Wildfire Year/dNBR/Mask 1985-2015

Wildfire 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

Date ( RI_367 ): 2020

Date ( RI_366 ): 2020

RI_415

Government of Canada; Natural Resources Canada; Canadian Forest Service, Pacific Forestry Centre, Forest Geomatics - Dr. M.A.Wulder ( Research Scientist )

506 Burnside Road West , Victoria , British Columbia , V8R 2E4 , Canada

(250) 363-0600
(250) 363-6004
https://cfs.nrcan.gc.ca/employes/vue/mwulder

Hours of service: email only please

Status: onGoing; enContinue RI_596

Maintenance and update frequency: asNeeded; auBesoin RI_540

Government of Canada Core Subject Thesaurus Thésaurus des sujets de base du gouvernement du Canada ( RI_528 )

Forests

Use limitation: Open Government Licence - Canada (http://open.canada.ca/en/open-government-licence-canada)

Access constraints: otherRestrictions; autresRestrictions RI_609

Use constraints: intellectualPropertyRights; droitsPropriétéIntellectuelle RI_607

Other constraints: The data represents stand replacing disturbances that occurred between 1985 and 2011. Other changes may be present that are not portrayed here. To avoid confusion in areas with dynamic agricultural land use, an agricultural mask was used in the change detection process. Therefore, changes near agricultural areas may not be captured due to use of this exclusionary mask. An image compositing window of August 1 ± 30 days was used to generate the best-available-pixel (BAP) image composites used as the source data for change detection and attribution. As a result, changes occurring after August 31 may not always be mapped to the correct year; however a national independent accuracy assessment indicated that 97.7% of changes were labelled to within ± 1 year (Hermosilla et al. 2016; http://www.tandfonline.com/doi/full/10.1080/17538947.2016.118767 )