Description

Wildfire Year/dNBR/Mask 1985-2015 Wildfire change magnitude 85-15. Spectral change magnitude for wildfires that occurred from 1985 and 2015. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). 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

Resources

Name	Format	Description	Link
An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites	PDF		https://doi.org/10.1016/j.rse.2014.11.005
Regional detection, characterization, and attribution of annual forest change from 1984 to 2012 using Landsat-derived time-series metrics	PDF		https://doi.org/10.1016/j.rse.2015.09.004
Three decades of forest structural dynamics over Canada's forested ecosystems using Landsat time-series and lidar plots.	PDF		https://doi.org/10.1016/j.rse.2018.07.024
Mass data processing of time series Landsat imagery: pixels to data products for forest monitoring	PDF		https://doi.org/10.1080/17538947.2016.1187673
CA_forest_wildfire_year_DNBR_Magnitude_1985_2015.zip	ZIP		https://opendata.nfis.org/downloads/forest_change/CA_forest_wildfire_year_DNBR_Magnitude_1985_2015.zip
CA_wildfire_dnbr	WMS		https://opendata.nfis.org/mapserver/cgi-bin/wms_change.cgi?request=GetCapabilities&service=WMS&version=1.3.0&layers=CA_wildfire_dnbr&legend_format=image%2Fpng&feature_info_type=text%2Fhtml
CA_wildfire_dnbr	WMS		https://opendata.nfis.org/mapserver/cgi-bin/wms_change_fra.cgi?request=GetCapabilities&service=WMS&version=1.3.0&layers=CA_wildfire_dnbr&legend_format=image%2Fpng&feature_info_type=text%2Fhtml
Satellite Forest Information for Canada (English)	HTML		https://opendata.nfis.org/mapserver/nfis-change_eng.html
Satellite Forest Information for Canada (French)	HTML		https://opendata.nfis.org/mapserver/nfis-change_fra.html
A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series	HTML		http://www.sciencedirect.com/science/article/pii/S0034425717301360

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