determine age. Age can be determined where disturbance can be identified directly (disturbance approach) or inferred using spectral information (recovery approach) or using inverted allometric equations to model age where there is no evidence of disturbance (allometric approach). The disturbance approach is based upon satellite data and mapped changes and is the most accurate. The recovery approach also avails upon satellite data plus logic regarding forest succession, with an accuracy that is greater than pure modeling. Given the lack of widespread recent disturbance over Canada's forests, the allometric approach is required over the greatest area (86.6%). Using information regarding realized heights and growth and yield modeling, ages are estimated where none are otherwise possible. Trees of all ages are mapped, with trees >150 years old combined in an - old tree - category.See Maltman et al. (2023) for an overview of the methods, data, image processing, as well as information on agreement assessment using Canada's National Inventory (NFI). Maltman, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., White, J.C., 2023. Estimating and mapping forest age across Canada's forested ecosystems. Remote Sensing of Environment 290, 113529. ( Maltman et al. 2023).

This dataset shows the locations of ignition points for forest fires less than 40 hectares in size. Fires that grow larger than 40 hectares are mapped in the [Fire Disturbance Area](https://data.ontario.ca/dataset/fire-disturbance-area-firedstb) dataset. The [Forest Fire Info Map](https://www.gisapplication.lrc.gov.on.ca/ForestFireInformationMap/index.html?viewer=FFIM.FFIM&locale=en-US) shows active fires, current fire danger and restricted fire zones in place due to high fire danger.

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)