This layer is the current fire year burn severity classification for large fires (greater than 100 ha). Burn severity mapping is conducted using best available pre- and post-fire satellite multispectral imagery acquired by the MultiSpectral Instrument (MSI) aboard the Sentinel-2 satellite or the Operational Land Imager (OLI) sensor aboard the Landsat-8 and 9 satellites. Every attempt is made to use cloud, smoke, shadow and snow-free imagery that was acquired prior to September 30th. However, in late fire seasons imagery acquired after September 30th may be used. This layer is considered an interim product for the 1-year-later burn severity dataset (WHSE_FOREST_VEGETATION.VEG_BURN_SEVERITY_SP). Mapping conducted during the following growing season benefits from greater post-fire image availability and is expected to be more representative of tree mortality. #### Methodology: • Select suitable pre- and post-fire imagery or create a cloud/snow/smoke-free composite from multiple images scenes • Calculate normalized burn severity ratio (NBR) for pre- and post-fire images • Calculate difference NBR (dNBR) where dNBR = pre NBR – post NBR • Apply a scaling equation (dNBR_scaled = dNBR*1000 + 275)/5) • Apply BARC thresholds (76, 110, 187) to create a 4-class image (unburned, low severity, medium severity, and high severity) • Mask out water bodies using a satellite-derived water layer • Apply region-based filters to reduce noise • Confirm burn severity analysis results through visual quality control • Produce a vector dataset and apply Euclidian distance smoothing

A Safety Feature is one of a number of various appliances/appurtenances that have been installed or constructed either alongside or as an integral part of the road infrastructure to reduce the severity or potential of accidents. It is a Point feature

Environment Canada issues weather alerts about weather related hazards in order to notify those in affected areas so that they can take steps to protect themselves and their property from harm. Alerts are classified depending on the severity and timing of the subject event and include: warnings, watches, advisories and statements. Warnings are usually issued six to 24 hours in advance, although some severe weather (such as thunderstorms and tornadoes) can occur rapidly, with less than a half hours' notice.

This data represents the dryness of the land surface based on vegetation conditions. The data is created weekly and uses weekly information on precipitation anomalies (namely the Standardized Precipitation Index or SPI) and satellite vegetation condition derived from Normalized Difference Vegetation Index (NDVI) from the MODIS Satellite. These dynamic data sets along with static data sets on land cover, soil water holding capacity, irrigation, ecozones and land surface elevation are used to model the drought severity, based on the Palmer Drought Severity Index (PDSI). The mapcubist model was trained on historical data and applied in real time to the dynamic inputs to produce drought severity ratings. The model is run at a 1km resolution and was developed by the AAFC, the United States Geological Survey and the United States Drought Monitor at the University of Nebraska Lincoln.

This feature delineates forest health disturbances which includes Abiotic and Biotic forest health agents in the Yukon at a scale of 1:100,000. It is a management level forest health overview survey (as opposed to an operational level) - meaning that analysis and mapping are most effective close to the 1:100,000 scale and not larger. This Forest Health Overview surveys has been completed in various stages: 1 ) Starting with mapping the disturbance type, and severity from the Air using Fix wing aircraft on to hardcopy 1:100,000 scale maps ; 2 ) Transfering the Data to a clean Mylar for scanning and digitizing ; and, 3 ) Scanning and digitizing and populate data into GIS spatial database .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)

The flood magnitude statistics can be used for applications such as flood plain delineation and design of hydraulic structures. The drought severity statistics can be used for applications such as water abstraction and effluent dilution.

A Linear Safety Feature is one of a number of various appliances/appurtenances that have been installed or constructed either alongside or as an integral part of the road infrastructure to reduce the severity or potential of accidents. It is a Linear feature

The fire regime describes the patterns of fire seasonality, frequency, size, spatial continuity, intensity, type (e.g., crown or surface fire) and severity in a particular area or ecosystem.The number of large fires refers to the annual number of fires greater than 200 hectares (ha) that occur per units of 100,000 ha. It was calculated per Homogeneous Fire Regime (HFR) zones. These HFR zones represent areas where the fire regime is similar over a broad spatial scale (Boulanger et al. 2014). Such zonation is useful in identifying areas with unusual fire regimes that would have been overlooked if fires had been aggregated according to administrative and/or ecological classifications.Fire data comes from the Canadian National Fire Database covering 1959–1999 (for HFR zones building) and 1959-1995 (for model building). Multivariate Adaptive Regression Splines (MARS) modeling was used to relate monthly fire regime attributes with monthly climatic/fire-weather in each HFR zone. Future climatic data were simulated using the Canadian Earth System Model version 2 (CanESM2) and downscaled at a 10 Km resolution using ANUSPLIN for two different Representative Concentration Pathways (RCP). RCPs are different greenhouse gas concentration trajectories adopted by the Intergovernmental Panel on Climate Change (IPCC) for its fifth Assessment Report. RCP 2.6 (referred to as rapid emissions reductions) assumes that greenhouse gas concentrations peak between 2010-2020, with emissions declining thereafter. In the RCP 8.5 scenario (referred to as continued emissions increases) greenhouse gas concentrations continue to rise throughout the 21st century.Provided layer: projected number of large fires (>200 ha) across Canada for the short-term (2011-2040) under the RCP 8.5 (continued emissions increases).Reference: Boulanger, Y., Gauthier, S., et al. 2014. A refinement of models projecting future Canadian fire regimes using homogeneous fire regime zones. Canadian Journal of Forest Research 44, 365–376.

The Blended Index (BI) is a model which employs multiple potential indicators of drought and excess moisture, such as the Palmer drought index, rolling precipitation amounts and soil moisture, and combines them into a weighted, normalized value between 0 and 100. The inputs and weights used in this model are subject to change periodically as it is optimized to best represent extent, duration and severity of impactful weather conditions. The blended index is deployed as two variations; short term (st) focusing on 1 to 3 months, and long term (lt) focusing on 6 months to 5 years.

The Blended Index (BI) is a model which employs multiple potential indicators of drought and excess moisture, such as the Palmer drought index, rolling precipitation amounts and soil moisture, and combines them into a weighted, normalized value between 0 and 100. The inputs and weights used in this model are subject to change periodically as it is optimized to best represent extent, duration and severity of impactful weather conditions. The blended index is deployed as two variations; short term (st) focusing on 1 to 3 months, and long term (lt) focusing on 6 months to 5 years.