Canada Landsat Disturbance (CanLaD) – 2025 Disturbance including Forest Insect Pest 2025 update, published on May 08, 2026 Please keep this “readme” file with the dataset for reference. Updated metadata and dataset updates can be found at this link: https://doi.org/10.23687/902801fd-4d9d-4df4-9e95-319e429545cc If you use this data in your research or publication, please use these citations: Dataset Perbet, P., Guindon, L., Correia D.L.P., P. Villemaire, O., Reisi Gahrouei R. St-Amant, Canada Landsat Disturbance with pest (CanLaD): a Canada-wide Landsat-based 30-m resolution product of fire, harvest and pest outbreak detection and attribution since 1985. https://doi.org/10.23687/902801fd-4d9d-4df4-9e95-319e429545cc Scientific publication Perbet, P., Guindon, L., Correia, D.L.P. et al. Historical insect disturbance maps from 1985 onwards for Canadian forests derived using earth observation data. Sci Data 12, 2012 (2025). https://doi.org/10.1038/s41597-025-06269-x - Description This dataset contains a set of raster files predicting disturbance in Canada from 1985 to 2025. The data was generated using deep learning algorithms applied to remote sensing data. The detailed methodology and data validation analyses are described in the scientific publication. The data consists of a set of raster files in GeoTIFF format, covering the entire non-arctic land mass of Canada. The raster files have a spatial resolution of 30 meters. Cartographic projection definition (WKT format) can be found in this file: _projectionDefinitionWKT_lcccan83.prj - The data is split into three sets of rasters: 1) Latest Disturbances * canlad_1985_2025_latest_type_v1_1_20260508.tif 1= Wildfire 2= Harvesting (and other human-induced disturbances) 3= Other disturbances (windthrow, partial harvesting, landslide, wildfire not confirmed by NBAC) 4= Water extension 5= Defoliation and Harvesting 6= Low severity defoliation 7= Medium severity defoliation 8= High severity defoliation * canlad_1985_2025_latest_start_year_v1_1_20260508.tif Value from 1985 to 2025 * canlad_1985_2025_latest_ending_year_v1_1_20260508.tif Value from 1985 to 2025 no data = Not disturbed or Ongoing Disturbance 2) Annual disturbance maps. 41 rasters, one for each year. canlad_annual_yyyy_v1_1_20260508.tif yyyy in filename represents year from 1985 to 2025 0= Undisturbed the current year 1= Wildfire 2= Harvesting 3= Other disturbances (windthrow, partial harvesting, landslide, wildfire not confirmed by NBAC) 4= Water extension 5= Defoliation and Harvesting 6= Low severity defoliation 7= Medium severity defoliation 8= High severity defoliation 3) Last Julian day of the time series. canlad_JJ_max.tif 2025 Update Changes: For the update of 2025, an additional post-processing step was performed to clean the annual data. The post-processing includes: (1) To limit false positives in defoliation classes, additional satellite data sources were used (Sentinel-2). (2) Correction of certain fire pixels in areas known to be heavily impacted by the hemlock looper. (3) Correction of pixels at disturbance boundaries. (4) In areas without forestry operations (the non-commercial northern part of Canada and national parks), visual inspection and correction as needed of pixels classified as forest harvesting. (5) Validation of forest fires using NBAC and visual validation across all of Canada. - Data limitations (1) For pest-related defoliation, the proposed defoliation severity classes do not directly correspond to annual aerial survey classifications. Instead, they represent the intensity of cumulative spectral change at the end of the epidemic or, for ongoing outbreaks, the most recent observed year. Contrary to aerial survey classifications, only moderate to severe cumulative defoliation levels are detected, representing a good compromise between omission and commission errors. (2) The models are aimed at insect pests that primarily affect conifers. However, they may also capture severe defoliation in mixed or deciduous forests. (3) The analysis is based on a 10-year time window to adequately capture the effects of progressive defoliation. Therefore, to properly detect a pest causing this type of defoliation, such as the spruce budworm, historical data only becomes truly relevant starting around 1995. For insects with faster defoliation, the 1990s might be considered a good starting point. (4) The wood harvesting class refers to the removal of trees, regardless of the underlying intention. It primarily includes areas intended to remain forested or to be reforested but may also encompass certain sectors converted to other uses, such as road construction, mining, or various infrastructure projects. (5) The 'other disturbances' class includes windthrow, partial harvesting, landslides, as well as fires not confirmed by the NBAC (National Burned Area Composite) database. (6) The new water body class was not formally validated in this study, though visual assessments were conducted. Users are advised to perform their own validation before use. (7) Since the summer composite considers only July and August imagery, disturbances occurring in the fall are detected the following year. For example, a wildfire that occurred in August 2023 might only become visible in the 2024 composite if the 2023 composite used images from early July, before the disturbance occurred. Additionally, cloud or shadow masking can create gaps in the time series, causing some disturbance events to appear delayed by one or two years. Users can use the national fire database (NBAC Canadian Wildland Fire Information System) for validation and year adjustments of wildfires. Moreover, the last Julians days raster could be used to better interpret the predicted year of disturbance. (8) The most recent years in the time series may have a higher commission error. These errors will be addressed in future annual updates. (9) The minimum detectable disturbance size is 1.08 hectares (12 pixels), which may limit the detection of linear disturbances such as roads. (10) Class 5 corresponds to the observation of defoliation followed by harvesting, for example, salvage logging. The severity of the defoliation is not associated with this class. For Class 5, the date indicated in the layer canlad_1985_2025_latest_start_year corresponds to the year when the defoliation began, and canlad_1985_2025_latest_ending_year corresponds to the year of the harvest. - Data Access and Usage The data is freely available for download and use. You may use this data for research or commercial purposes, but you must cite the original source of the data. The data is licensed under the Creative Commons Attribution 4.0 International license. To access and download the data, please navigate to https://doi.org/10.23687/902801fd-4d9d-4df4-9e95-319e429545cc - Contact If you have any questions or feedback about this data, please contact the authors at luc.guindon@nrcan-rncan.gc.ca