Modeling Watershed-Scale Historic Change in the Alpine Treeline Ecotone Using Random Forest. Issue 6 (1st November 2020)

• Record Type: Journal Article
• Authors: McCaffrey, David R.; Hopkinson, Chris
• Is Part Of: Canadian journal of remote sensing. Volume 46:Issue 6(2020)
• Page Start: 715
• Page End: 732
• Publication Date: 2020-11-01
• Subjects: Remote sensing -- Periodicals; 621.367805
• DOI: 10.1080/07038992.2020.1865792
• Languages: English
• ISSNs: 0703-8992

Abstract

Abstract: Historic changes in Alpine Treeline Ecotone were modeled using 21 topographic, climatic, geologic, and disturbance variables in a random forest model. Airborne LiDAR and oblique historic repeat photography were used to identify changes in canopy cover in the West Castle Watershed (WCW), Alberta, Canada (49.3° N, 114.4° W). A Random Forest model was trained on ∼30% of the watershed which was observable in oblique imagery, then used for a spatial extension to predict change classes in the unobserved regions of the watershed. Overall accuracy of the model was 77.3% and kappa showed moderate agreement at 0.56. The relative strength of each prediction variable was compared using permutation importance. Fire exposure, annual temperature, and annual solar radiation were the highest-ranking variables; canopy cover decreases on warm, fire-exposed aspects at high elevations, and increases on cool, non-fire-exposed aspects.