Canada Landsat Disturbance (CanLaD) – Including Forest Insect Pest

This data publication includes three map datasets:

Detailed annual disturbance maps – Forty raster layers mapping Canadian forest disturbance types from 1985 to 2024 at a 30m resolution.

Latest disturbance type and latest disturbance year maps – A simplified version for enhanced usability, consisting of three rasters that represent the most recent disturbance type and year (starting and ending).

Latest Landsat time series Julian day map – A raster capturing the latest Julian day for each pixel in the time series, where the Julian day represents the number of days elapsed since January 1, 1970.

The forest disturbance types include wildfire, harvesting, pest outbreaks, windthrow, and new water bodies.

The method is based on the summer composite Landsat time series (Guindon et al 2024). Disturbance breaks in the time series are first detected using the LandTrendr approach (Kennedy et al., 2010). Next, a one-dimensional convolutional neural network model (TempCNN; Pelletier et al., 2019) is applied with a 10-year window to classify disturbance types. The resulting maps achieve an overall accuracy of 81%. For aggregated pest/no-pest classes, the overall accuracy is 88.0% ±1.2%, with a commission error of 25.4% ±5.7% and an omission error of 63.2% ±4.3%.