The Natural Disturbance Type map is based on the Provincial Biodiversity Guidebook (1995) and the current and most detailed version of the approved corporate provincial Biogeoclimatic Ecosystem Classification (BEC) Zone/Subzone/Variant/Phase map (version 12, September 2, 2021) (Data Catalog record: https://catalogue.data.gov.bc.ca/dataset/bec-map). The natural disturbance type classification code is used to designate a period process or event such as insect outbreaks, fire, disease, flooding, windstorms and avalanches that cause ecosystem change and renewal. Natural disturbance type classification and mapping is used for a wide variety of applications in British Columbia. A few examples include: delineation of Natural Disturbance Types for Landscape Unit Planning; delineation of Seed Planning Zones; as an input for Predictive Ecosystem Mapping; reporting on the ecological representation of the Protected Areas Strategy; and as a level in the classification hierarchy for Broad Ecosystem Units. Note that this mapping is deliberately extended across the ocean, lakes, glaciers, etc to facilitate intersection with a terrestrial landcover layer of your choice

An opening's disturbance and silviculture activities reported into RESULTS. Most activities are within opening boundaries with the exception of broadcast treatments. An opening may have more than one activities associated with it. Activities may also overlap each other. Reporting of disturbance and silviculture attribute information is a mandatory requirement while the map is optional. This is part of the Silviculture and Land status Tracking dataset, which includes tracking harvesting and silviculture obligations on Crown Land

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.

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)      

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.

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 publication includes three map datasets:1. Detailed annual disturbance maps – Forty raster layers mapping Canadian forest disturbance types from 1985 to 2024 at a 30m resolution.2. Latest disturbance type and latest disturbance year maps – A simplified version for enhanced usability, consisting of three rasters that represent the most recent disturbance type and year (starting and ending).3. Latest Landsat time series Julian day map – A raster capturing the latest Julian day for each pixel in the time series, where the Julian day represents the number of days elapsed since January 1, 1970.The forest disturbance types include wildfire, harvesting, pest outbreaks, windthrow, and new water bodies.The method is based on the summer composite Landsat time series (Guindon et al 2024). Disturbance breaks in the time series are first detected using the LandTrendr approach (Kennedy et al., 2010). Next, a one-dimensional convolutional neural network model (TempCNN; Pelletier et al., 2019) is applied with a 10-year window to classify disturbance types. The resulting maps achieve an overall accuracy of 81%. For aggregated pest/no-pest classes, the overall accuracy is 88.0% ±1.2%, with a commission error of 25.4% ±5.7% and an omission error of 63.2% ±4.3%.## Data use constraints:1. For pest-related disturbances, the proposed defoliation severity classes do not directly correspond to annual aerial survey classifications. Instead, they represent the intensity of cumulative spectral change at the end of the epidemic or, for ongoing outbreaks, the most recent observed year. Contrary to aerial survey classifications, only moderate to severe cumulative defoliation levels are detected, representing a good compromise between omission error and commission. 2. The models are aimed at insect pests that primarily affect conifers. However, they may also capture severe defoliation in mixed or deciduous forests.3. The analysis is based on a 10-year time window to adequately capture the effects of progressive defoliation. Therefore, to properly detect a pest causing this type of defoliation, such as the spruce budworm, historical data only becomes truly relevant starting around 1995. For insects with faster defoliation, the 1990s might be considered a good starting point. 4. The wood harvesting class refers to the removal of trees, regardless of the underlying intention. It primarily includes areas intended to remain forested or to be reforested but may also encompass certain sectors converted to other uses, such as road construction, mining, or various infrastructure projects.6. The windthrow class is effective at detecting large-scale events but has a high false detection rate, particularly along the edges of harvested areas, where mixed pixels create spectral similarities with windthrow. Among all disturbance classes, windthrow has the highest error rate. 7. The new water body class was not formally validated in this study, though visual assessments were conducted. 8. Since the summer composite considers only July and August imagery, disturbances occurring in the fall are detected the following year. For example, a wildfire that occurred in August 2023 might only become visible in the 2024 composite if the 2023 composite used images from early July, before the disturbance occurred. Additionally, cloud or shadow masking can create gaps in the time series, causing some disturbance events to appear delayed by one or two years. Users can use the national fire database (NBAC Canadian Wildland Fire Information System) for validation and year adjustments of wildfires. Moreover, the last Julian days raster could be used to better interpret the predicted year of disturbance. 9. The most recent years in the time series may have a higher commission error. These errors will be addressed in future annual updates.10. The minimum detectable disturbance size is 1.08 hectares (12 pixels), which may limit the detection of linear disturbances such as roads. ## More details will be available in the future scientific publication:Perbet, P., ## Please cite this dataset as:Perbet, P., Guindon, L., Correia D.L.P., P. Villemaire, O., Reisi Gahrouei R. St-Amant, Canada Landsat Disturbance with pest (CanLaD): a Canada-wide Landsat-based 30-m resolution product of fire, harvest and pest outbreak detection and attribution since 1987. https://doi.org/10.23687/902801fd-4d9d-4df4-9e95-319e429545cc## Cited references:Guindon, Luc, Francis Manka, David L.P. Correia, Philippe Villemaire, Byron Smiley, Pierre Bernier, Sylvie Gauthier, Andre Beaudoin, Jonathan Boucher, et Yan Boulanger. 2024. « A New Approach for Spatializing the CAnadian National Forest Inventory (SCANFI) Using Landsat Dense Time Series ». Canadian Journal of Forest Research, février, cjfr-2023-0118. https://doi.org/10.1139/cjfr-2023-0118.Kennedy, Robert E., Zhiqiang Yang, et Warren B. Cohen. 2010. « Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms ». Remote Sensing of Environment 114 (12): 2897 2910. https://doi.org/10.1016/j.rse.2010.07.008.Pelletier, Charlotte, Geoffrey I. Webb, et François Petitjean. 2019. « Temporal Convolutional Neural Network for the Classification of Satellite Image Time Series ». Remote Sensing 11 (5): 523. https://doi.org/10.3390/rs11050523.

These lines represent routes within Motor Vehicle Prohibition Regulation Areas where motor vehicles are prohibited or restricted year round or seasonally. These lines were created as a visual representation of the Wildlife Act Motor Vehicle Prohibition Regulations. Under the Motor Vehicle Prohibition Regulation of the provincial Wildlife Act, motor vehicle use on crown land in B.C. may be prohibited or restricted. This data is a summary of the Motor Vehicle Prohibition Regulations, and is intended for general information purposes only. Where there is a discrepancy between these maps and the Regulations, the Motor Vehicle Prohibition Regulations are the final authority. Motor Vehicle Prohibitions (MVP) are put in place for a variety of reasons. MVPs can be used to: * protect habitat * reduce disturbance and displacement of wildlife * provide areas for hunters on foot, bike or horseback to hunt without motorized vehicles present * reduce hunter harvest while maintaining hunting opportunity   Motor vehicles include but are not limited to: * vehicles * ATVs/UTVs * snowmobiles * motorcycles * electric bikes   For full definitions and detailed regulations, visit the Motor Vehicle Prohibition Regulations website (available under Related Links). There are 2 types of motor vehicle restrictions under the Wildlife Act, and all types can be seasonal or year-round. 1. **Motor Vehicle Closed Area** (formerly referred to as Access Management Areas (AMAs): Prohibits the use or operation of a motor vehicle and e-bike. These prohibitions can be for all motor vehicles, or specific to ATVs/e-bikes or snowmobiles. 2. **Motor Vehicle Hunting Closed Area**: The operation of motor vehicles and e-bikes to hunt, transport wildlife, transport equipment and supplies which are intended for or in support of hunting, or transport hunters to and from the location of wildlife is prohibited. These prohibitions can apply to all motor vehicles, or be specific to ATVs/e-bikes or snowmobiles.

These polygons represent areas across the Province where motor vehicles are prohibited or restricted year round or seasonally. These areas were created as a visual representation of the Wildlife Act Motor Vehicle Prohibition Regulations. Under the Motor Vehicle Prohibition Regulation of the provincial Wildlife Act, motor vehicle use on crown land in B.C. may be prohibited or restricted. This data is a summary of the Motor Vehicle Prohibition Regulations, and is intended for general information purposes only. Where there is a discrepancy between these maps and the Regulations, the Motor Vehicle Prohibition Regulations are the final authority. Motor Vehicle Prohibitions (MVP) are put in place for a variety of reasons. MVPs can be used to: * protect habitat * reduce disturbance and displacement of wildlife * provide areas for hunters on foot, bike or horseback to hunt without motorized vehicles present * reduce hunter harvest while maintaining hunting opportunity   Motor vehicles include but are not limited to: * vehicles * ATVs/UTVs * snowmobiles * motorcycles * electric bikes   For full definitions and detailed regulations, visit the Motor Vehicle Prohibition Regulations website (available under Related Links). There are 2 types of motor vehicle restrictions under the Wildlife Act, and all types can be seasonal or year-round. 1. **Motor Vehicle Closed Area** (formerly referred to as Access Management Areas (AMAs): Prohibits the use or operation of a motor vehicle and e-bike. These prohibitions can be for all motor vehicles, or specific to ATVs/e-bikes or snowmobiles. 2. **Motor Vehicle Hunting Closed Area**: The operation of motor vehicles and e-bikes to hunt, transport wildlife, transport equipment and supplies which are intended for or in support of hunting, or transport hunters to and from the location of wildlife is prohibited. These prohibitions can apply to all motor vehicles, or be specific to ATVs/e-bikes or snowmobiles.

The data layer identifies areas of disturbance to vegetation including burns, commercial forestry harvesting (cuts), weather events, infrastructure and pest/disease. Instructions for downloading this dataset: This product requires the use of geographic information system (GIS) software.