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.

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.

Wildfire historic incident point locations for all fire seasons before the current season. Supplied through various sources. Not to be used for legal purposes. This data includes all incidents tracked by BC Wildfire Service, ie. actual fires, suspected fires, nusiance fires, smoke chases, etc. On April 1 of each year this layer is updated with the previous fire season's data

Wildfire perimeters for all fire seasons before the current year. Supplied through various sources. Not to be used for legal purposes. These perimeters may be updated periodically during the year. On April 1 of each year the previous year's fire perimeters are merged into this dataset

Wildfire Year/dNBR/Mask 1985-2015Wildfire change magnitude 85-15. Spectral change magnitude for wildfires that occurred from 1985 and 2015. 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

Hotspots represent active wildfires. Natural Resources Canada Canadian Wild Fire Information System identifies them by processing Infrared satellite images. This layer contains the hotspots that are selected to be used as input for the Regional Air Quality Deterministic Prediction System FireWork (RAQDPS-FW) to enable forecasting air quality while taking into account wildfire emissions. Geographical coverage is Canada and the United States. The products are presented as historical annual compilations which highlight long-term trends in cumulative effects on the environment.

Hourly data collected by Alberta Environment and Parks using a mobile atmospheric monitoring laboratory (MAML) as part of emergency response monitoring during the 2016 Horse River Wildfire.

A national map of Canadian Fire Behaviour Prediction (FBP) Fuel Types (FT) developed from public data sources. The resolution of the raster grid is 30m, classified from the Spatialized Canadian National Forest Inventory (SCANFI) dataset, ecozones of Canada, and the National Burned Area Composite (NBAC). The purpose of the dataset is to characterize Canadian forests into fuel types for use in Fire Behaviour Prediction calculations as well as for situational awareness of national fire potential.

Dataset including information on wildfires in the province of Alberta from 1983 to 1995, inclusive. Information tracked for each fire includes: cause, size, location (latitude and longitude, legal land description, and forest area), time and duration, weather conditions, staffing and physical resources used to suppress the fire, and area burned.

High resolution forest change for Canada (Binary Change/No-change) 1985-2011The forest change data included in this product is national in scope (entire forested ecosystem) and represents the first wall-to-wall characterization of wildfire and harvest in Canada at a spatial resolution commensurate with human impacts. The information outcomes represent 27 years of stand replacing change in Canada’s forests, derived from a single, consistent spatially-explicit data source, derived in a fully automated manner. This demonstrated capacity to characterize forests at a resolution that captures human impacts is key to establishing a baseline for detailed monitoring of forested ecosystems from management and science perspectives. Time series of Landsat data were used to characterize national trends in stand replacing forest disturbances caused by wildfire and harvest for the period 1985–2011 for Canada's 650 million hectare forested ecosystems (https://authors.elsevier.com/sd/article/S0034425717301360 ). Landsat data has a 30m spatial resolution, so the change information is highly detailed and is commensurate with that of human impacts. These data represent annual stand replacing forest changes. The stand replacing disturbances types labeled are wildfire and harvest, with lower confidence wildfire and harvest, also shared. The distinction and sharing of lower class membership likelihoods is to indicate to users that some change events were more difficult to allocate to a change type, but are generally found to be in the correct category. For an overview on the data, image processing, and time series change detection methods applied, as well as information on independent accuracy assessment of the data, see Hermosilla et al. (2016; http://www.tandfonline.com/doi/full/10.1080/17538947.2016.1187673).The data available is, 1. a binary change/no-change; 2. Change year; and, 3. Change type. When using this data, please cite as: White, J.C., M.A. Wulder, T. Hermosilla, N.C. Coops, and G. Hobart. (2017). A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment. 192: 303-321. DOI: 10.1016/j.rse.2017.03.035. https://authors.elsevier.com/sd/article/S0034425717301360Geographic extent: Canada's forested ecosystems (~ 650 Mha)Time period: 1985–2011