The Forest Change Type data described here is an update to previously posted open data. The date range for this data is 2012 to 2015. The Forest Change Type data for the prior period from 1985 to 2011 can be found here: https://opendata.nfis.org/mapserver/nfis-change_eng.html or https://gcgeo.gc.ca/geonetwork/search/eng search for “Forest Change” but you must be logged in to see the data. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS).The 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 25 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 1985–2010 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: Hermosilla, T.,Wulder, M. A.,White, J. C.,Coops, N. C.,Hobart, G. W., (2017). Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation. 63: 104-111. DOI: 10.1016/j.jag.2017.07.013 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.

The Forest Change Type data described here is an update to previously posted open data. The date range for this data is 2012 to 2015. The Forest Change Type data for the prior period from 1985 to 2011 can be found here: https://opendata.nfis.org/mapserver/nfis-change_eng.html or https://gcgeo.gc.ca/geonetwork/search/eng search for “Forest Change” but you must be logged in to see the data. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). The 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 25 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 1985–2010 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: Hermosilla, T.,Wulder, M. A.,White, J. C.,Coops, N. C.,Hobart, G. W., (2017). Updating Landsat time series of surface-reflectance composites and forest change products with new observations. International Journal of Applied Earth Observation and Geoinformation. 63: 104-111. DOI: 10.1016/j.jag.2017.07.013 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.

Post-disturbance forest recovery data for Canada's forested ecosystems, representing a total area of ~650 million ha, captures the return of forests following wildfire and harvest that occurred between 1986 and 2012. It is developed within the framework of Canada’s National Terrestrial Ecosystem Monitoring System (NTEMS). These spatially-explicit outputs represent the rate of spectral recovery: the rate at which a pixel returns to 80% of its pre-disturbance value (White et al. 2017) within the observation period (1985-2017) using the Y2R or Years-to-Recovery metric derived from Landsat times series data. Baseline rates of spectral recovery (Y2R) were defined for each of Canada's 12 forested ecozones. These baselines were then used to identify spatial clusters of recovering pixels on the landscape where Y2R were either significantly faster or slower than their ecozonal baseline. Finally, areas that were disturbed by wildfire and harvest (1986-2012), but which had not recovered by the end of the observation period (2017) are also provided. Note that these areas are still recovering, but they had not yet recovered according to our metric of spectral recovery, by the end of the time series in 2017. For an overview of the methods, the validation of the Y2R metric, and interpretation of the derived trends, see White et al. (2022) and White et al. (2017).White, J.C., Hermosilla, T., Wulder, M.A., Coops, N.C., 2022. Mapping, validating, and interpreting spatio-temporal trends in post-disturbance forest recovery. Remote Sensing of Environment, 271, 112904. https://doi.org/10.1016/j.rse.2022.112904 ( White et al. 2022)White, J.C., Wulder, M.A., Hermosilla, T., Coops, N.C., Hobart, G.W. 2017. A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series. Remote Sensing of Environment, 194, pp. 303-321. DOI: https://doi.org/10.1016/j.rse.2017.03.035 .( White et al. 2017)

The Department of Homeland Security (MSI) supports the development of flood risk knowledge. In collaboration with Laval University and the Reunification of Quebec Basin Organizations, the MSI has developed a methodical and rigorous process for documenting floods that have an impact on the safety of people and essential goods.Thus, since 2017, the Ministry of Homeland Security (MSI) has been acquiring in certain cases data related to the water level reached when floods with proven consequences occur in southern Quebec. Maximum water levels are indicated by flood overflows.__What is a flood disaster? __A flood (flood) is characterized by a rise in water on land that is usually dry, the reaching of a peak, then a descent of water (decline). Waste forms at the beginning of the flood when the water, when withdrawing, deposits materials that were in suspension or floating. These materials (mud, seeds, twigs and other debris) constitute flood wastes or flood plains.__Marking and surveying flood plains and water levels__The marking of floodplains and water levels takes place on the ground shortly after the peak of the flood. The physical indices of the maximum water level reached (abandoned by the flood) or of the current water levels are identified and marked using permanent markers (markers). Afterwards, a land surveyor will precisely record the location and the altitude of the markers. __Point dataset “Water levels during a flood"__The “Water levels during a flood” data set contains, for each marker, the date, altitude and location (measured by a land surveyor). There are two main types of observations made in the field: the natural flood defect (line of mud, seeds or trace of water) which indicates the maximum water level reached during the flood (called MAX) and the water level observed during the field visit (called CURRENT). The list of all attributes is provided in the dataset description sheet (Additional Information section).Despite the quality of the work carried out, the Ministry of Homeland Security cannot guarantee the absence of errors in the data.__Related datasets__ The “Flood Benchmarks” dataset produced by the Ministry of Homeland Security also contains maximum water levels reached during a flood. The link to this dataset is provided in the _Documentation_ section.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

High resolution forest change for Canada (Change Type) 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

High resolution forest change for Canada (Change Year) 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

The purpose of this feature layer is to provide the 2009 overland flooding boundary in the Red River Valley.This dataset shows the extent of peak overland flooding in the Red River Valley in 20 09 . Data is based on RADARSAT – 1 satellite imagery. During processing, the raw data set was resampled to 12.5 meter pixel resolution, then classified using PCI Geomatica software which is a specialized software designed to manipulate space born imagery. The final output depicting the flooding boundary is available as a TIFF or Shapefile. Launched in November 1995, RADARSAT-1 was a Canadian-led project which provided useful information to both commercial and scientific users in such fields as disaster management, agriculture, cartography, hydrology, forestry, oceanography, ice studies and coastal monitoring. Equipped with a powerful synthetic aperture radar (SAR) instrument, it acquired images of the Earth day or night, in all weather and through cloud cover, smoke and haze. As of March 2013, the satellite was declared non-operational and is no longer collecting data. Many applications were developed to take advantage of RADARSAT-1 capacity for detecting the presence of water. These included monitoring flooding and the build-up of river ice, and mapping the melting of snow-covered areas. When used for flood monitoring, RADARSAT-1 data helped assess the impact of flooding, predicted the extent and duration of floodwaters, analyzed the environmental impact of water diversion projects, and developed flood mitigation measures. Fields Included:FID : Internal feature numberNAME : Flooded area nameAREA_SQKM : Size of flooded area

The purpose of this feature layer is to provide the 1997 overland flooding boundary in the Red River Valley.This dataset shows the extent of peak overland flooding in the Red River Valley in 1997 . Data is based on RADARSAT – 1 satellite imagery. During processing, the raw data set was resampled to 12.5 meter pixel resolution, then classified using PCI Geomatica software which is a specialized software designed to manipulate space born imagery. The final output depicting the flooding boundary is available as a TIFF or Shapefile. Launched in November 1995, RADARSAT-1 was a Canadian-led project which provided useful information to both commercial and scientific users in such fields as disaster management, agriculture, cartography, hydrology, forestry, oceanography, ice studies and coastal monitoring. Equipped with a powerful synthetic aperture radar (SAR) instrument, it acquired images of the Earth day or night, in all weather and through cloud cover, smoke and haze. As of March 2013, the satellite was declared non-operational and is no longer collecting data. Many applications were developed to take advantage of RADARSAT-1 capacity for detecting the presence of water. These included monitoring flooding and the build-up of river ice, and mapping the melting of snow-covered areas. When used for flood monitoring, RADARSAT-1 data helped assess the impact of flooding, predicted the extent and duration of floodwaters, analyzed the environmental impact of water diversion projects, and developed flood mitigation measures. Fields Included:FID : Internal feature numberNAME : Flooded area nameAREA_SQKM : Size of flooded area

The purpose of this feature layer is to provide the 2011 overland flooding boundary in the Red River Valley.This dataset shows the extent of peak overland flooding in the Red River Valley in 2011. Data is based on RADARSAT – 1 satellite imagery. During processing, the raw data set was resampled to 12.5 meter pixel resolution, then classified using PCI Geomatica software which is a specialized software designed to manipulate space born imagery.  The final output depicting the flooding boundary is available as a TIFF or Shapefile. Launched in November 1995, RADARSAT-1 was a Canadian-led project which provided useful information to both commercial and scientific users in such fields as disaster management, agriculture, cartography, hydrology, forestry, oceanography, ice studies and coastal monitoring. Equipped with a powerful synthetic aperture radar (SAR) instrument, it acquired images of the Earth day or night, in all weather and through cloud cover, smoke and haze.  As of March 2013, the satellite was declared non-operational and is no longer collecting data. Many applications were developed to take advantage of RADARSAT-1 capacity for detecting the presence of water. These included monitoring flooding and the build-up of river ice, and mapping the melting of snow-covered areas.  When used for flood monitoring, RADARSAT-1 data helped assess the impact of flooding, predicted the extent and duration of floodwaters, analyzed the environmental impact of water diversion projects, and developed flood mitigation measures. Fields Included:FID : Internal feature numberNAME : Flooded area nameAREA_SQKM : Size of flooded area

BiologicEcologic ISO Feature Dataset symbolization and publication. September 5, 2017.