Mountain ecosystems are experiencing disproportionately greater rates of warming and ecological change globally. Snowpack has declined as much as 80% in watersheds of the western United States since 1950 due to warmer winter temperatures and changing patterns of accumulation and ablation. Earlier snowmelt and drought impact plant phenology, which can indicate tree stress, growth, reproduction, and survival. We commonly use satellite-based remote sensing to assess snow cover and vegetation phenology; however, these data products often have limited temporal and spatial resolution to analyze ecological processes and dynamics. Ground-based remote sensing can provide daily, stand-level imagery to assess vegetation phenology and snowpack dynamics. The southern Cascades of Oregon comprise the headwaters the Klamath, Rogue, Deschutes, and Santiam River Watersheds and have experienced significant declines in spring snowpack, increasing drought, and greater incidence, size, and severity of wildfires. Our team of undergraduate researchers deployed timelapse cameras at elevations of 1500-3200m from Mt. Shasta in the south to Mt. Bachelor in the north. We set them to record conifer phenology at multiple scales from close-distance stand-level to long-distance landscape scale. We used the phenopix package in program R to extract digital color numbers within polygons representing Regions of Interest (ROIs) that specify specific trees, stands, or areas of forest cover. We then obtained seasonal time series of phenology. We learned important methodological lessons regarding timing and placement of cameras and analysis.