Wildfire Year/dNBR/Mask 1985-2015

Wildfire Year/dNBR/Mask 1985-2015 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 2020-04-08 Natural Resources Canada mike.wulder@canada.ca Form DescriptorsNature and EnvironmentScience and TechnologyForests 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 seriesHTML http://www.sciencedirect.com/science/article/pii/S0034425717301360 Wildfire Year/dNBR/Mask 1985-2015WMS https://opendata.nfis.org/mapserver/cgi-bin/wms_change_fra.cgi?service=wms&version=1.3.0&request=GetCapabilities&layers=wildfire_dnbr_fra&legend_format=image/png&feature_info_type=text/html CA_forest_wildfire_year_DNBR_Magnitude_1985_2015.zipZIP https://opendata.nfis.org/downloads/forest_change/CA_forest_wildfire_year_DNBR_Magnitude_1985_2015.zip Wildfire Year/dNBR/Mask 1985-2015WMS https://opendata.nfis.org/mapserver/cgi-bin/wms_change.cgi?service=wms&version=1.3.0&request=GetCapabilities&layers=wildfire_dnbr&legend_format=image/png&feature_info_type=text/html 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 monitoringPDF https://doi.org/10.1080/17538947.2016.1187673 An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance compositesPDF 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 metricsPDF https://doi.org/10.1016/j.rse.2015.09.004

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

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Electronic Mail Address: mike.wulder@canada.ca

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