Friesen, Hannah2026-04-272026-04-272026https://hdl.handle.net/1828/23732The Mountain Image Analysis Suite (MIAS) is an open-source QGIS plugin developed to generate landcover viewsheds from oblique imagery, primarily applied to high elevation alpine landscape images through the Mountain Legacy Project. This study evaluates the efficacy of MIAS on low elevation, urban imagery using historic (1908) and contemporary (2022) repeat photograph pairs taken from Pkaals (Mt. Tolmie) towards PKOLS (formerly, Mt. Douglas) in Victoria, B.C. Four of the five MIAS processing steps were applied: [1] landcover classification, [2] virtual photograph production, [3] image alignment, and [4] viewshed creation. Results indicate that while MIAS shows promise for low elevation applications, further training is required for the deep learning models to accurately identify landcover without extensive manual correction. The existing deep learning model overproduced unclassified pixels while underrepresenting key landcover categories. Large foreground trees, temporal mismatches between imagery and DEM data, and classification scale incompatibilities posed additional challenges. Despite these limitations, MIAS demonstrates potential for quantifying landcover change in low elevations with further development, particularly for analyzing historic images predating aerial photography or on landscapes with variable topography.enGISQGISlandcoverMIASlow elevationPKOLSJamie Cassels Undergraduate Research Awards (JCURA)PosterSchool of Environmental Studies