Spatial and Temporal Land Cover Change Trends in the Canadian Prairies Region from 1984-2022

Understanding landscape change and its impact on ecosystem services such as biodiversity and carbon sequestration is essential for developing effective management strategies that balance conservation and economic objectives. Reliable information on landscape change is critical for building this understanding and assessing impacts at the landscape scale. To this end, we applied a modified version of a previously developed change detection method to generate annual land cover change data across the Canadian Prairies from 1984 to 2022. The method captures from-to transitions among ten land cover classes, encompassing 90 possible change classes (excluding no-change). We assessed the accuracy of these change classes and produced summaries to identify various spatial and temporal patterns of change. Many of the change classes achieved F1 scores above 70%, indicating good model performance. Sources of error included mixed pixels, small landscape features, gradual transitions, and confusion between similar classes. The timing of detected changes was generally within +/- 1 year; however, precise reference timing is often uncertain due to gradual or complex transitions and interpretation challenges with Landsat. Change summaries reveal key trends, examples included net forest change, grassland loss, expansion of built-up areas, and conversion of wetlands and water bodies to cropland.